CN117769745A

CN117769745A - Method and system for providing exercise program to user

Info

Publication number: CN117769745A
Application number: CN202280051795.1A
Authority: CN
Inventors: 金成喆; 金暻禄; 徐基弘; 林福万
Original assignee: Samsung Electronics Co Ltd
Current assignee: Samsung Electronics Co Ltd
Priority date: 2021-10-15
Filing date: 2022-10-17
Publication date: 2024-03-26

Abstract

The electronic device according to the embodiment may obtain an exercise program to be provided to the user based on target exercise information that has been set before exercise and a current value for a gait evaluation item and a target value thereof, and provide the exercise program to the user through the wearable device.

Description

Method and system for providing exercise program to user

Technical Field

Example embodiments relate to a technique for providing an exercise program to a user.

Background

With the start of an aging society, more and more people experience inconvenience and pain in walking due to weakening of muscle strength or joint problems caused by aging, and there is growing interest in a walking aid that enables the aged with reduced muscle strength or patients with discomfort in muscle joints to walk easily.

Disclosure of Invention

Technical object

According to an example embodiment, a system for providing various exercise programs to a user through a wearable device may be provided.

However, the technical aspects are not limited to the foregoing aspects, and other technical aspects may exist.

According to an example embodiment, there may be provided an electronic device including: a communication module (including a communication circuit) configured to exchange data with an external device; and at least one processor configured to control the electronic device, wherein the at least one processor is configurable to: receiving target exercise information from a user of the electronic device, the target exercise information including target exercise time information and target exercise interval information; based on the target exercise information and the current value of the gait evaluation item, an optimal value of a control parameter capable of satisfying a preset target value of the evaluation item is determined, the control parameter being a parameter for adjusting at least one of: the magnitude, direction and timing of the torque, the angle of offset between joint angles, or the sensitivity of the state factor to the joint angles; acquiring one or more recommended exercise programs based on the optimal values of the control parameters; determining a target exercise program of the one or more recommended exercise programs; transmitting information about the target exercise program to a wearable device worn by the user; receiving sensing information from the wearable device while the target exercise program is being executed by the wearable device; and providing feedback information to the user based on the sensed information when the target exercise program is executed.

The gait assessment items may include one or more of a step size, a gait speed, a gait symmetry and a gait rhythm.

The processor may obtain a current value of the gait evaluation item based on previous sensed information obtained when the user performed a previous exercise program.

The processor may transmit information about a test exercise program for obtaining a current value of a gait evaluation item to the wearable device, receive test sensing information from the wearable device while executing the test exercise program, and obtain the current value of the gait evaluation item based on the test sensing information.

The processor may determine an optimal value of the control parameter such that a target value of the gait evaluation item can be satisfied within a range satisfying a set objective function.

The processor may send the optimal value of the control parameter to a server and receive from the server one or more recommended exercise programs determined by the server based on the optimal value of the control parameter.

The processor may determine one or more recommended exercise programs corresponding to the optimal value among a plurality of stored exercise programs.

The processor may determine the one or more recommended exercise programs corresponding to the optimal value among a plurality of stored exercise programs based on a history of exercise programs performed by the user.

The information about the target exercise program may include values of control parameters during the target exercise time.

The processor may determine whether a target value of the evaluation item is satisfied based on the sensing information, determine an action required to satisfy the target value when the target value is not satisfied, and provide the feedback information including the required action to the user.

The processor may send the feedback information to an additional electronic device, and the feedback information may be output by the additional electronic device.

The additional electronic device may be, for example, but not limited to, any one of a headset, a glasses-type electronic device, or a watch-type electronic device.

The processor may receive the heart rate of the user from the additional electronic device as the sensed information.

The target exercise section information may include information about a start point, an end point, and a detailed route between the start point and the end point.

In response to the target exercise program being performed normally, an estimated gait age may be provided to the user.

The target value of the gait evaluation item may be set based on a target exercise target selected by a user among a plurality of exercise targets.

The plurality of exercise goals may include two or more of improving gait ability, improving gait posture, improving cardiovascular health and improving muscle strength.

According to an example embodiment, a method performed by an electronic device may be provided, wherein the method may comprise: receiving target exercise information from a user of the electronic device, the target exercise information including target exercise time information and target exercise interval information; determining an optimal value of a control parameter capable of satisfying a preset target value of a gait evaluation item based on the target exercise information and a current value of the gait evaluation item, the control parameter being a parameter for adjusting at least one of: sensitivity of the offset angle or state factor between the magnitude, direction and timing of torque to the joint angle; acquiring one or more recommended exercise programs based on the optimal values of the control parameters; determining a target exercise program of the one or more recommended exercise programs; transmitting information about the target exercise program to a wearable device worn by the user; receiving sensing information from the wearable device while the target exercise program is being executed by the wearable device; and providing feedback information to the user regarding the execution of the target exercise program based on the sensed information.

According to an example embodiment, a server may be provided, which may include: a communication module (including a communication circuit) configured to exchange data with an external device; and at least one processor configured to control the server, wherein the at least one processor is configurable to: receiving, from the electronic device, an optimal value of a control parameter, the control parameter being a parameter for adjusting at least one of: the magnitude, direction and timing of the torque, the angle of offset between the joint angles, or the sensitivity of the state factor to the joint angle; determining one or more recommended exercise programs from a plurality of exercise programs stored in the server based on the optimal value of the control parameter; and transmitting the one or more recommended exercise programs to the electronic device.

The processor may receive, from the electronic device, sensory information received by the electronic device from the wearable device while the wearable device connected to the electronic device is executing a target exercise program of the one or more recommended exercise programs, and store the target exercise program and the sensory information in association with an account of the user.

Advantageous effects

According to certain example embodiments, a system for providing various exercise programs to a user via a wearable device may be provided.

According to some example embodiments, even when a user repeatedly performs exercises in the same exercise interval, a user wearing a wearable device may feel as if the corresponding exercise interval is a different exercise interval by performing different exercise programs a plurality of times.

Drawings

FIG. 1 is a diagram illustrating a system for providing an exercise program to a user according to an example embodiment;

FIG. 2 is a block diagram illustrating an electronic device in a network environment according to an example embodiment;

fig. 3a to 3d are diagrams illustrating a wearable device according to an embodiment;

fig. 4 is a diagram illustrating a wearable device in communication with an electronic device according to an example embodiment;

fig. 5 and 6 are diagrams illustrating a method of outputting torque by a wearable device, according to some example embodiments;

FIG. 7 is a block diagram illustrating optimization of parameter values of a wearable device according to an example embodiment;

FIG. 8 is a flowchart illustrating a method of providing an exercise program to a user according to an example embodiment;

FIG. 9 is a flowchart illustrating a method of obtaining a current value of a gait evaluation item in accordance with an example embodiment;

FIG. 10 is a flowchart illustrating a method of determining an optimal value of a control parameter according to an example embodiment;

FIG. 11 is a diagram illustrating a method of determining a recommended exercise program based on target exercise information according to an example embodiment;

FIG. 12 is a flowchart illustrating a method of acquiring a recommended exercise program through a server according to an example embodiment;

FIG. 13 is a flowchart illustrating a method of providing feedback information to a user according to an example embodiment; and

fig. 14 is a diagram showing a configuration of a server according to an example embodiment.

Detailed Description

Hereinafter, various exemplary non-limiting embodiments of the present disclosure will be described with reference to the accompanying drawings. However, this is not intended to limit the disclosure to the particular embodiments and should be understood to include various modifications, equivalents, and/or alternatives to the embodiments.

Fig. 1 is a diagram illustrating a system for providing an exercise program to a user according to an example embodiment.

According to an example embodiment, a system for providing an exercise program to a user may include an electronic device 110, a wearable device 120, an add-on device 130, and a server 140.

According to an example embodiment, the electronic device 110 may be a user terminal connectable to the wearable device 120 using short range wireless communication. For example, the electronic device 110 may send a control signal to the wearable device 120 for controlling the wearable device 120. The electronic device 110 will be described in detail below with reference to fig. 2, and transmission of control signals will be described in detail below with reference to fig. 4.

According to example embodiments, the wearable device 120 may provide an assisting force assisting walking or a resistance obstructing walking to a user wearing the wearable device 120. Resistance may be provided to the user to assist the user in performing the exercise. By controlling the values of the various control parameters used in the wearable device 120, the assist force or resistance output by the wearable device 120 can be controlled. The structure and driving method of the wearable device 120 will be described in detail with reference to fig. 3a to 7.

According to an example embodiment, the electronic device 110 may be directly or indirectly connected to the additional device 130 (e.g., the wireless headset 131, the smart watch 132, or the smart glasses 133) using short-range wireless communication. For example, the electronic device 110 may output information indicating the state of the electronic device 110 or the state of the wearable device 120 to the user through the additional device 130. For example, feedback information about the walking state of the user wearing the wearable device 120 may be output through the haptic device, the speaker device, and the display device of the additional device 130.

According to an example embodiment, the electronic device 110 may connect to the server 140 directly or indirectly using short range wireless communication or cellular communication. For example, server 140 may include a database in which information regarding a plurality of exercise programs that may be provided to a user via wearable device 120 is stored. For example, the server 140 may manage a user account for the electronic device 110 or a user of the wearable device 120. Server 140 may store and manage exercise programs performed by the user and the results of the exercise programs in association with the user account. An example configuration of the server 140 will be described in detail below with reference to fig. 14.

According to an example embodiment, the system may provide an exercise program to a user to achieve exercise goals in various exercise environments desired by the user. For example, the user's exercise goals may be preset and may include, for example, improving gait ability, improving gait posture, improving cardiovascular health and improving muscle strength. Based on the exercise goal, the user may specify a predetermined exercise environment each time an exercise is performed. For example, the user may designate the target exercise interval and the target exercise time as an exercise environment through the electronic device 110 before performing the exercise. Electronic device 110 may determine a value of a control parameter of wearable device 120 that may satisfy the exercise environment based on the set exercise goal. For example, the control parameters may include parameters for adjusting at least one of: the magnitude, direction, or timing of the torque to be output by the wearable device 120, the offset angle between the joint angles of the wearable device 120, and the sensitivity of the state factor to the joint angle. Electronic device 110 may obtain one or more exercise programs based on the determined values of the control parameters.

According to an example embodiment, the exercise program may relate to a method of providing an assist force or resistance provided to a user wearing wearable device 120 in a set exercise environment. For example, the exercise program may provide the user with the same assistance force or the same resistance throughout the exercise time. In another example, the exercise program may divide the entire exercise time into a plurality of intervals, and provide different assisting forces or resistances to the user in the plurality of intervals. For example, the output timing of the assist force or resistance outputted by the exercise program may vary according to the target exercise time and the exercise target.

According to an example embodiment, a plurality of exercise programs may be converted into a database and stored in electronic device 110 or server 140. For example, electronic device 110 or server 140 may recommend one or more of a plurality of exercise programs to the user based on the determined values of the control parameters. For example, electronic device 110 or server 140 may determine an exercise program to recommend to the user based on the history of exercises performed by the user. Accordingly, even when the user exercises in the same exercise environment, a new exercise program can be recommended to the user, and the user can feel as if they were performing an exercise different from the existing exercise by executing the new exercise program.

A method of providing an exercise program to a user will be described in detail with reference to fig. 8 to 13.

Fig. 2 is a block diagram illustrating an electronic device in a network environment according to an embodiment.

Fig. 2 is a block diagram illustrating an electronic device 201 in a network environment 200 according to an embodiment. Referring to fig. 2, an electronic device 201 in a network environment 200 may communicate with an electronic device 202 via a first network 298 (e.g., a short-range wireless communication network) or with at least one of an electronic device 204 or a server 208 via a second network 299 (e.g., a long-range wireless communication network). According to an example embodiment, the electronic device 201 may communicate with the electronic device 204 via a server 208. According to an example embodiment, the electronic device 201 may include a processor 220, a memory 230, an input module 250, a sound output module 255, a display module 260, an audio module 270, a sensor module 276, an interface 277, a connection 278, a haptic module 279, a camera module 280, a power management module 288, a battery 289, a communication module 290, a Subscriber Identity Module (SIM) 296, or an antenna module 297. In some embodiments, at least one of the components (e.g., connection end 278) may be omitted from electronic device 201, or one or more other components may be added to electronic device 201. In some embodiments, some of the components (e.g., the sensor module, the camera module 280, or the antenna module 297) may be implemented as a single component (e.g., the display module 260). Each antenna module herein includes at least one antenna, and each sensor module herein includes circuitry and/or at least one sensor.

The processor 220 may run, for example, software (e.g., program 240) to control at least one other component of the electronic device 201 (e.g., a hardware component or a software component) that is directly or indirectly connected to the processor 220, and may perform various data processing or calculations. According to an example embodiment, as at least part of the data processing or calculation, the processor 220 may store commands or data received from another component (e.g., the sensor module 276 or the communication module 290) into the volatile memory 232, process the commands or data stored in the volatile memory 232, and store the resulting data in the nonvolatile memory 234. According to an example embodiment, the processor 220 may include a main processor 221 (e.g., a Central Processing Unit (CPU) or an Application Processor (AP)) or an auxiliary processor 223 (e.g., a Graphics Processing Unit (GPU), a Neural Processing Unit (NPU), an Image Signal Processor (ISP), a sensor hub processor, or a Communication Processor (CP)) that is operatively independent or combined with the main processor 221. For example, when the electronic device 201 comprises a main processor 221 and an auxiliary processor 223, the auxiliary processor 223 may be adapted to consume less power than the main processor 221 or to be dedicated to a specific function. The auxiliary processor 223 may be implemented separately from the main processor 221 or as part of the main processor 221.

The auxiliary processor 223 (rather than the main processor 221) may control at least some of the functions or states associated with at least one of the components of the electronic device 2012 (e.g., the display module 260, the sensor module 276, or the communication module 290) when the main processor 221 is in an inactive (e.g., sleep) state, or the auxiliary processor 223 may control at least some of the functions or states associated with at least one of the components of the electronic device 201 (e.g., the display module 260, the sensor module 276, or the communication module 290) with the main processor 221 when the main processor 221 is in an active state (e.g., running an application). According to an example embodiment, the auxiliary processor 223 (e.g., ISP or CP) may be implemented as part of another component (e.g., camera module 280 or communication module 290) functionally associated with the auxiliary processor 223. According to an example embodiment, the auxiliary processor 223 (e.g., NPU) may include hardware architecture dedicated to Artificial Intelligence (AI) model processing. AI models may be generated by machine learning. Machine learning may be performed by, for example, the electronic device 201 performing artificial intelligence, or via a separate server (e.g., server 208). The learning algorithm may include, but is not limited to, for example, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning algorithms. The AI model may include a plurality of artificial neural network layers. The artificial neural network may include, for example, a Deep Neural Network (DNN), a Convolutional Neural Network (CNN), a Recurrent Neural Network (RNN), a boltzmann machine limited (RBM), a Deep Belief Network (DBN), a bi-directional recurrent deep neural network (BRDNN), a deep Q network, or a combination of two or more thereof, but is not limited thereto. Additionally or alternatively, the AI model may include software structures in addition to hardware structures.

The memory 230 may store various data used by at least one component of the electronic device 201 (e.g., the processor 220 or the sensor module 276). The various data may include, for example, software (e.g., program 240) and input data or output data for commands associated therewith. Memory 230 may include volatile memory 232 or nonvolatile memory 234.

Program 240 may be stored as software in memory 230 and program 240 may include, for example, an Operating System (OS) 242, middleware 244, or applications 246.

The input module 250 may receive commands or data from outside the electronic device 201 (e.g., a user) to be used by other components of the electronic device 201 (e.g., the processor 220). The input device 250 may include, for example, a microphone, a mouse, a keyboard, keys (e.g., buttons) or a digital pen (e.g., a stylus), and typically includes input circuitry.

The sound output module 255 may output a sound signal to the outside of the electronic device 201. The sound output module 255 may include, for example, a speaker or a receiver. Speakers may be used for general purposes such as playing multimedia or playing a record. The receiver may be used to receive an incoming call. According to example embodiments, the receiver may be implemented separately from the speaker or as part of the speaker.

The display module 260, including a display, may visually provide information to an outside (e.g., a user) of the electronic device 201. The display module 260 may include, for example, a display, a holographic device, or a projector, and control circuitry for controlling a respective one of the display, the holographic device, and the projector. According to an example embodiment, the display module 260 may include a touch sensor adapted to detect a touch or a pressure sensor adapted to measure the intensity of a force caused by a touch.

The audio module 270 may convert sound into electrical signals and vice versa. According to an example embodiment, the audio module 270 may obtain sound via the input module 250, or output sound via the sound output module 255 or an external electronic device (e.g., the electronic device 202 such as a speaker and headphones) that is directly (e.g., wired) or wirelessly connected with the electronic device 201.

The sensor module 276 may detect an operational state (e.g., power or temperature) of the electronic device 201 or an environmental state (e.g., a state of a user) external to the electronic device 201 and then generate an electrical signal or data value corresponding to the detected state. According to example embodiments, the sensor module 276 may include, for example, a gesture sensor, a gyroscope sensor, an atmospheric pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a proximity sensor, a color sensor, an Infrared (IR) sensor, a biometric sensor, a temperature sensor, a humidity sensor, or an illuminance sensor.

Interface 277 may support one or more specific protocols that will be used to connect electronic device 201 directly (e.g., wired) or wirelessly with an external electronic device (e.g., electronic device 202). According to an embodiment, interface 277 may include, for example, a high-definition multimedia interface (HDMI), a Universal Serial Bus (USB) interface, a Secure Digital (SD) card interface, or an audio interface.

The connection terminals 278 may include connectors via which the electronic device 201 may be physically connected with an external electronic device (e.g., the electronic device 202). According to example embodiments, the connection end 278 may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (e.g., a headphone connector).

The haptic module 279 may convert the electrical signal into mechanical stimulus (e.g., vibration or motion) or electrical stimulus that can be recognized by the user via his sense of touch or kinesthetic sense. According to an example embodiment, the haptic module 279 may include, for example, a motor, a piezoelectric element, or an electrostimulator.

The camera module 280 may capture still images or moving images. According to an example embodiment, the camera module 280 may include one or more lenses, an image sensor, an image signal processor, or a flash.

The power management module 288 may manage power supplied to the electronic device 201. According to an example embodiment, the power management module 288 may be implemented as at least part of, for example, a Power Management Integrated Circuit (PMIC).

Battery 289 may power at least one component of electronic device 201. According to an example embodiment, battery 289 may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.

The communication module 290 may support establishing a direct (e.g., wired) communication channel or a wireless communication channel between the electronic device 201 and an external electronic device (e.g., the electronic device 202, the electronic device 204, or the server 208) and performing communication via the established communication channel. The communication module 290 may include one or more communication processors capable of operating independently of the processor 220 (e.g., an Application Processor (AP)) and supporting direct (e.g., wired) or wireless communication. According to an example embodiment, the communication module 290 may include a wireless communication module 292 (e.g., a cellular communication module, a short-range wireless communication module, or a Global Navigation Satellite System (GNSS) communication module) or a wired communication module 294 (e.g., a Local Area Network (LAN) communication module or a Power Line Communication (PLC) module). A respective one of these communication modules may be connected via a first network 298 (e.g., a short-range communication network such as bluetooth ^TM Wireless fidelity (Wi-Fi) direct or infrared data association (IrDA)) or a second network 299 (for exampleFor example, a long-range communication network, such as a conventional cellular network, a 5G network, a next-generation communication network, the internet, or a computer network (e.g., a LAN or Wide Area Network (WAN)), communicates with external electronic devices. These various types of communication modules may be implemented as a single component (e.g., a single chip), or may be implemented as multiple components (e.g., multiple chips) separate from each other. The wireless communication module 292 can identify and authenticate the electronic device 201 in a communication network, such as the first network 298 or the second network 299, using user information (e.g., an International Mobile Subscriber Identity (IMSI)) stored in the user identification module 296.

The wireless communication module 292 may support a 5G network following a 4G network and next generation communication technologies (e.g., new Radio (NR) access technologies). NR access technologies may support enhanced mobile broadband (eMBB), large-scale machine type communication (mctc), or ultra-reliable and low-latency communication (URLLC). The wireless communication module 292 may support high frequency bands (e.g., millimeter-wave bands) to achieve, for example, high data transmission rates. The wireless communication module 292 may support various techniques for ensuring performance over high frequency bands such as, for example, beamforming, massive multiple-input multiple-output (MIMO), full-dimensional MIMO (FD-MIMO), array antennas, analog beamforming, or massive antennas. The wireless communication module 292 may support various requirements specified in the electronic device 201, an external electronic device (e.g., electronic device 204), or a network system (e.g., second network 299). According to an example embodiment, the wireless communication module 292 may support a peak data rate (e.g., 20Gbps or greater) for implementing an eMBB, a lost coverage (e.g., 164dB or less) for implementing an emtc, or a U-plane delay (e.g., a round trip of 0.5ms or less, or 1ms or less for each of the Downlink (DL) and Uplink (UL)) for implementing a URLLC.

The antenna module 297 may transmit signals or power to or receive signals or power from the outside of the electronic device 201 (e.g., an external electronic device). According to an example embodiment, the antenna module 297 may include an antenna including a radiating element including a conductive material or conductive pattern formed in or on a substrate (e.g., a Printed Circuit Board (PCB)). According to an example embodiment, the antenna module 297 may include multiple antennas (e.g., an array antenna). In this case, at least one antenna of a communication scheme suitable for use in a communication network such as first network 298 or second network 299 may be selected from a plurality of antennas by, for example, communication module 290. Signals or power may be transmitted or received between the communication module 290 and an external electronic device via at least one selected antenna. According to example embodiments, another component other than a radiating element, such as a Radio Frequency Integrated Circuit (RFIC), may additionally be formed as part of the antenna module 297.

According to an example embodiment, antenna module 297 may form a millimeter wave antenna module. According to example embodiments, a millimeter wave antenna module may include a PCB, an RFIC disposed on or adjacent to a first surface (e.g., a bottom surface) of the PCB and capable of supporting a specified high frequency band (e.g., millimeter wave band), and a plurality of antennas (e.g., array antennas) disposed on or adjacent to a second surface (e.g., a top surface or a side surface) of the PCB and capable of transmitting or receiving signals in the specified high frequency band.

At least some of the above components may be interconnected via an inter-peripheral communication scheme (e.g., bus, general Purpose Input and Output (GPIO), serial Peripheral Interface (SPI), or Mobile Industrial Processor Interface (MIPI)) and exchange signals (e.g., commands or data) therebetween.

According to an example embodiment, commands or data may be sent or received between the electronic device 201 and the external electronic device 204 via the server 208 connected to the second network 299. Each of the external electronic devices (e.g., electronic device 202 and/or electronic device 204) may be the same type or a different type of device than electronic device 201. According to example embodiments, all or some of the operations to be performed by electronic device 201 may be performed at one or more external electronic devices (e.g., external devices 202 and/or 204 and server 208). For example, if the electronic device 201 needs to automatically perform a function or service, or in response to a request from a user or another device, the electronic device 201 may request one or more external electronic devices to perform at least a portion of the function or service instead of or in addition to the function or service, or the electronic device 201 may request one or more external electronic devices to perform at least a portion of the function or service. The one or more external electronic devices that receive the request may perform at least part of the function or service, or additional functions or additional services related to the request, and may transmit the result of the execution to the electronic device 201. The electronic device 201 may provide the results as at least a portion of the response to the request with or without further processing of the results. To this end, for example, cloud computing, distributed computing, mobile Edge Computing (MEC), or client-server computing techniques may be used. The electronic device 201 may provide ultra-low latency services using, for example, distributed computing or MEC. In example embodiments, the external electronic devices (e.g., electronic devices 202 and/or 204) may include internet of things (IoT) devices. Server 208 may be an intelligent server using machine learning and/or neural networks. According to an example embodiment, the external electronic device 204 or the server 208 may be included in the second network 299. The electronic device 201 may be applied to smart services (e.g., smart home, smart city, smart car, or healthcare) based on 5G communication technology or IoT-related technology.

The electronic device according to the embodiment may be one of various types of electronic devices. The electronic device may include, for example, a portable communication device (e.g., a smart phone), a computer device, a portable multimedia device, a portable medical device, a camera, a wearable device, or a household appliance device. According to the embodiment, the electronic device is not limited to those described above.

It should be understood that the various embodiments of the disclosure and the terminology used therein are not intended to limit the technical features set forth herein to the particular embodiments, but rather include various modifications, equivalents or alternatives to the corresponding embodiments. The same reference numbers may be used for similar or related elements throughout the description taken in conjunction with the drawings. It is to be understood that the singular form of a noun corresponding to an item may include one or more things unless the context clearly indicates otherwise. As used herein, "a or B", "at least one of a and B", "at least one of a or B", "at least one of A, B or C", "A, B and C", and "A, B or C", each of which may include any one of the items listed together in a corresponding one of the phrases, or all possible combinations thereof. Terms such as "1 st", "2 nd", or "first" or "second" may be used simply to distinguish a component in question from other components and to not limit the component in other respects (e.g., importance or order). It will be understood that if an element (e.g., a first element) is referred to as being "coupled to," "connected to," or "connected to" another element (e.g., a second element) with or without the term "operatively" or "communicatively," it can be directly (e.g., via a cable), wirelessly, or via at least a third element.

As used in connection with various embodiments, the term "module" may include units implemented in hardware, software, or firmware, and may be used interchangeably with other terms (e.g., "logic," "logic block," "component," or "circuit"). A module may be a single integrated component or a minimal unit or portion thereof adapted to perform one or more functions. For example, according to an example embodiment, a module may be implemented in the form of an Application Specific Integrated Circuit (ASIC).

Various embodiments of the present disclosure as set forth herein may be implemented as software (e.g., program 240) comprising one or more instructions stored on a storage medium (e.g., internal memory 236 or external memory 238) readable by a machine (e.g., electronic device 201). For example, a processor (e.g., processor 220) of a machine (e.g., electronic device 201) may invoke at least one of one or more instructions stored in a storage medium and execute it. This allows the machine to be operated to perform at least one function in accordance with the at least one instruction invoked. The one or more instructions may include code generated by a compiler or code executable by an interpreter. The machine-readable storage medium may be provided in the form of a non-transitory storage medium. Here, the term "non-transitory" simply means that the storage medium is a tangible device and does not include a signal (e.g., electromagnetic waves), but the term does not distinguish between data being semi-permanently stored in the storage medium and data being temporarily stored in the storage medium. .

According to example embodiments, methods according to various embodiments of the present disclosure may be included and provided in a computer program product. The computer program product may be used as a product for conducting transactions between sellers and buyers. The computer program product may be distributed in the form of a machine-readable storage medium, such as a compact disk read only memory (CD-ROM), or may be distributed via an application Store (e.g., a Play Store ^TM ) The computer program product may be published (e.g., downloaded or uploaded) online, or may be distributed (e.g., downloaded or uploaded) directly between two user devices (e.g., smartphones). At least some of the computer program product may be temporarily generated if published online, or at least some of the computer program product may be stored at least temporarily in a machine readable storage medium, such as the memory of a manufacturer's server, an application store's server, or a forwarding server.

According to embodiments, each of the above-described components (e.g., a module or a program) may include a single entity or a plurality of entities, and some of the plurality of entities may be separately provided in different components. Depending on the embodiment, one or more of the above components may be omitted, or one or more other components may be added. Alternatively or additionally, multiple components (e.g., modules or programs) may be integrated into a single component. In this case, according to an embodiment, the integrated component may still perform the one or more functions of each of the plurality of components in the same or similar manner as the corresponding one of the plurality of components performed the one or more functions prior to integration. According to embodiments, operations performed by a module, a program, or another component may be performed sequentially, in parallel, repeatedly, or in a heuristic manner, or one or more of the operations may be performed in a different order or omitted, or one or more other operations may be added.

Fig. 3a to 3d are diagrams illustrating a wearable device according to an embodiment.

Referring to fig. 3 a-3 d, a wearable device 300 (e.g., wearable device 120 of fig. 1) may be worn by a user to assist in user gait. For example, wearable device 300 may be a device that assists a user in walking. Further, wearable device 300 may be an exercise device that assists a user in walking and provides exercise functionality by providing resistance to the user. For example, a resistance force (such as a force output by a device such as a motor) provided to a user may be actively applied to the user. In another example, a resistance force (such as a friction force) may not be actively applied to the user, but may hinder movement of the user. Resistance may be referred to as exercise load.

Although fig. 3a to 3d illustrate the wearable device 300 as a hip type, the type of the wearable device is not limited thereto, and the wearable device may be of a type supporting all lower limbs or a type supporting a part of lower limbs. In addition, the wearable device may be any one of a form supporting a part of a lower limb, a form supporting an ankle, and a form supporting the entire body.

The embodiments described with reference to fig. 3a to 3d may be applied to a hip type, but are not limited thereto, and may be applied to various types of wearable devices.

According to an example embodiment, the wearable device 300 may include a driver 310, a sensor 320 (e.g., 321 and/or 321-1 in fig. 3 c-3 d), an Inertial Measurement Unit (IMU) 330, a controller 340, a battery 350, and a communication module 352 including communication circuitry. For example, the IMU330 and the controller 340 may be disposed in a main frame of the wearable device 300. In another example, the IMU330 and the controller 340 may be included in a housing (not shown) formed outside of (or attached to) the main frame of the wearable device 300. Each "module" herein may include circuitry.

The driver 310 may include a motor 314 and a motor driver circuit 312 for driving the motor 314. The sensor 320 may include at least one sensor 321. The controller 340 may include a processor 342, a memory 344, and an input interface 346. Although only one sensor 321, one motor driver circuit 312, and one motor 314 are shown in fig. 3c, this is provided as an example only, and according to another example as shown in fig. 3d, a wearable device (e.g., wearable device 300-1) may include a plurality of sensors 321 and 321-1, a plurality of motor driver circuits 312 and 312-1, and a plurality of motors 314 and 314-1. Furthermore, according to an embodiment, the wearable device 300 may include a plurality of processors. The number of motor drive circuits, the number of motors, or the number of processors may vary depending on the body part on which the wearable device 300 is worn.

The following description of the sensor 321, motor driver circuit 312, and motor 314 is also applicable to the sensor 321-1, motor driver circuit 312-1, and motor 314-1 shown in fig. 3 d.

The driver 310 may drive the hip joint of the user. For example, the driver 310 may be disposed on the right hip of the user and/or the left hip of the user. The driver 310 may be additionally provided on the knee part and the ankle part of the user. The driver 310 may include a motor 314 configured to generate a rotational torque and a motor driver circuit 312 configured to drive the motor 314.

The sensor 320 may measure the angle of the user's hip joint as the user walks. The information about the hip angle sensed by the sensor 320 may include a right hip angle, a left hip angle, a difference between the two hip angles, and a hip movement direction. For example, the sensor 321 may be disposed in the driver 310. Depending on the location of the sensors, the sensors 320 (e.g., 321 and/or 321-1) may additionally measure the knee angle and ankle angle of the user. The sensor 321 may comprise an encoder. Information about the hip angle measured by the sensor 320 may be sent to the controller 340.

According to an example embodiment, the sensor 320 may include a potentiometer. The potentiometer may sense the R-axis joint angle and the L-axis joint angle, as well as the R-axis joint angular velocity and the L-axis angular velocity, based on the user's walking motion. In this case, the R-axis and the L-axis may be reference axes of the right leg and the left leg of the user, respectively. For example, the R axis and the L axis may be set to be perpendicular to the ground and set such that the front side of the human body has a negative value and the rear side of the human body has a positive value.

The IMU330 may measure acceleration information and posture information while the user is walking. For example, the IMU330 may sense X-axis acceleration, Y-axis acceleration, and Z-axis acceleration, as well as X-axis angular velocity, Y-axis angular velocity, and Z-axis angular velocity, based on the user's walking motion. Acceleration information and pose information measured by the IMU330 may be sent to the controller 340.

The wearable device 300 may detect a point of the user's foot landing based on acceleration information measured by the IMU 330.

Pressure sensors (not shown) may be provided on the soles of the user's feet to detect the landing time of the user's feet.

In addition to the sensors 320 and IMU330 described above, the wearable device 300 may include other sensors (e.g., electromyography (EMG) sensors) configured to sense a change in the amount of motion of the user or a change in a bio-signal based on the user's walking motion.

The controller 340 may control the overall operation of the wearable device 300. For example, the controller 340 may receive information sensed by each of the sensors 320 and IMU 330. The information sensed by the IMU330 may include acceleration information and pose information, and the information sensed by the sensor 320 may include information about right hip angle, left hip angle, difference between the two hip angles, and hip motion direction. According to an embodiment, the controller 340 may calculate a difference between the right and left hip angles based on the two hip angles. The controller 340 may generate a signal for controlling the driver 310 based on the sensed information. For example, the generated signal may be an assisting force for assisting the user in walking. In another example, the generated signal may be a resistance to walk by the user. Resistance may be provided to the user to assist the user in performing the exercise.

According to an example embodiment, the processor 342 of the controller 340 may control the driver 310 to provide resistance to a user.

For example, the driver 310 may provide resistance to the user by applying active force to the user via the motor 314. In another example, the driver 310 may provide resistance to the user using the reverse driving of the motor 314 without applying active force to the user. Here, the reverse driving property of the motor may refer to the reactivity of the rotation shaft of the motor in response to an external force, and the greater reverse driving property may refer to the motor being more easily responsive to an external force acting on the rotation shaft, that is, the motor being more easily rotatable about the rotation shaft. For example, even when the same external force is applied to the rotation shaft of the motor, the degree of rotation of the motor about the rotation axis may vary depending on the degree of reverse driving.

In another example, the driver 310 may provide resistance to the user by outputting torque in a direction that impedes movement of the user.

According to an example embodiment, the processor 342 of the controller 240 may control the driver 310 such that the driver 310 outputs torque (or assistance torque) to assist the user in walking. For example, in the hip-type wearable device 300, the driver 310 may be provided on each of the left and right hips, and the controller 340 may output a control signal for controlling the driver 310 to generate torque.

The driver 310 may generate torque based on a control signal output by the controller 340. The torque value for generating torque may be set externally or by the controller 340. For example, to indicate the magnitude of the torque value, the controller 340 may use the magnitude of the current for the signal sent to the driver 310. That is, as the magnitude of the current received by the driver 310 increases, the torque value may increase. In another example, the processor 342 of the controller 340 may send a control signal to the motor driver circuit 312 of the driver 310, and the motor driver circuit 312 may generate a current corresponding to the control signal to control the motor 314.

The battery 350 may provide power to the components of the wearable device 300. The wearable device 300 may further include: circuitry (e.g., a Power Management Integrated Circuit (PMIC)) configured to convert power of the battery 350 to match an operating voltage of components of the wearable device 300 and provide power to the components of the wearable device 300. Additionally, the battery 350 may or may not power the motor 314 based on the operating mode of the wearable device 300.

The communication module 352 including the communication circuitry may support establishment of a direct (e.g., wired) communication channel or a wireless communication channel between the wearable device 300 and an external electronic device, and support communication over the established communication channel. The communication module 352 may include: one or more communication processors configured to support direct (e.g., wired) communication or wireless communication. According to example embodiments, the communication module 352 may include a wireless communication module (e.g., a cellular communication module, a short-range wireless communication module, or a GNSS communication module) or a wired communication module (e.g., a LAN communication module or a PLC module). A respective one of the communication modules may be connected via a first network (e.g., such as Bluetooth ^TM A short-range communication network of Wi-Fi direct or IrDA) or a second network (e.g., a conventional cellular network, a 5G network, a next-generation communication network, the internet, or a computer network) with an external electronic device. These various types of communication modules may be implemented as a single component (e.g., a single chip), or may be implemented as multiple components (e.g., multiple chips) separate from each other. Each processor herein includes processing circuitry.

Fig. 4 is a diagram illustrating a wearable device in communication with an electronic device according to an example embodiment.

Referring to fig. 4, a wearable device 300 may communicate with an electronic device 201. For example, the electronic device 201 may be an electronic device of a user of the wearable device 300. According to an example embodiment, the wearable device 300 and the electronic device 201 may be connected using short-range wireless communication.

The electronic device 201 may display a User Interface (UI) on the display 201-1 for controlling the operation of the wearable device 300. The UI may include, for example, at least one soft key through which the user may control the wearable device 300.

A user may input a command for controlling the operation of the wearable device 300 through a UI on the display 201-1 of the electronic device 201, and the server 1400 (for example, refer to fig. 14) may generate a control command corresponding to the command and transmit the generated control command to the wearable device 300. The wearable device 300 may operate according to the received control command and transmit the control result to the electronic device 201. The electronic device 201 may display a control complete message on the display 201-1 of the electronic device 201.

Fig. 5 and 6 are diagrams illustrating a method of outputting torque by a wearable device according to an embodiment.

Referring to fig. 5 and 6, the drivers 310-1 and 310-2 of the wearable apparatus 300 of fig. 3 may be disposed at or near the hip joint of the user, and the controller 340 of the wearable apparatus 300 may be disposed at or near the waist of the user. However, the locations of the drivers 310-1 and 310-2 and the controller 340 are not limited to the example locations shown in fig. 5 and 6.

The wearable device 300 may measure (or sense) the left hip angle q_1 and the right hip angle q_r of the user. For example, the wearable device 300 may measure the left hip angle q_1 of the user by the left encoder and the right hip angle q_r of the user by the right encoder. As shown in fig. 6, the left hip angle q_1 may be negative because the user's left leg is in front of the reference line 620, and the right hip angle q_r may be positive because the user's right leg is behind the reference line 620. According to an embodiment, the right hip angle q_r may be negative when the right leg is in front of the reference line 620, and the left hip angle q_1 may be positive when the left leg is behind the reference line 620.

According to an example embodiment, the wearable device 300 may obtain the first angle (e.g., q_r) and the second angle (e.g., q_1) by filtering a first original angle (e.g., q_r_raw) of a first joint (e.g., right hip joint) and a second original angle (e.g., q_l_raw) of a second joint (e.g., left hip joint) measured by the sensor 320. For example, the wearable device 300 may filter the first original angle and the second original angle based on the first previous angle and the second previous angle measured for the previous time.

According to an example embodiment, the wearable device 300 may determine the torque value τ (t) based on the left hip angle q_1, the right hip angle q_r, the offset angle c, the sensitivity α, the gain κ, and the delay Δt, and control the motor driver circuit 312 of the wearable device 300 to output the determined torque value τ (t). The force provided to the user by the torque value τ (t) may be referred to as force feedback. For example, the wearable device 300 may determine the torque value τ (t) based on equation 1 below.

[ equation 1]

y＝sin(q_r)-sin(q_l)

τ(t)＝κy(t-Δt)

In equation 1 above, y may represent a state factor, q_r may represent a right hip joint angle, and q_1 may represent a left hip joint angle. According to equation 1, the state factor y may be associated with the distance between the two legs. For example, y being 0 may indicate a state (e.g., a crossing state) in which the distance between the legs is 0, and an absolute value of y being a maximum value may indicate a state (e.g., a landing state) in which the angle between the legs is maximum. When q_r and q_1 are measured at time t, the state factor may be expressed as y (t).

The gain κ is a parameter indicative of the magnitude and direction of the output torque. As the magnitude of the gain κ increases, greater torque may be output. When the gain κ is a negative value, a torque acting as a resistance may be output to the user. When the gain κ is a positive value, a torque serving as an assist force can be output to the user. The delay Δt may be a parameter associated with the torque output timing. The value of gain κ and the value of delay Δt may be preset and adjustable by the user or the wearable device 300. The model for outputting the torque serving as the assist force to the user based on parameters such as equation 1, gain κ, and delay Δt may be a torque output model (or torque output algorithm). The wearable device 300 may determine the torque magnitude and torque delay to be output by inputting the value of the input parameter received through the sensor to the torque output model.

According to an example embodiment, the wearable device 300 may determine the first torque value by applying the first gain value and the first delay value, which are parameter values determined for the state factor y (t), to the first state factor y (t) based on the following equation 2.

[ equation 2]

τ _l (t)＝κy(t-Δt)

τ _r (t)＝-κy(t-Δt)

Because the first torque value is applied to both legs, the calculated first torque value may include a value associated with the first joint and a value associated with the second joint. For example, τl (t) may be a value related to the left hip joint as the second joint, and τr (t) may be a value related to the right hip joint as the first joint. τl (t) and τr (t) may have the same magnitude and opposite torque directions. The wearable device 300 may control the motor driver 312 of the wearable device 300 to output a torque corresponding to the first torque value.

According to an example embodiment, when the user performs a gait with asymmetric left and right legs, the wearable device 300 may provide asymmetric torque to the two legs of the user to assist the asymmetric gait. For example, the wearable device 300 may provide a stronger assist force to a leg with a shorter step size or a slower swing speed. Hereinafter, a leg with a shorter step or slower swing speed may be referred to as an affected leg or target leg.

In general, the swing time or step length of the affected leg may be shorter than the swing time or step length of the unaffected leg. According to an example embodiment, to assist the gait of the user, a method of adjusting the timing of the torque acting on the affected leg may be considered. For example, the offset angle may be added to the actual joint angle of the affected leg to increase the output time of torque for assisting the swing motion of the affected leg. c may be a value of a parameter indicating an offset angle between joint angles. By adding the offset angle to the actual joint angle of the affected leg, the value of the input parameter input to the torque output model installed (or applied) to the wearable device 300 may be adjusted. For example, the values of q_r and q_l may be adjusted by the following equation 3. c _r May represent an offset angle for the right hip joint, and c ₁ An offset angle for the left hip joint may be represented.

[ equation 3]

q _{_r} (t)←q _{_r} (t)+c _r

q _{_l} (t)←q _{_l} (t)+c _l

According to an example embodiment, the wearable device 300 may filter the state factor to reduce discomfort to the user due to irregular torque output. For example, the wearable device 300 may determine the initial state factor y for the current time t based on the first angle of the first joint and the second angle of the second joint _raw (t), and based on a previous state factor y determined for a previous time t-1 ^prv And an initial state factor y _raw (t) determining a first state factor y (t). The current time t may indicate the processing time of the t-th data (or sample), and the previous time t-1 may indicate the processing time of the t-1 th data. For example, the difference between the current time t and the previous time t-1 may be an operating period of a processor configured to generate or process corresponding data. The sensitivity α may be a value of a parameter indicating the sensitivity. For example, the sensitivity value may be continuously adjusted during test walking, but in order to reduce the complexity of calculation, the sensitivity value may be preset to a predetermined value.

Each embodiment herein may be used in combination with any other embodiment described herein.

Fig. 7 is a block diagram for optimizing parameter values of a wearable device according to an example embodiment.

According to an example embodiment, the electronic device 201 may optimize the value of the control parameter used by the system 770 (e.g., the wearable device 300 of fig. 3) to output torque. For example, the optimized value of the control parameter may be determined by the optimizer 720 of the electronic device 201. According to an example embodiment, the control parameters may include at least one of an offset angle 730, a sensitivity 740, a delay 750, or a gain 760.

According to an example embodiment, the optimizer 720 may optimize the values of the control parameters based on test sensing information obtained by testing the gait of the user of the wearable device 300. For example, the gait test may be used to check the current state of the user's gait, and the wearable device 300 may not provide the user with an auxiliary force or resistance when performing the gait test. The optimizer 720 may optimize the values of the control parameters based on the test sensing information and the exercise target 710 preset by the user through the gait test.

The determination of the optimal values of the control parameters by the electronic device 201 through gait tests will be described in detail below with reference to fig. 9.

Fig. 8 is a flowchart illustrating a method of providing an exercise program to a user according to an example embodiment.

According to an example embodiment, operations 810 through 880 may be performed by an electronic device (e.g., electronic device 110 of fig. 1 or electronic device 201 of fig. 2).

In operation 810, the electronic device may receive target exercise information from a user. For example, the target exercise information may include target exercise time information and target exercise section information.

According to an example embodiment, the target exercise time information may be information about an entire exercise time (e.g., 30 minutes or 1 hour) that the user currently wants to perform an exercise.

According to an example embodiment, the target exercise interval information may include an exercise route. For example, the workout route may include information about a start point, an end point, and a detailed route between the start point and the end point.

In operation 820, the electronic device may obtain a current value of the gait evaluation item. For example, the gait evaluation project may include at least one of: step size, gait speed, gait symmetry or gait rhythm.

According to an example embodiment, the electronic device may obtain the current value of the gait evaluation item based on previous sensed information obtained when a previous exercise program was performed using a wearable device (e.g., wearable device 120 of fig. 1 or wearable device 300 of fig. 3 a). For example, the previous exercise program may be a recently executed exercise program or an accumulated exercise program.

According to example embodiments, the electronic device may enable a user to perform a test exercise program through the wearable device and obtain a current value of the gait evaluation item based on test sensing information obtained as a result of the execution of the test exercise program. The acquisition of the current value of the gait evaluation item based on the test exercise program will be described in detail below with reference to fig. 9.

According to an example embodiment, the step size may be the distance between the left foot and the right foot while walking. For example, when the left and right legs contact the ground at the same time, the legs and the ground may form a triangle. In this example, a step size representing the remainder of the triangle may be calculated based on the left hip angle, the right hip angle, and the leg length. For example, an average step size of a plurality of steps performed by the user may be acquired as the step size.

According to an example embodiment, gait speed may be acquired based on a distance of movement and a time of movement. For example, the IMU may be used to estimate gait speed. The IMU may acquire acceleration in 3 degrees of freedom and rotation rate in 3 degrees of freedom. The electronic device may acquire gait speed by inputting the acquired acceleration of 3 degrees of freedom and the rotation rate of 3 degrees of freedom to a Long Short Term Memory (LSTM) based pre-trained gait speed estimation model. For example, the gait speed estimation model may be pre-trained by machine learning. For example, the gait speed estimation model may be a model using dynamic analysis. For example, the gait speed estimation model may be a model using a method of extracting features and performing linear regression.

According to an example embodiment, the gait rhythm may indicate a consistency of user walking. For example, gait rhythm can be calculated by equation 4.

[ equation 4]

In equation 4, the stride time standard deviation may indicate a standard deviation of the stride time, and the stride time average may indicate an average stride time. That is, the gait rhythm may be a Coefficient of Variation (CV) for stride time.

According to an example embodiment, the stride time may be calculated based on the movement of the periodically moving leg. For example, the step time of the left leg may be calculated based on the time between time points when the sign of the angular velocity of the left hip joint is changed, and the step time of the right leg may be calculated based on the time between time points when the sign of the angular velocity of the right hip joint is changed. For example, in order to reduce noise, 50 angular velocity samples may be averaged, and the step time and stride time for each leg may be calculated based on the time between points when the sign of the average changes. For example, one stride time may be calculated as the sum of the left leg's stride time and the right leg's stride time.

According to example embodiments, gait symmetry may indicate how the gait of the left leg and the gait of the right leg are symmetrical. For example, gait symmetry may be calculated based on the ratio of the stride time of one leg to the stride time of the other leg. For example, gait symmetry can be calculated by equation 5.

[ equation 5]

In equation 5, the left step time average may indicate an average time of steps with respect to the left leg, and the right step time average may indicate an average time of steps with respect to the right leg. That is, gait symmetry may be the Symmetry Index (SI) between steps. For example, gait symmetry calculated as SI may indicate temporal gait symmetry, and when time is converted to a length corresponding to time, gait symmetry may indicate spatial gait symmetry.

In operation 830, the electronic device may determine an optimal value of the control parameter that may satisfy the target value of the gait evaluation item based on the target exercise information and the current value of the gait evaluation item.

According to an example embodiment, the electronic device may set the target value of the gait evaluation item based on a target exercise target selected by the user from a plurality of exercise targets. For example, the plurality of exercise goals may include two or more of improving gait ability, improving gait posture, improving cardiovascular health, and improving muscle strength. For example, the target value of the evaluation item may be adjusted in detail based on the physical information, age, and sex of the user. The electronic device may prioritize or rank the assessment items that are preferentially needed by the user among the assessment items based on the target workout goal.

According to example embodiments, the electronic device may determine a target evaluation item to be improved based on a current value of the gait evaluation item, and determine one or more control parameters having a greatest impact on the value of the target evaluation item. For example, when the target evaluation item is an improvement step, the timing and gain may be determined as control parameters. For example, when the target evaluation item is to improve gait speed, sensitivity may be determined as the control parameter. For example, when the target evaluation item is to improve gait symmetry, the offset angle may be determined as the control parameter. For example, when the target evaluation item is to improve gait rhythm, sensitivity may be determined as the control parameter. During the optimization process, the values of other control parameters that are not determined for the target evaluation item may be fixed. According to an example embodiment, when the correlation between the target evaluation item and the control parameter is established in advance by a lookup table or a regression model, the process for determining the optimal value of the control parameter may be rapidly performed.

According to an example embodiment, the electronic device may determine an optimal value of the control parameter such that the target value of the gait evaluation item may be satisfied within a range that satisfies the set objective function. For example, the objective function may be expressed as the following equation 6.

[ equation 6]

Objective function = α x step size + β x gait speed + γ x gait symmetry + δ x gait rhythm

In equation 6, α, β, γ, and δ may represent weights of each evaluation item. The value of the objective function may be used as an indicator of directionality and, for example, an optimal value of the control parameter may be determined such that an improved value relative to the previous value of the objective function is calculated. For example, when the user exercises every day, the value of the control parameter of today may be determined as the optimal value, so that a value of improvement with respect to the value of the objective function of the exercise yesterday is calculated.

According to an example embodiment, the electronic device may also consider the target workout information to determine an optimal value for the control parameter. For example, as the target exercise time becomes shorter or the target exercise distance increases, the torque output timing may be shortened as the gait speed increases. In addition, when it is determined that it is difficult to achieve the target exercise distance within the target exercise time only by adjusting the torque output timing based on the gait ability of the current user, the electronic device may determine the gain value such that the magnitude of the torque output for assisting the user in walking is increased. In contrast to the above-described embodiments, when it is determined that the target exercise distance can be achieved within the target exercise time based on the gait ability of the current user, the electronic device may determine the gain value such that a torque that impedes the gait of the user is output to the user. The amount of torque interfering with gait may vary depending on the current gait capabilities of the user. For example, the user's current gait capabilities may correspond to any of the upper, middle or lower groups.

According to an example embodiment, the electronic device may also consider topographical information about the exercise route to determine an optimal value of the control parameter. The electronic device may obtain topographical information received from the user regarding the exercise route. For example, topographical information about the exercise route may be obtained based on a database in the electronic device. For example, topographical information about the exercise route may be acquired from an external server providing a map service. According to an example embodiment, when the topography of the exercise route is an uphill slope, the electronic device may determine a gain value such that torque for assisting walking is output to the user.

According to an example embodiment, the optimal value of the control parameter may be determined as any one of predetermined values, or may be determined as a range including predetermined values. The optimal values of the plurality of control parameters may be referred to as an optimal value set.

In operation 840, the electronic device may obtain one or more recommended exercise programs based on the optimal value (or set of optimal values) of the control parameter.

According to an example embodiment, the control parameters used by or applied to the exercise program may be matched to each exercise program. The intensity of the assist force or resistance output by the exercise program and the output timing may be varied according to the value of the control parameter applied to the exercise program. For example, an exercise program may provide the same assistance force or resistance to the user throughout the exercise time through the wearable device. For example, an exercise program may divide an entire exercise time into a plurality of intervals, and provide different assisting forces or resistances to a user through a wearable device in the plurality of intervals.

According to an example embodiment, the electronic device may determine a candidate exercise program corresponding to an optimal value of the control parameter among a plurality of exercise programs stored in the electronic device. For example, the electronic device may determine candidate exercise programs corresponding to optimal values of the control parameters based on a database storing values of the control parameters applied to each of the plurality of exercise programs.

According to an example embodiment, the electronic device may determine recommended ones of the candidate exercise programs based on preset filter conditions. For example, the filtering conditions may be preset by a user. For example, the filtering condition may be set based on a history of exercise programs that the user has recently performed. Even when the user frequently exercises in the same exercise environment, the recommended exercise program may vary according to the exercise history, and thus it may feel to the user as if it exercises in an exercise environment different from the corresponding exercise environment. The determination of recommended exercise programs and candidate exercise programs will be described in detail below with reference to fig. 11.

According to an example embodiment, the electronic device may send the optimal value of the control parameter to a server (e.g., server 140 of fig. 1) and receive the recommended exercise program from the server. The exercise program executed by the electronic device to acquire recommendations through the server will be described in detail below with reference to fig. 12.

In operation 850, the electronic device may determine a target exercise program of the one or more recommended exercise programs. For example, the electronic device may determine the target exercise program by receiving a selection of the target exercise program from the user.

According to an example embodiment, the electronic device may output one or more recommended exercise programs via a display of the electronic device or a display of an add-on device connected to the electronic device (e.g., add-on device 130 of fig. 1), and receive a selection of a target exercise program from the user via a touch input or a button input.

According to an example embodiment, the electronic device may provide the user with a gait age achieved when performing the recommended exercise program. For example, the average age of a user that can normally perform a recommended exercise program without the aid of a wearable device may be matched with the recommended exercise program in advance.

In operation 860, the electronic device may send information about the target exercise program to a wearable device worn by the user. For example, the information about the target exercise program may include information about values of control parameters applied to the target exercise program. When a user performs a target exercise program while wearing the wearable device, the wearable device may provide an assist force or resistance to the user's body (e.g., legs) based on the received values of the control parameters. For example, the value of the control parameter may characterize the trajectory for the target exercise time.

For example, the target exercise program may provide the same assistance or resistance to the user throughout the exercise time. As another example, the target exercise program may divide the entire exercise time into multiple intervals and provide different assistance or resistance to the user in the multiple intervals. As another example, the target exercise program may divide the entire exercise route into a plurality of detailed exercise routes and provide different assistance or resistance to the user among the plurality of detailed exercise routes.

In operation 870, the electronic device may receive the sensed information from the wearable device while the target exercise program is being executed by the wearable device. For example, the wearable device may generate sensing information about the gait of the user using at least one sensor and send the sensing information to the electronic device.

For example, the sensed information may include an angle of a left hip joint and an angle of a right hip joint of the user generated by the encoder. For example, the sensing information may include acceleration information and gesture information generated by the IMU. For example, the sensing information may include biometric information generated by a biosensor. For example, the sensed information may include location information generated by a Global Positioning System (GPS) sensor. Each element in the sensing information may be associated with a timestamp.

According to an example embodiment, the electronic device may receive additional sensing information from an additional device connected to the electronic device. For example, when the additional device is a smart watch (e.g., smart watch 132 of fig. 1), the electronic device may receive the heart rate from the smart watch as additional sensed information.

In operation 880, the electronic device may provide feedback information to the user regarding the execution of the target exercise program based on the sensed information.

According to example embodiments, the electronic device may determine whether a target value of the gait evaluation item is satisfied based on the sensing information, and provide different feedback information to the user based on whether the target value is satisfied. Providing feedback information to the user will be described in detail below with reference to fig. 13.

According to example embodiments, the electronic device may provide feedback information to a user through a user interface device of the wearable device. For example, the feedback information may be provided to the user through a speaker, display, or haptic device of the wearable device.

According to example embodiments, the electronic device may provide feedback information to the user through an add-on device (e.g., add-on device 130 of fig. 1) that is directly or indirectly connected to the electronic device. For example, when the add-on device is a wireless headset (e.g., wireless headset 131 of fig. 1), audible feedback information may be provided to the user through the wireless headset. For example, when the add-on device is a smart watch (e.g., smart watch 132 of fig. 1) or smart glasses (e.g., smart glasses 133 of fig. 1), visual, audible, or tactile feedback information may be provided to the user.

According to an example embodiment, a user may identify a current state of gait through feedback information and change how to perform an exercise based on the identified current state of gait. For example, the user may increase the gait speed when the feedback information indicates that the gait speed is low.

According to an example embodiment, after a user has completed an exercise of a target exercise program, an electronic device may evaluate the execution result of the exercise and store the execution result and the evaluation. For example, the results and evaluations of performance for a current workout may be used as current values for gait evaluation items for subsequent workouts.

Fig. 9 is a flowchart illustrating a method of acquiring a current value of a gait evaluation item according to an example embodiment.

According to an example embodiment, operation 820 described above with reference to fig. 8 may include operations 910 through 930 that will be described below with reference to fig. 9.

In operation 910, the electronic device may send information about a test exercise program for obtaining a current value of the gait evaluation item to the wearable device.

According to an example embodiment, the test exercise program may be an exercise program for checking a current state of gait of the user. For example, the test exercise program may instruct the user to begin walking, and the user may walk a preset distance (e.g., 10 meters) or a preset time (e.g., 5 seconds). While the user is performing the test walk, the test exercise program may not provide the user with an auxiliary force or resistance through the wearable device.

In operation 920, the electronic device may receive test sensing information regarding the execution of the test exercise program from the wearable device. For example, the wearable device may generate test sensing information regarding a user's test walk using at least one sensor and send the test sensing information to the electronic device.

For example, the test sensing information may include an angle of a left hip joint and an angle of a right hip joint of the user generated by the encoder. For example, the test sensing information may include acceleration information and pose information generated by the IMU. For example, the test sensing information may include biometric information generated by a biosensor. Each element in the test sensing information may be associated with a timestamp.

In operation 930, the electronic device may obtain a current value of the gait evaluation item based on the test sensing information. For example, the gait evaluation project may include at least one of: step size, gait speed, gait symmetry or gait rhythm or a combination thereof. The further description of obtaining the current values for each of step size, gait speed, gait symmetry and gait rhythm may be replaced with the description of operation 820 described above with reference to fig. 8.

Fig. 10 is a flowchart illustrating a method of determining an optimal value of a control parameter according to an example embodiment.

According to an example embodiment, operation 830 described above with reference to fig. 8 may include operations 1010 through 1030, which will be described below with reference to fig. 10.

In operation 1010, the electronic device may determine a target assessment item based on the current value and the target value of the gait assessment item. For example, the evaluation items may be ordered in an order of a maximum difference between the current value and the target value of each evaluation item, and one or more target evaluation items may be determined based on the ordering.

In operation 1020, the electronic device may determine a target control parameter for improving a value of the target evaluation item. For example, when the target evaluation item is an improvement step, the timing and gain may be determined as control parameters. For example, when the target evaluation item is to improve gait speed, sensitivity may be determined as the control parameter. For example, when the target evaluation item is to improve gait symmetry, the offset angle may be determined as the control parameter. For example, when the target evaluation item is to improve gait rhythm, sensitivity may be determined as the control parameter. During the optimization process, the values of other control parameters that are not determined for the target evaluation item may be fixed.

In operation 1030, the electronic device may determine an optimal value of the target control parameter that may satisfy the target value of the evaluation item within a range that satisfies the target function. For example, the objective function may be represented by equation 6 above.

According to an example embodiment, to determine an optimal value of the target control parameter, target exercise time information, target exercise interval information, a current value of the evaluation item, and a target value of the evaluation item may be considered. For example, an optimal value of the target control parameter may be determined such that the user's exercise goal is achieved while satisfying both the target exercise time and the target exercise interval. For example, the objective function may be satisfied by achieving an exercise goal of the user, and may be satisfied when a value of the objective function related to the current exercise becomes greater than a value of the objective function related to the previous exercise.

Fig. 11 is a diagram illustrating a method of determining a recommended exercise program based on target exercise information according to an example embodiment.

The three-dimensional space shown in fig. 11 illustrates an exercise environment represented by exercise time, exercise distance, and exercise topography according to an example. As the value of each axis increases, a greater intensity of exercise from the user may be required.

According to an example embodiment, the electronic device or a server receiving an optimal value (or set of optimal values) of the control parameter from the electronic device may determine a recommended exercise program based on the optimal value of the control parameter.

For example, when an exercise interval having a record of a previously performed exercise is selected, but an exercise time shorter than before is selected (e.g., moving from point C to point a), an exercise program that increases gait speed as compared to the previously performed exercise program may be determined as the recommended exercise program.

For example, when the same exercise time as the previous exercise time is selected, but a shorter exercise distance is selected (e.g., moving from point E to point a), an exercise program that increases the exercise load (e.g., resistance) as compared to the previously performed exercise program may be determined as the recommended exercise program.

For example, when an exercise time that is the same as a previous exercise time is selected, but an easier exercise topography is selected (e.g., moving from point F to point a), an exercise program that increases the exercise load (e.g., resistance) as compared to a previously performed exercise program may be determined as a recommended exercise program.

For example, when the same exercise time as the previous exercise time is selected, but a longer exercise distance is selected (e.g., moving from point a to point E), an exercise program that reduces the exercise load (e.g., resistance) or provides an assisting force as compared to the previously performed exercise program may be determined as the recommended exercise program.

For example, when an exercise time identical to a previous exercise time is selected, but a more difficult exercise topography is selected (e.g., moving from point a to point F), an exercise program that reduces an exercise load (e.g., resistance) or provides an assist force as compared to a previously performed exercise program may be determined as a recommended exercise program.

For example, when an exercise time, an exercise distance, and an exercise topography that are different from a previous exercise time, exercise distance, and exercise topography are selected (e.g., moving from point D to point F), various recommended exercise programs may be determined based on optimal values of the control parameters.

According to an example embodiment, when a plurality of recommended exercise programs are determined, the server may preferentially recommend exercise programs that are well suited to user preferences based on exercise programs performed by users other than the user of the electronic device. The server may include a database in which information relating to exercises performed by the user using the wearable device is stored. For example, based on the target exercise interval information, exercise programs performed by other users in the target exercise interval may be acquired. For example, other users to be referred to may have the same exercise goals as the user or have the same gait age as the user.

Fig. 12 is a flowchart illustrating a method of acquiring a recommended exercise program through a server according to an example embodiment.

According to an example embodiment, operation 840 described above with reference to fig. 8 may include operations 1210 and 1220, which will be described below with reference to fig. 12.

In operation 1210, an electronic device (e.g., electronic device 110 of fig. 1 or electronic device 201 of fig. 2) may send an optimal value (or set of optimal values) of a control parameter to a server (e.g., server 140 of fig. 1).

According to an example embodiment, the server may determine one or more recommended exercise programs based on an optimal value of the control parameter.

In operation 1220, the electronic device may receive one or more recommended exercise programs from the server that are determined by the server based on the optimal values of the control parameters.

Fig. 13 is a flowchart illustrating a method of providing feedback information to a user according to an example embodiment.

According to an example embodiment, operation 880 described above with reference to fig. 8 may include operations 1310 to 1330, which will be described below with reference to fig. 13.

In operation 1310, the electronic device may determine whether a target value of the gait evaluation item is satisfied based on the sensing information received from the wearable device.

According to example embodiments, the electronic device may calculate a current value of the gait evaluation item based on the sensing information, and may determine whether the calculated current value corresponds to the target value. For example, current values of step size, gait speed, gait symmetry and gait rhythm may be calculated, and it may be determined whether the current values correspond to target values. The current value of the evaluation item may correspond to a target value when the user performs well for the target exercise program, and the current value of the at least one evaluation item may not reach the target value when the user performs poorly for the target exercise program.

In operation 1320, when the target value of the evaluation item is not satisfied, the electronic device may determine a required action for satisfying the target value. For example, when the target value of the gait speed is not satisfied, "walking faster than the current speed" may be determined as an action required for satisfying the target value of the gait speed. For example, when the target value of the step size is not satisfied, "widen your step size" may be determined as an action required for satisfying the target value of the step size.

In operation 1330, the electronic device may provide feedback information to the user including the desired action.

According to an example embodiment, the electronic device may provide feedback information to the user through an additional device (e.g., additional device 130 of fig. 1) connected to the electronic device. For example, when the add-on device is a wireless headset (e.g., wireless headset 131 of fig. 1), audible feedback information may be provided to the user through the wireless headset. For example, when the add-on device is a smart watch (e.g., smart watch 132 of fig. 1) or smart glasses (e.g., smart glasses 133 of fig. 1), visual, audible, or tactile feedback information may be provided to the user.

The server 1400 may include a communicator 1410, a processor 1420, and a memory 1430. For example, server 1400 may be server 140 described above with reference to fig. 1.

A communicator 1410 including communication circuitry may be directly or indirectly connected to the processor 1420 and the memory 1430 to send data to the processor 1420 and the memory 1430 and to receive data from the processor 1420 and the memory 1430. The communicator 1410 may be connected to another external device to transmit and receive data to and from the external device.

The communicator 1410 may be implemented as circuitry in the server 1400. For example, the communicator 1410 may include an internal bus and an external bus. In another example, the communicator 1410 may be an element that connects the server 1400 to an external device. Communicator 1410 may be an interface. The communicator 1410 may receive data from external devices and send the data to the processor 1420 and the memory 1430.

Processor 1420 may process data received from communicator 1410 and data stored in memory 1430. A "processor" may be a data processing apparatus implemented by hardware including circuitry having physical structures for performing desired operations. For example, the desired operations may include code or instructions included in a program. For example, a hardware-implemented data processing apparatus may include a microprocessor, a Central Processing Unit (CPU), a processor core, a multi-core processor, a multiprocessor, an Application Specific Integrated Circuit (ASIC), and a Field Programmable Gate Array (FPGA).

The processor 1420 may execute computer readable code (e.g., software) stored in a memory (e.g., memory 1430) and instructions triggered by the processor 1420.

The memory 1430 may store data received by the communicator 1410 and data processed by the processor 1420. For example, memory 1430 may store programs (or applications or software). The stored program may be a collection of grammars encoded by processor 1420 and executable by processor 1420 for determining one or more recommended exercise programs based on optimal values of control parameters.

The memory 1430 may include, for example, at least one volatile memory, non-volatile memory, random Access Memory (RAM), flash memory, a hard disk drive, or an optical disk drive, or a combination thereof.

Memory 1430 may store a set of instructions (e.g., software) for operating server 1400. A set of instructions for operating the server 1400 may be executed by the processor 1420. According to an example embodiment, memory 1430 may include a database containing information regarding a plurality of exercise programs. According to an example embodiment, memory 1430 may include a database storing a history of exercise programs performed by a plurality of users.

According to an example embodiment, the server 1400 may include: a communication module (e.g., communicator 1410) configured to exchange data with an external device; and at least one processor (e.g., processor 1420) configured to control the server 1400, wherein the processor may be configured to: receiving, from an electronic device (e.g., electronic device 110 of fig. 1 or electronic device 201 of fig. 2), an optimal value of a control parameter, the control parameter being a parameter for adjusting at least one of: sensitivity of the offset angle or state factor between the magnitude, direction and timing of torque to the joint angle; one or more recommended exercise programs of the plurality of exercise programs stored in a memory (e.g., memory 1430) of the server are determined based on the optimal values of the control parameters and the one or more recommended exercise programs are sent to the electronic device. As used herein, "based on" encompasses at least based on.

The processor of server 1400 may determine one or more recommended exercise programs corresponding to the optimal value among the plurality of exercise programs stored in the memory of server 1400 based on the history of exercise programs performed by the user.

The processor of server 1400 may receive sensed information received by the electronic device from the wearable device while the wearable device connected to the electronic device is executing a target exercise program of the one or more recommended exercise programs, and store the target exercise program and the sensed information in association with an account of the user.

The embodiments described herein may be implemented using hardware components, software components, and/or combinations thereof. The processing device may be implemented using one or more general purpose or special purpose computers, such as, for example, a processor, controller and Arithmetic Logic Unit (ALU), DSP, microcomputer, field Programmable Gate Array (FPGA), programmable Logic Unit (PLU), microprocessor, or any other device capable of responding to and executing instructions in a defined manner. The processing device may run an OS and one or more software applications running on the OS. The processing device may also access, store, manipulate, process, and create data in response to execution of the software. For simplicity, the description of the processing means is singular; however, those skilled in the art will appreciate that the processing device may include multiple processing elements and multiple types of processing elements. For example, the processing device may include multiple processors, or a single processor and a single controller. In addition, different processing configurations are possible, such as parallel processors. Each "cell" herein may include a circuit.

The software may include a computer program, code segments, instructions, or some combination thereof to individually or collectively instruct or configure the processing device to operate as needed. The software and data may be embodied permanently or temporarily in any type of machine, component, physical or virtual equipment, computer storage medium or device, or in a propagated signal wave capable of providing instructions or data to, or being interpreted by, a processing device. The software may also be distributed over network-coupled computer systems so that the software is stored and executed in a distributed fashion. The software and data may be stored by one or more non-transitory computer readable recording media.

The method according to the above-described embodiments may be recorded in a non-transitory computer-readable medium including program instructions for implementing various operations of the above-described embodiments. Media may also include data files, data structures, and the like, alone or in combination with program instructions. The program instructions recorded on the medium may be program instructions specially designed and constructed for the purposes of the embodiments, or they may be of the type well known and available to those having skill in the computer software arts. Examples of non-transitory computer readable media include magnetic media such as hard disks, floppy disks, and magnetic tape; optical media such as CD-ROM disks and/or DVDs; magneto-optical media such as optical disks; and hardware devices that are specially configured to store and perform program instructions, such as read-only memory (ROM), random Access Memory (RAM), flash memory, and the like. Examples of program instructions include both machine code, such as produced by a compiler, and files containing higher level code that may be executed by the computer using an interpreter.

The apparatus described above may be configured to act as one or more software modules in order to perform the operations of the examples described above, and vice versa.

As described above, although the embodiments have been described with reference to the limited drawings, those skilled in the art can apply various technical modifications and variations thereto. For example, suitable results may be achieved if the described techniques were performed in a different order and/or if components in the described systems, architectures, devices or circuits were combined in a different manner and/or replaced or supplemented by other components or their equivalents. It should be understood that the various exemplary embodiments are intended to be illustrative and not limiting. It will be further understood by those skilled in the art that various changes in form and details may be made therein without departing from the true spirit and full scope of the disclosure, including the appended claims and their equivalents. It should also be understood that any of the embodiments described herein may be used in combination with any other embodiment described herein.

Accordingly, other implementations, other examples, and equivalents of the claims are within the scope of the following claims.

Claims

1. An electronic device, comprising:

a communication module including a communication circuit configured to exchange data with an external device; and

At least one processor configured to control the electronic device,

wherein the at least one processor is configured to:

receiving target exercise information from a user of the electronic device, the target exercise information including target exercise time information and target exercise interval information;

determining an optimal value of a control parameter capable of satisfying a preset target value of the gait evaluation item based on the target exercise information and a current value of the gait evaluation item, the control parameter including a parameter for adjusting at least one of: the magnitude, direction and timing of the torque, the angle of offset between joint angles, or the sensitivity of the state factor to the joint angles;

acquiring at least one recommended exercise program based on an optimal value of the control parameter;

determining a target exercise program of the at least one recommended exercise program;

controlling sending information about the target exercise program to a wearable device worn by the user, the target exercise program configured to be executed by the wearable device;

receiving sensing information from the wearable device based on execution of the target exercise program; and

Control provides feedback information to the user based on the sensed information.

2. The electronic device of claim 1, wherein,

the gait assessment items include one or more of a step size, a gait speed, a gait symmetry and a gait rhythm.

3. The electronic device of claim 1, wherein,

the processor is configured to obtain a current value of the gait evaluation item based on previous sensed information obtained when a user performed a previous exercise program.

4. The electronic device of claim 1, wherein the processor is configured to:

control to send information about a test exercise program for obtaining a current value of the gait evaluation item to the wearable device;

receiving test sensing information from the wearable device while executing the test exercise program; and

a current value of the gait evaluation item is obtained based on the test sensing information.

5. The electronic device of claim 1, wherein the processor is configured to:

an optimal value of the control parameter is determined so that a target value of the gait evaluation item can be satisfied within a range satisfying a set objective function.

6. The electronic device of claim 1, wherein the processor is configured to:

controlling to send the optimal value of the control parameter to a server; and

one or more recommended exercise programs determined by the server based on the optimal values of the control parameters are received from the server.

7. The electronic device of claim 1, wherein the processor is configured to:

one or more recommended exercise programs corresponding to the optimal value are determined among a plurality of stored exercise programs.

8. The electronic device of claim 7, wherein the processor is configured to:

the one or more recommended exercise programs corresponding to the optimal value are determined among the plurality of stored exercise programs based on a history of exercise programs performed by the user.

9. The electronic device of claim 1, wherein

The information about the target exercise program includes values of control parameters during the target exercise time.

10. The electronic device of claim 1, wherein the processor is configured to:

determining whether a target value of the evaluation item is satisfied based on the sensing information;

Responsive to the target value not being met, determining an action required to meet the target value; and

the feedback information including the required actions is provided to the user.

11. The electronic device of claim 1, wherein the processor is configured to send the feedback information to an additional electronic device, and

wherein the feedback information is configured to be output by the additional electronic device.

12. The electronic device of claim 11, wherein the additional electronic device is any one of: earphone, glasses type electronic device, or watch type electronic device.

13. The electronic device of claim 11, wherein the processor is configured to:

a heart rate of the user is received from the additional electronic device as at least a portion of the sensed information.

14. A method performed by an electronic device, the method comprising:

determining an optimal value of a control parameter capable of satisfying a preset target value of the gait evaluation item based on the target exercise information and a current value of the gait evaluation item, the control parameter including a parameter for adjusting at least one of: the magnitude, direction and timing of the torque, the offset angle between the joint angles or the sensitivity of the state factor to the joint angles;

Acquiring a plurality of recommended exercise programs based on the optimal values of the control parameters;

determining a target exercise program of the plurality of recommended exercise programs;

transmitting information about the target exercise program to the user's wearable device;

receiving sensing information from the wearable device based on execution of the target exercise program at the wearable device; and

feedback information is provided to the user based on the sensed information.

15. A server, comprising:

at least one processor configured to control the server,

wherein the at least one processor is configured to:

receiving, from the electronic device, an optimal value of a control parameter, the control parameter being a parameter for adjusting at least one of: the magnitude of the torque, the direction and timing, the angle of offset between the joint angles, or the sensitivity of the state factor to the joint angles,

determining at least one recommended exercise program from a plurality of exercise programs stored in the server based on an optimal value of the control parameter; and

the at least one recommended exercise program is sent to the electronic device.