CN114652493A - Electromyographic signal control method and device, electromyographic equipment and storage medium - Google Patents
Electromyographic signal control method and device, electromyographic equipment and storage medium Download PDFInfo
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- A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
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Abstract
The invention discloses an electromyographic signal control method, an electromyographic signal control device, electromyographic equipment and a storage medium, wherein the method comprises the following steps: acquiring gesture data and electromyographic signal data, and determining that the gesture corresponding to the electromyographic signal data is an unconscious finger movement when the gesture data and the electromyographic signal data meet a preset judgment condition; acquiring duration time corresponding to the gesture, and if the duration time is longer than first preset time, adjusting control time and/or control intensity corresponding to the electromyographic signal data; and if the duration time is longer than the second preset time, outputting a pause control instruction, and after the pause control instruction is executed for a preset time period, recovering the control time and/or the control intensity corresponding to the electromyographic signal data. The invention can determine whether the gesture movement is the finger unconscious movement or not, and can control the electromyographic signal data according to the duration time of the gesture movement of the finger unconscious movement so as to control the energy consumption of the electromyographic equipment.
Description
Technical Field
The invention relates to the technical field of electromyographic signal control, in particular to an electromyographic signal control method and device, an electromyographic device and a storage medium.
Background
With the development of artificial intelligence technology and bioelectricity collection technology, people increasingly strongly demand intelligent auxiliary equipment. In the life of disabled people, the demand of the artificial limb is not only limited to beauty and some simple aids, but also is the desire of intelligent artificial limb, so that the emergence of electromyographic equipment is promoted. The electromyographic equipment is an intelligent product with high integration of a brain-computer interface technology and an artificial intelligence algorithm. The bionic hand can identify the movement intention of the wearer by extracting the arm neuromuscular signals of the wearer and convert the movement schematic diagram into the actions of the bionic hand, so that the dexterity and intelligence are achieved, and the hand moves with the heart.
At present, the bionic hand basically collects the myoelectric signals uninterruptedly, so that the timeliness and the accuracy of the myoelectric signal collection can be ensured. However, the continuous collection of the electromyographic signals causes high energy consumption of the bionic hand and influences the use of the user. The electromyographic devices of the prior art do not control the electromyographic signals on a dynamic basis.
Thus, there is a need for improvements and enhancements in the art.
Disclosure of Invention
The present invention is to provide an electromyographic signal control method, an electromyographic device, and a storage medium, which are used to solve the above-mentioned drawbacks of the prior art, and are intended to solve the problem that the electromyographic device in the prior art does not dynamically control the electromyographic signal.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows:
in a first aspect, the present invention provides an electromyographic signal control method, wherein the method comprises:
acquiring gesture data and electromyographic signal data, and determining that the gesture corresponding to the electromyographic signal data is finger unconscious movement when the gesture data and the electromyographic signal data meet preset judgment conditions;
acquiring duration corresponding to the gesture, and if the duration is longer than first preset time, adjusting control time and/or control intensity corresponding to the electromyographic signal data;
and if the duration is longer than a second preset time, outputting a pause control instruction, and after the pause control instruction is executed for a preset time period, recovering the control time and/or the control intensity corresponding to the electromyographic signal data.
In one implementation manner, when the gesture data and the electromyographic signal data meet a preset judgment condition, determining that a gesture motion corresponding to the electromyographic signal data is an involuntary finger movement includes:
determining a first fluctuation state corresponding to the attitude data according to the attitude data, wherein the first fluctuation state is used for reflecting the change condition of the attitude data;
acquiring a second fluctuation state corresponding to the electromyographic signal data, wherein the second fluctuation state is used for reflecting the change condition of the electromyographic signal data;
and if the first fluctuation state and the second fluctuation state meet the judgment condition, determining that the gesture corresponding to the electromyographic signal data is an unconscious finger disorder movement.
In one implementation manner, the determining that the gesture motion corresponding to the electromyographic signal data is an unconscious finger movement if the first fluctuation state and the second fluctuation state satisfy the determination condition includes:
acquiring a fluctuation amplitude corresponding to the first fluctuation state, wherein the fluctuation amplitude is used for reflecting a difference value between a wave peak value and a wave trough value in the attitude data;
if the fluctuation amplitude exceeds a preset amplitude threshold value, acquiring the signal jitter frequency of the second fluctuation state;
and if the signal jumping frequency is high-frequency jumping, determining that the first fluctuation state and the second fluctuation state meet the judgment condition, and determining that the gesture corresponding to the electromyographic signal data is finger unconscious movement.
In one implementation manner, the obtaining of the duration corresponding to the gesture motion, and if the duration is greater than a first preset time, adjusting the control time and/or the control intensity corresponding to the electromyographic signal data includes:
acquiring the starting time and the ending time of the finger unconscious disturbance, and determining the duration time according to the starting time and the ending time;
comparing the duration with the first preset time;
and if the duration is longer than the first preset time, reducing the control time and/or the control intensity corresponding to the electromyographic signal data.
In one implementation manner, if the duration is longer than a second preset time, outputting a pause control instruction, and after the pause control instruction is executed for a preset time period, recovering the control time and/or the control intensity corresponding to the electromyographic signal data, includes:
comparing the duration with a second preset time, wherein the second preset time is greater than the first preset time;
if the duration time is longer than the second preset time, outputting a pause control instruction, and controlling the electromyographic signal data to have no response according to the pause control instruction;
acquiring the execution duration of the pause control instruction, and comparing the execution duration with the preset time period;
and if the execution duration is greater than or equal to the preset time period, controlling the control time and/or the control intensity corresponding to the electromyographic signal data to recover.
In one implementation manner, if the duration is longer than a second preset time, outputting a pause control instruction, and after the pause control instruction is executed for a preset time period, recovering the control time and/or the control intensity corresponding to the electromyographic signal data, further includes:
and after a pause control instruction is output, calling a preset stop gesture, and controlling the gesture action to be the stop gesture when the pause control instruction is executed.
In an implementation manner, if the execution duration is greater than or equal to the preset time period, controlling the control time and/or the control intensity corresponding to the electromyographic signal data to recover includes:
if the execution duration is greater than or equal to the preset time period, acquiring a preset default gesture and default electromyographic signal data corresponding to the default gesture;
acquiring default control time and/or default control intensity corresponding to the default electromyographic signal data;
and adjusting the control time and/or the control intensity corresponding to the electromyographic signal data to the default control time and/or the default control intensity corresponding to the default electromyographic signal data.
In a second aspect, an embodiment of the present invention further provides an electromyographic signal control apparatus, where the apparatus includes:
the gesture motion analysis module is used for acquiring gesture data and electromyographic signal data and determining that a gesture motion corresponding to the electromyographic signal data is an unconscious finger disorder motion when the gesture data and the electromyographic signal data meet preset judgment conditions;
the first signal adjusting module is used for acquiring duration time corresponding to the gesture action, and if the duration time is longer than first preset time, adjusting control time and/or control intensity corresponding to the electromyographic signal data;
and the second signal adjusting module is used for outputting a pause control instruction if the duration time is longer than a second preset time, and recovering the control time and/or the control intensity corresponding to the electromyographic signal data after the pause control instruction executes a preset time period.
In one implementation, the gesture motion analysis module includes:
the first fluctuation analysis unit is used for determining a first fluctuation state corresponding to the attitude data according to the attitude data, and the first fluctuation state is used for reflecting the change condition of the attitude data;
the second fluctuation analysis unit is used for acquiring a second fluctuation state corresponding to the electromyographic signal data, and the second fluctuation state is used for reflecting the change condition of the electromyographic signal data;
and the gesture analysis and judgment unit is used for determining that the gesture corresponding to the electromyographic signal data is an unconscious finger disorder movement if the first fluctuation state and the second fluctuation state meet the judgment condition.
In one implementation, the gesture analysis and determination unit includes:
a fluctuation amplitude obtaining subunit, configured to obtain a fluctuation amplitude corresponding to the first fluctuation state, where the fluctuation amplitude is used to reflect a difference between a peak value and a trough value in the attitude data;
the jitter frequency determining subunit is used for acquiring the signal jitter frequency of the second fluctuation state if the fluctuation amplitude exceeds a preset amplitude threshold;
and the finger disorder determining subunit is configured to determine that the first fluctuation state and the second fluctuation state meet the determination condition and determine that the gesture corresponding to the electromyographic signal data is finger unconscious disorder if the signal jitter frequency is high-frequency jitter.
In one implementation, the first signal conditioning module includes:
the duration determining unit is used for acquiring the starting time and the ending time of the finger unconscious disturbance and determining the duration according to the starting time and the ending time;
a first time comparison unit for comparing the duration with the first preset time;
and the electromyographic signal control unit is used for reducing the control time and/or the control intensity corresponding to the electromyographic signal data if the duration is longer than the first preset time.
In one implementation, the second signal conditioning module includes:
a second time comparing unit, configured to compare the duration with a second preset time, where the second preset time is greater than the first preset time;
the signal pause control unit is used for outputting a pause control instruction if the duration time is longer than the second preset time, and controlling the electromyographic signal data to have no response according to the pause control instruction;
the execution duration acquisition unit is used for acquiring the execution duration of the pause control instruction and comparing the execution duration with the preset time period;
and the electromyographic signal recovery unit is used for controlling the control time and/or the control intensity corresponding to the electromyographic signal data to recover if the execution duration is greater than or equal to the preset time period.
In one implementation, the second signal adjusting module further includes:
and the stopping gesture determining unit is used for calling a preset stopping gesture after a pause control instruction is output, and controlling the gesture action to be the stopping gesture when the pause control instruction is executed.
In one implementation, the electromyographic signal recovery unit includes:
the default gesture obtaining subunit is configured to obtain a preset default gesture and default electromyographic signal data corresponding to the default gesture if the execution duration is greater than or equal to the preset time period;
the default signal acquisition subunit is used for acquiring default control time and/or default control intensity corresponding to the default electromyographic signal data;
and the signal recovery execution subunit is used for adjusting the control time and/or the control intensity corresponding to the electromyographic signal data to the default control time and/or the default control intensity corresponding to the default electromyographic signal data.
In a third aspect, an embodiment of the present invention further provides an electromyographic device, where the electromyographic device includes a memory, a processor, and an electromyographic signal control program stored in the memory and executable on the processor, and when the processor executes the electromyographic signal control program, the steps of the electromyographic signal control method according to any one of the above schemes are implemented.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, where an electromyographic signal control program is stored on the computer-readable storage medium, and when the electromyographic signal control program is executed by a processor, the steps of the electromyographic signal control method according to any one of the above schemes are implemented.
Has the advantages that: compared with the prior art, the invention provides an electromyographic signal control method, which comprises the steps of firstly obtaining posture data and electromyographic signal data, and determining that a gesture corresponding to the electromyographic signal data is an unconscious finger disorder when the posture data and the electromyographic signal data meet a preset judgment condition. And then obtaining the duration time corresponding to the gesture action, and if the duration time is longer than a first preset time, adjusting the control time and/or the control intensity corresponding to the electromyographic signal data. And finally, if the duration time is longer than a second preset time, outputting a pause control instruction, and after the pause control instruction is executed for a preset time period, recovering the control time and/or the control intensity corresponding to the electromyographic signal data. The invention can determine whether the gesture movement is the finger unconscious disorder movement or not by analyzing the gesture data and the electromyographic signal data, and can control the electromyographic signal data according to the duration time of the gesture movement of the finger unconscious disorder movement so as to control the energy consumption of the electromyographic equipment.
Drawings
Fig. 1 is a flowchart of an embodiment of an electromyographic signal control method according to an embodiment of the present invention.
Fig. 2 is a schematic block diagram of an electromyographic signal control apparatus according to an embodiment of the present invention.
Fig. 3 is a schematic block diagram of an electromyographic apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and effects of the present invention clearer and clearer, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The embodiment provides an electromyographic signal control method, and electromyographic signal data can be controlled through an electromyographic device based on the method of the embodiment so as to control energy consumption. In specific implementation, in this embodiment, firstly, gesture data and electromyographic signal data are obtained, and when the gesture data and the electromyographic signal data meet a preset judgment condition, a gesture corresponding to the electromyographic signal data is determined as an unintentional movement of a finger. And then obtaining the duration time corresponding to the gesture action, and if the duration time is longer than a first preset time, adjusting the control time and/or the control intensity corresponding to the electromyographic signal data. And finally, if the duration time is longer than a second preset time, outputting a pause control instruction, and after the pause control instruction is executed for a preset time period, recovering the control time and/or the control intensity corresponding to the electromyographic signal data. The embodiment can determine whether the gesture motion is the finger unconscious disorder motion or not by analyzing the gesture data and the electromyographic signal data, and can control the electromyographic signal data according to the duration time of the gesture motion of the finger unconscious disorder motion so as to control the energy consumption of the electromyographic equipment.
For example, the electromyographic device first obtains and analyzes the posture data and the electromyographic signal data, and determines whether a gesture corresponding to the electromyographic signal data is an involuntary finger movement, and if the gesture is the involuntary finger movement, it is determined that the electromyographic signal data at this time is disordered or interfered. And when the duration time is longer than a second preset time (for example, 5 seconds), the duration time indicates that the finger is unconsciously moved for too long time at the moment, and the response to the electromyographic signal data needs to be stopped, so that the electromyographic device outputs a pause control command at the moment. The control time and/or the control intensity of the electromyographic signal data can not be recovered until the execution time of the pause control command exceeds a preset time period (such as 3 seconds), so that the use of a user is met.
Exemplary method
The electromyographic signal control method of the present embodiment may be applied to an electromyographic device, which may be an intelligent bionic hand, as shown in fig. 1, and includes the following steps:
s100, acquiring gesture data and electromyographic signal data, and determining that a gesture corresponding to the electromyographic signal data is an unconscious finger movement when the gesture data and the electromyographic signal data meet preset judgment conditions.
In this embodiment, firstly, posture data and electromyographic signal data are obtained, where the posture data reflects a movement posture change of an intelligent bionic hand (i.e., an electromyographic device), and specifically may include data such as coordinate changes of each finger joint of the intelligent bionic hand. In specific implementation, the embodiment may detect and obtain IMU (inertial measurement unit) data of the finger joint through the inertial measurement unit, and the IMU data may reflect the posture data. The electromyographic signal data is data which is collected by connecting the electromyographic equipment with neurons on arms of a human body and can reflect action potential information on the neurons. After the gesture data and the electromyographic signal data are obtained, the gesture data and the electromyographic signal data can be analyzed by the embodiment, whether the gesture data and the electromyographic signal data meet preset judgment conditions or not is judged, and if the gesture data and the electromyographic signal data meet the preset judgment conditions, the gesture corresponding to the electromyographic signal data can be determined to be finger unconscious and disoriented.
In one implementation manner, the present embodiment, when determining that the gesture motion is an unintentional finger movement, includes the following steps:
s101, determining a first fluctuation state corresponding to the attitude data according to the attitude data, wherein the first fluctuation state is used for reflecting the change condition of the attitude data;
step S102, acquiring a second fluctuation state corresponding to the electromyographic signal data, wherein the second fluctuation state is used for reflecting the change condition of the electromyographic signal data;
step S103, if the first fluctuation state and the second fluctuation state meet the judgment condition, determining that the gesture corresponding to the electromyographic signal data is finger unconscious and disoriented.
In specific implementation, after obtaining the attitude data, the embodiment determines a first fluctuation state corresponding to the attitude data, where the first fluctuation state is used to reflect a change condition of the attitude data. Specifically, the present embodiment may collect posture data within a preset time period, analyze the posture data, draw corresponding fluctuation curve data according to the posture data, and specifically, automatically generate the fluctuation curve data according to the posture data based on preset software. The fluctuation curve data reflects the attitude data at different moments and can reflect the change condition of the attitude data in a preset time period, so that a first fluctuation state corresponding to the attitude data is obtained. According to the embodiment, the start time and the end time corresponding to the fluctuation curve data can be obtained according to the fluctuation curve data, and the peak value and the valley value between the start time and the end time are determined. Determining the fluctuation amplitude based on the peak value and the valley value, wherein the fluctuation amplitude is the difference between the peak value and the valley value. For example, the fluctuation range is a-B because the peak value and the trough value between the start time and the end time obtained from the fluctuation curve data are a and B, respectively.
Next, the embodiment compares the fluctuation amplitude with a preset amplitude threshold, and if the fluctuation amplitude exceeds the preset amplitude threshold, it indicates that the fluctuation amplitude of the posture data is large, and at this time, a second fluctuation state corresponding to the electromyographic signal data is obtained, where the second fluctuation state is used to reflect a change condition of the electromyographic signal data. Similarly, the embodiment may also collect the electromyographic signal data within a preset time period for analysis, and draw a corresponding signal graph, where the signal graph reflects a change situation of the electromyographic signal data within the preset time period, so that based on the signal graph, the embodiment may obtain time information of each electromyographic signal data within the preset time period, and based on each myopoint signal data and its corresponding time information, may determine a signal beating frequency corresponding to the electromyographic signal data, where the signal beating frequency is a change frequency of the electromyographic signal data within the preset time period. If the signal bounce frequency is higher than the preset frequency threshold, it may be determined that the signal bounce frequency is a high-frequency bounce, and at this time, it may be determined that the first fluctuation state and the second fluctuation state satisfy the determination condition, that is, the determination condition of this embodiment is that the fluctuation amplitude of the posture data exceeds the preset amplitude threshold and the bounce frequency corresponding to the myoelectric signal data is a high-frequency bounce, and when the two conditions are satisfied at the same time, it may be determined that the gesture motion corresponding to the myoelectric signal data is a finger involuntary movement.
And S200, obtaining duration time corresponding to the gesture action, and if the duration time is longer than first preset time, adjusting control time and/or control intensity corresponding to the electromyographic signal data.
When the gesture motion is determined to be finger involuntary movement, the electromyography device determines that the finger involuntary movement may be due to signal disorder. Therefore, the electromyographic device continues to acquire the duration time of the finger unconsciously and disorderly, and if the duration time is longer than a first preset time, the electromyographic device indicates that the electromyographic signal data is disturbed for a long time, and the control time and/or the control intensity corresponding to the electromyographic signal data are/is adjusted.
In one implementation manner, the embodiment includes the following steps when the electromyographic signal data is controlled:
step S201, obtaining the starting time and the ending time of the finger unconscious disturbance, and determining the duration time according to the starting time and the ending time;
step S202, comparing the duration time with the first preset time;
and S203, if the duration time is longer than the first preset time, reducing the control time and/or the control intensity corresponding to the electromyographic signal data.
Specifically, in this embodiment, the starting time and the ending time of the finger involuntary movement are first obtained, and the duration is determined according to the starting time and the ending time. The electromyographic device then compares the duration time with the first preset time. If the duration is longer than the first preset time (for example, 3 seconds), it is indicated that the electromyographic signal data is disturbed for a long time, the control time and/or the control intensity corresponding to the electromyographic signal data is reduced, the control time and/or the control intensity of the electromyographic signal data is reduced, the influence of the electromyographic signal data on the user can be reduced, the user cannot perform gesture actions of fingers which are unconsciously and disorderly moved, and thus the electromyographic device does not need to respond to the electromyographic signal data in real time and frequently, and the energy consumption of the electromyographic device can be reduced.
Step S300, if the duration time is longer than a second preset time, outputting a pause control instruction, and after the pause control instruction is executed for a preset time period, recovering the control time and/or the control intensity corresponding to the electromyographic signal data.
In this embodiment, the duration of the gesture motion of the finger which is unconsciously and disorderly moved is continuously obtained, and if the duration is longer than the second preset time, it indicates that the finger joint of the bionic hand is not controlled and needs to be controlled in time. Therefore, the embodiment outputs a pause control command, which can control the electromyographic device to pause the response to the electromyographic signal data, so as to avoid the phenomenon that fingers continue to move unconsciously. After the pause control instruction is executed for a preset time period, the embodiment recovers the control time and/or the control intensity corresponding to the electromyographic signal data so as to meet the use requirement of the user.
In one implementation manner, when recovering the electromyographic signal data, the embodiment includes the following steps:
step S301, comparing the duration time with the second preset time;
step S302, if the duration time is longer than the second preset time, outputting a pause control instruction, and controlling the electromyographic signal data to have no response according to the pause control instruction;
step S303, obtaining the execution duration of the pause control instruction, and comparing the execution duration with the preset time period;
and S304, if the execution duration is greater than or equal to the preset time period, controlling the control time and/or the control intensity corresponding to the electromyographic signal data to recover.
Specifically, the present embodiment compares the duration with the second preset time, where the second preset time is greater than the first preset time. If the duration time is longer than the second preset time, the finger joints of the bionic hand are not controlled, and the response of the electromyographic equipment to the electromyographic signal data needs to be paused in time. The myoelectric device can output the pause control instruction and control the myoelectric signal data to be unresponsive according to the pause control instruction, so that the myoelectric device cannot execute gesture actions of fingers which are unconsciously and disorderly moved even if receiving the myoelectric signal data. In a specific application, the embodiment may invoke a preset stop gesture after outputting the pause control instruction, and control the gesture action to be the stop gesture when executing the pause control instruction. The embodiment is used for controlling the electromyographic device to execute the stop gesture so as to enable the electromyographic device to be in a dormant or static mode, for example, the stop gesture is in a half-fist state, when the electromyographic device receives a pause control instruction, the electromyographic device stops responding to electromyographic signal data, and then performs and maintains the half-fist gesture action. And when the electromyographic device executes the pause control instruction, starting to acquire the execution duration of the pause control instruction, wherein the execution duration is the duration for the electromyographic device to execute the gesture action of half making a fist. Then, the electromyographic device compares the execution duration with a preset time period, if the execution duration is greater than or equal to the preset time period (for example, 3 seconds), the electromyographic device may consider the control of the pause response of the electromyographic signal data, and this embodiment may acquire a preset default gesture and default electromyographic signal data corresponding to the default gesture, and then control the electromyographic device to adjust the control time and/or the control intensity corresponding to the electromyographic signal data to the default control time and/or the default control intensity corresponding to the default electromyographic signal data. In this embodiment, the default gesture action is a starting action of the electromyographic device for recovering control on the electromyographic signal data, so that the electromyographic device acquires default control time and/or default control intensity of the default gesture so as to recover the control on the electromyographic signal data. That is to say, the default gesture of this embodiment is that the user wakes up the myoelectric device from the sleep state, so that the user can continue to use the myoelectric device, and the use requirement of the user is met.
In summary, in this embodiment, firstly, gesture data and electromyographic signal data are acquired, and when the gesture data and the electromyographic signal data meet a preset determination condition, it is determined that a gesture corresponding to the electromyographic signal data is an unintentional movement of a finger. And then obtaining the duration time corresponding to the gesture action, and if the duration time is longer than a first preset time, adjusting the control time and/or the control intensity corresponding to the electromyographic signal data. And finally, if the duration time is longer than a second preset time, outputting a pause control instruction, and after the pause control instruction is executed for a preset time period, recovering the control time and/or the control intensity corresponding to the electromyographic signal data. The embodiment can determine whether the gesture motion is the finger unconscious disorder motion or not by analyzing the gesture data and the electromyographic signal data, and can control the electromyographic signal data according to the duration time of the gesture motion of the finger unconscious disorder motion so as to control the energy consumption of the electromyographic equipment.
Exemplary devices
Based on the above embodiment, the present invention also provides an electromyographic signal control apparatus, as shown in fig. 2, the apparatus including: the gesture analysis module 10, the first signal adjustment module 20, and the second signal adjustment module 30. Specifically, the gesture motion analysis module 10 is configured to acquire gesture data and electromyographic signal data, and determine that a gesture motion corresponding to the electromyographic signal data is an involuntary finger movement when the gesture data and the electromyographic signal data meet a preset determination condition. The first signal adjusting module 20 is configured to obtain a duration time corresponding to the gesture, and adjust a control time and/or a control intensity corresponding to the electromyographic signal data if the duration time is greater than a first preset time. The second signal adjusting module 30 is configured to output a pause control instruction if the duration is greater than a second preset time, and recover the control time and/or the control intensity corresponding to the electromyographic signal data after the pause control instruction executes a preset time period.
In one implementation, the gesture motion analysis module 10 includes:
the first fluctuation analysis unit is used for determining a first fluctuation state corresponding to the attitude data according to the attitude data, and the first fluctuation state is used for reflecting the change condition of the attitude data;
the second fluctuation analysis unit is used for acquiring a second fluctuation state corresponding to the electromyographic signal data, and the second fluctuation state is used for reflecting the change condition of the electromyographic signal data;
and the gesture analysis and judgment unit is used for determining that the gesture corresponding to the electromyographic signal data is an unconscious finger disorder movement if the first fluctuation state and the second fluctuation state meet the judgment condition.
In one implementation manner, the gesture analysis and determination unit includes:
a fluctuation amplitude obtaining subunit, configured to obtain a fluctuation amplitude corresponding to the first fluctuation state, where the fluctuation amplitude is used to reflect a difference between a peak value and a trough value in the attitude data;
the jitter frequency determining subunit is used for acquiring the signal jitter frequency of the second fluctuation state if the fluctuation amplitude exceeds a preset amplitude threshold value;
and the finger disorder determining subunit is configured to determine that the first fluctuation state and the second fluctuation state meet the determination condition and determine that the gesture corresponding to the electromyographic signal data is finger unconscious disorder if the signal jitter frequency is high-frequency jitter.
In one implementation, the first signal adjusting module 20 includes:
the duration determining unit is used for acquiring the starting time and the ending time of the unconscious and disordered movements of the fingers and determining the duration according to the starting time and the ending time;
a first time comparison unit for comparing the duration with the first preset time;
and the electromyographic signal control unit is used for reducing the control time and/or the control intensity corresponding to the electromyographic signal data if the duration is longer than the first preset time.
In one implementation, the second signal adjusting module 30 includes:
a second time comparison unit for comparing the duration with the second preset time;
the signal pause control unit is used for outputting a pause control instruction if the duration time is longer than the second preset time, and controlling the electromyographic signal data to have no response according to the pause control instruction;
the execution duration acquisition unit is used for acquiring the execution duration of the pause control instruction and comparing the execution duration with the preset time period;
and the electromyographic signal recovery unit is used for controlling the control time and/or the control intensity corresponding to the electromyographic signal data to recover if the execution duration is greater than or equal to the preset time period.
In one implementation, the second signal adjusting module 30 further includes:
and the stopping gesture determining unit is used for calling a preset stopping gesture after a pause control instruction is output, and controlling the gesture action to be the stopping gesture when the pause control instruction is executed.
In one implementation, the electromyographic signal recovery unit includes:
the default gesture obtaining subunit is configured to obtain a preset default gesture and default electromyographic signal data corresponding to the default gesture if the execution duration is greater than or equal to the preset time period;
the default signal acquisition subunit is used for acquiring default control time and/or default control intensity corresponding to the default electromyographic signal data;
and the signal recovery execution subunit is used for adjusting the control time and/or the control intensity corresponding to the electromyographic signal data to the default control time and/or the default control intensity corresponding to the default electromyographic signal data.
The working principle of each module in the electromyographic signal control device of this embodiment is the same as the principle of each step in the above method embodiments, and is not described herein again.
Based on the above embodiments, the present invention also provides an electromyographic device, and a schematic block diagram of the electromyographic device may be as shown in fig. 3. The electromyographic device comprises a processor and a memory which are connected through a system bus, wherein the processor and the memory are arranged in a host. Wherein, the processor of the electromyographic device is used for providing calculation and control capability. The memory of the electromyographic device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the electromyographic equipment is used for being connected and communicated with an external terminal through network communication. The computer program is executed by a processor to implement an electromyographic signal control method.
It will be understood by those skilled in the art that the schematic block diagram shown in fig. 3 is only a block diagram of a partial structure related to the scheme of the present invention, and does not constitute a limitation on the electromyographic device to which the scheme of the present invention is applied, and a specific electromyographic device may include more or less components than those shown in the figure, or may combine some components, or have a different arrangement of components.
In one embodiment, an electromyographic device is provided, where the electromyographic device includes a memory, a processor, and an electromyographic signal control method program stored in the memory and executable on the processor, and when the processor executes the electromyographic signal control method program, the following operation instructions are implemented:
acquiring gesture data and electromyographic signal data, and determining that the gesture corresponding to the electromyographic signal data is finger unconscious movement when the gesture data and the electromyographic signal data meet preset judgment conditions;
acquiring duration corresponding to the gesture, and if the duration is longer than first preset time, adjusting control time and/or control intensity corresponding to the electromyographic signal data;
and if the duration time is longer than a second preset time, outputting a pause control instruction, and after the pause control instruction is executed for a preset time period, recovering the control time and/or the control intensity corresponding to the electromyographic signal data.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware related to instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, operational databases, or other media used in embodiments provided herein may include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), double-rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
In summary, the invention discloses an electromyographic signal control method, an electromyographic signal control device, an electromyographic device, and a storage medium, wherein the method comprises the following steps: acquiring gesture data and electromyographic signal data, and determining that the gesture corresponding to the electromyographic signal data is an unconscious finger movement when the gesture data and the electromyographic signal data meet a preset judgment condition; acquiring duration time corresponding to the gesture action, and if the duration time is longer than first preset time, adjusting control time and/or control intensity corresponding to the electromyographic signal data; and if the duration is longer than the second preset time, outputting a pause control instruction, and after the pause control instruction executes a preset time period, recovering the control time and/or the control intensity corresponding to the electromyographic signal data. The invention can determine whether the gesture movement is the finger unconscious movement or not, and can control the electromyographic signal data according to the duration time of the gesture movement of the finger unconscious movement so as to control the energy consumption of the electromyographic equipment.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (16)
1. An electromyographic signal control method, the method comprising:
acquiring gesture data and electromyographic signal data, and determining that the gesture corresponding to the electromyographic signal data is finger unconscious movement when the gesture data and the electromyographic signal data meet preset judgment conditions;
acquiring duration corresponding to the gesture, and if the duration is longer than first preset time, adjusting control time and/or control intensity corresponding to the electromyographic signal data;
and if the duration time is longer than a second preset time, outputting a pause control instruction, and after the pause control instruction is executed for a preset time period, recovering the control time and/or the control intensity corresponding to the electromyographic signal data.
2. The electromyographic signal control method according to claim 1, wherein determining that the gesture corresponding to the electromyographic signal data is an involuntary finger movement when the gesture data and the electromyographic signal data satisfy a preset judgment condition comprises:
determining a first fluctuation state corresponding to the attitude data according to the attitude data, wherein the first fluctuation state is used for reflecting the change condition of the attitude data;
acquiring a second fluctuation state corresponding to the electromyographic signal data, wherein the second fluctuation state is used for reflecting the change condition of the electromyographic signal data;
and if the first fluctuation state and the second fluctuation state meet the judgment condition, determining that the gesture corresponding to the electromyographic signal data is an unconscious finger disorder movement.
3. The electromyographic signal control method according to claim 2, wherein determining that the gesture corresponding to the electromyographic signal data is an involuntary finger movement if the first and second fluctuation states satisfy the determination condition comprises:
acquiring a fluctuation amplitude corresponding to the first fluctuation state, wherein the fluctuation amplitude is used for reflecting a difference value between a wave peak value and a wave trough value in the attitude data;
if the fluctuation amplitude exceeds a preset amplitude threshold value, acquiring the signal jitter frequency of the second fluctuation state;
and if the signal jumping frequency is high-frequency jumping, determining that the first fluctuation state and the second fluctuation state meet the judgment condition, and determining that the gesture corresponding to the electromyographic signal data is finger unconscious movement.
4. The electromyographic signal control method according to claim 1, wherein the obtaining a duration corresponding to the gesture motion, and if the duration is longer than a first preset time, adjusting a control time and/or a control intensity corresponding to the electromyographic signal data comprises:
acquiring the starting time and the ending time of the finger unconscious disturbance, and determining the duration time according to the starting time and the ending time;
comparing the duration with the first preset time;
and if the duration is longer than the first preset time, reducing the control time and/or the control intensity corresponding to the electromyographic signal data.
5. The electromyographic signal control method according to claim 4, wherein outputting a pause control command if the duration is greater than a second preset time, and restoring the control time and/or control intensity corresponding to the electromyographic signal data after the pause control command is executed for a preset time period comprises:
comparing the duration with a second preset time, wherein the second preset time is greater than the first preset time;
if the duration time is longer than the second preset time, outputting a pause control instruction, and controlling the electromyographic signal data to have no response according to the pause control instruction;
acquiring the execution duration of the pause control instruction, and comparing the execution duration with the preset time period;
and if the execution duration is greater than or equal to the preset time period, controlling the control time and/or the control intensity corresponding to the electromyographic signal data to recover.
6. The electromyographic signal control method according to claim 5, wherein, if the duration is longer than a second preset time, outputting a pause control command, and after the pause control command is executed for a preset time period, restoring the control time and/or the control intensity corresponding to the electromyographic signal data, further comprising:
and after a pause control instruction is output, calling a preset stop gesture, and controlling the gesture action to be the stop gesture when the pause control instruction is executed.
7. The electromyographic signal control method according to claim 6, wherein controlling the control time and/or the control intensity corresponding to the electromyographic signal data to recover if the execution duration is greater than or equal to the preset time period comprises:
if the execution duration is greater than or equal to the preset time period, acquiring a preset default gesture and default electromyographic signal data corresponding to the default gesture;
acquiring default control time and/or default control intensity corresponding to the default electromyographic signal data;
and adjusting the control time and/or the control intensity corresponding to the electromyographic signal data to the default control time and/or the default control intensity corresponding to the default electromyographic signal data.
8. An electromyographic signal control apparatus, the apparatus comprising:
the gesture motion analysis module is used for acquiring gesture data and electromyographic signal data and determining that a gesture motion corresponding to the electromyographic signal data is an unconscious finger disorder motion when the gesture data and the electromyographic signal data meet preset judgment conditions;
the first signal adjusting module is used for acquiring duration time corresponding to the gesture action, and if the duration time is longer than first preset time, adjusting control time and/or control intensity corresponding to the electromyographic signal data;
and the second signal adjusting module is used for outputting a pause control instruction if the duration time is longer than a second preset time, and recovering the control time and/or the control intensity corresponding to the electromyographic signal data after the pause control instruction executes a preset time period.
9. The electromyographic signal control apparatus of claim 8, wherein the gesture analysis module comprises:
the first fluctuation analysis unit is used for determining a first fluctuation state corresponding to the attitude data according to the attitude data, and the first fluctuation state is used for reflecting the change condition of the attitude data;
the second fluctuation analysis unit is used for acquiring a second fluctuation state corresponding to the electromyographic signal data, and the second fluctuation state is used for reflecting the change condition of the electromyographic signal data;
and the gesture analysis and judgment unit is used for determining that the gesture corresponding to the electromyographic signal data is an unconscious finger disorder movement if the first fluctuation state and the second fluctuation state meet the judgment condition.
10. The myoelectric signal control device according to claim 9, wherein the gesture analysis determination unit includes:
a fluctuation amplitude obtaining subunit, configured to obtain a fluctuation amplitude corresponding to the first fluctuation state, where the fluctuation amplitude is used to reflect a difference between a peak value and a trough value in the attitude data;
the jitter frequency determining subunit is used for acquiring the signal jitter frequency of the second fluctuation state if the fluctuation amplitude exceeds a preset amplitude threshold value;
and the finger disorder determining subunit is configured to determine that the first fluctuation state and the second fluctuation state meet the determination condition and determine that the gesture corresponding to the electromyographic signal data is finger unconscious disorder if the signal jitter frequency is high-frequency jitter.
11. The electromyographic signal control apparatus of claim 8, wherein the first signal conditioning module comprises:
the duration determining unit is used for acquiring the starting time and the ending time of the finger unconscious disturbance and determining the duration according to the starting time and the ending time;
a first time comparison unit for comparing the duration with the first preset time;
and the electromyographic signal control unit is used for reducing the control time and/or the control intensity corresponding to the electromyographic signal data if the duration is longer than the first preset time.
12. The electromyographic signal control apparatus of claim 11, wherein the second signal conditioning module comprises:
a second time comparing unit, configured to compare the duration with a second preset time, where the second preset time is greater than the first preset time;
the signal pause control unit is used for outputting a pause control instruction if the duration time is longer than the second preset time, and controlling the electromyographic signal data to have no response according to the pause control instruction;
the execution duration acquisition unit is used for acquiring the execution duration of the pause control instruction and comparing the execution duration with the preset time period;
and the electromyographic signal recovery unit is used for controlling the control time and/or the control intensity corresponding to the electromyographic signal data to recover if the execution duration is greater than or equal to the preset time period.
13. The electromyographic signal control apparatus of claim 12, wherein the second signal conditioning module further comprises:
and the stopping gesture determining unit is used for calling a preset stopping gesture after a pause control instruction is output, and controlling the gesture action to be the stopping gesture when the pause control instruction is executed.
14. The electromyogram signal control apparatus of claim 13, wherein the electromyogram signal recovery unit comprises:
the default gesture obtaining subunit is configured to obtain a preset default gesture and default electromyographic signal data corresponding to the default gesture if the execution duration is greater than or equal to the preset time period;
the default signal acquisition subunit is used for acquiring default control time and/or default control intensity corresponding to the default electromyographic signal data;
and the signal recovery execution subunit is used for adjusting the control time and/or the control intensity corresponding to the electromyographic signal data to the default control time and/or the default control intensity corresponding to the default electromyographic signal data.
15. An electromyographic device comprising a memory, a processor, and an electromyographic signal control program stored in the memory and executable on the processor, the steps of the electromyographic signal control method according to any of claims 1-7 being performed by the processor when executing the electromyographic signal control program.
16. A computer-readable storage medium, wherein an electromyographic signal control program is stored on the computer-readable storage medium, the electromyographic signal control program, when executed by a processor, performing the steps of the electromyographic signal control method of any one of claims 1-7.
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Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN115153985A (en) * | 2022-09-08 | 2022-10-11 | 深圳市心流科技有限公司 | Control method, device and terminal of intelligent artificial limb and computer readable storage medium |
CN115192049A (en) * | 2022-09-14 | 2022-10-18 | 深圳市心流科技有限公司 | Myoelectricity sampling frequency adjusting method of intelligent artificial limb |
CN116449967A (en) * | 2023-06-20 | 2023-07-18 | 浙江强脑科技有限公司 | Bionic hand teaching aid, control method thereof and main control equipment |
Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2007195592A (en) * | 2006-01-24 | 2007-08-09 | National Institute Of Advanced Industrial & Technology | Safety system for myoelectric interface |
CN107169432A (en) * | 2017-05-09 | 2017-09-15 | 深圳市科迈爱康科技有限公司 | Biometric discrimination method, terminal and computer-readable recording medium based on myoelectricity |
CN108209911A (en) * | 2017-05-25 | 2018-06-29 | 深圳市前海未来无限投资管理有限公司 | A kind of electromyographic signal collection method and device |
CN111743667A (en) * | 2020-06-29 | 2020-10-09 | 北京海益同展信息科技有限公司 | Artificial limb control method, device, system and storage medium |
CN112773582A (en) * | 2021-01-20 | 2021-05-11 | 京东数科海益信息科技有限公司 | Artificial limb control method, device, system and medium |
CN113977589A (en) * | 2021-12-23 | 2022-01-28 | 深圳市心流科技有限公司 | Gesture recognition threshold adjusting method and device and storage medium |
CN114452054A (en) * | 2022-02-23 | 2022-05-10 | 深圳市心流科技有限公司 | Control method and device of intelligent artificial limb, intelligent artificial limb and storage medium |
-
2022
- 2022-05-25 CN CN202210575280.3A patent/CN114652493B/en active Active
Patent Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2007195592A (en) * | 2006-01-24 | 2007-08-09 | National Institute Of Advanced Industrial & Technology | Safety system for myoelectric interface |
CN107169432A (en) * | 2017-05-09 | 2017-09-15 | 深圳市科迈爱康科技有限公司 | Biometric discrimination method, terminal and computer-readable recording medium based on myoelectricity |
CN108209911A (en) * | 2017-05-25 | 2018-06-29 | 深圳市前海未来无限投资管理有限公司 | A kind of electromyographic signal collection method and device |
CN111743667A (en) * | 2020-06-29 | 2020-10-09 | 北京海益同展信息科技有限公司 | Artificial limb control method, device, system and storage medium |
CN112773582A (en) * | 2021-01-20 | 2021-05-11 | 京东数科海益信息科技有限公司 | Artificial limb control method, device, system and medium |
CN113977589A (en) * | 2021-12-23 | 2022-01-28 | 深圳市心流科技有限公司 | Gesture recognition threshold adjusting method and device and storage medium |
CN114452054A (en) * | 2022-02-23 | 2022-05-10 | 深圳市心流科技有限公司 | Control method and device of intelligent artificial limb, intelligent artificial limb and storage medium |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN115153985A (en) * | 2022-09-08 | 2022-10-11 | 深圳市心流科技有限公司 | Control method, device and terminal of intelligent artificial limb and computer readable storage medium |
CN115192049A (en) * | 2022-09-14 | 2022-10-18 | 深圳市心流科技有限公司 | Myoelectricity sampling frequency adjusting method of intelligent artificial limb |
CN116449967A (en) * | 2023-06-20 | 2023-07-18 | 浙江强脑科技有限公司 | Bionic hand teaching aid, control method thereof and main control equipment |
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