CN117213532A - Multifunctional microfluidic flexible sensor - Google Patents
Multifunctional microfluidic flexible sensor Download PDFInfo
- Publication number
- CN117213532A CN117213532A CN202311466188.4A CN202311466188A CN117213532A CN 117213532 A CN117213532 A CN 117213532A CN 202311466188 A CN202311466188 A CN 202311466188A CN 117213532 A CN117213532 A CN 117213532A
- Authority
- CN
- China
- Prior art keywords
- data
- flexible
- flexible sensor
- preset
- current
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000001514 detection method Methods 0.000 claims abstract description 105
- 238000000034 method Methods 0.000 claims abstract description 36
- 238000007405 data analysis Methods 0.000 claims abstract description 17
- 230000008569 process Effects 0.000 claims description 22
- 238000004458 analytical method Methods 0.000 claims description 9
- 238000012360 testing method Methods 0.000 claims description 5
- 230000000694 effects Effects 0.000 abstract description 2
- 230000006870 function Effects 0.000 description 7
- 230000036541 health Effects 0.000 description 5
- 238000012545 processing Methods 0.000 description 5
- 238000007689 inspection Methods 0.000 description 3
- 239000000463 material Substances 0.000 description 3
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000004590 computer program Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000003745 diagnosis Methods 0.000 description 1
- 201000010099 disease Diseases 0.000 description 1
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000000758 substrate Substances 0.000 description 1
- 210000000707 wrist Anatomy 0.000 description 1
Landscapes
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
Abstract
The application relates to a multifunctional microfluidic flexible sensor, which belongs to the field of sensors, wherein the flexible sensor is internally provided with the following method, and the method comprises the steps of taking a current flexible sensor as a center and receiving the rest detection data of the rest flexible sensors in a preset range; acquiring current detection data of a current flexible sensor; analyzing the rest detection data and the current detection data according to a preset data analysis rule to determine error data; determining an error center flexible sensor from the error data; and calculating intersection flexible sensors contained in intersection of preset ranges of each error center flexible sensor, and determining a data detection error result according to the intersection flexible sensors. The application has the effect of improving the accuracy of the human body detection result.
Description
Technical Field
The application relates to the field of sensors, in particular to a multifunctional microfluidic flexible sensor.
Background
The flexible sensor is a sensor made of flexible materials, has good flexibility and ductility, can be freely bent or even folded, and can be arranged randomly according to application scenes due to flexible materials and structures, so that a measured unit can be conveniently detected; the flexibility is relatively rigid, and the flexible sensor adopts a flexible substrate which is a film; the application scene of the sensor is greatly expanded through breakthrough from rigidity to flexibility; not only intelligent wearing equipment in the game field, but also electronic skin, disease diagnosis equipment, health monitoring equipment, intelligent neck pillow, intelligent massage equipment in the medical large health field, intelligent wrist rings, metauniverse gloves in the consumption field, intelligent mattresses in the intelligent home field and the like; the flexible sensor is widely applied to the application scene; for the medical health field, when human body detection is performed by using a flexible sensor, a detection error may occur, which may lead to inaccurate final detection results.
Disclosure of Invention
The application provides a multifunctional microfluidic flexible sensor which has the characteristic of improving the accuracy of human body detection.
The above-mentioned application purpose of the application is realized through the following technical scheme:
a multi-functional microfluidic flexible sensor having performed therein a method comprising:
taking the current flexible sensor as a center, and receiving the rest detection data of the rest flexible sensors in a preset range;
acquiring current detection data of a current flexible sensor;
analyzing the rest detection data and the current detection data according to a preset data analysis rule to determine error data;
determining an error center flexible sensor from the error data;
and calculating intersection flexible sensors contained in intersection of preset ranges of each error center flexible sensor, and determining a data detection error result according to the intersection flexible sensors.
The present application may be further configured in a preferred example to: the centering around the current flexible sensor includes, each of the flexible sensors being considered a current flexible sensor.
The present application may be further configured in a preferred example to: the remaining flexible sensors within the preset range refer to at least one remaining flexible sensor within the preset range.
The present application may be further configured in a preferred example to: the step of analyzing the rest detection data and the current detection data according to a preset data analysis rule to determine error data comprises the following steps:
judging whether the current detection data and the rest detection data are the same type of data according to a preset data analysis rule;
if yes, calculating the difference value between the current detection data and the rest detection data, comparing the difference value with a preset difference value to obtain a comparison result, and determining error data according to the comparison result;
otherwise, determining error data according to the data types of the current flexible sensor and the data types of the rest flexible sensors.
The present application may be further configured in a preferred example to: the determining error data according to the data types of the current flexible sensor and the data types of the rest flexible sensors comprises the following steps:
the standard data types of the current flexible sensors of the rest flexible sensors with different data types in a preset range are called;
judging whether the data type of the current flexible sensor is the same as the standard data type;
if the data types of the flexible sensors are the same, determining error data according to the data types of the other flexible sensors;
otherwise, the detection data of the rest flexible sensors different from the current flexible sensor data type are regarded as error data.
The present application may be further configured in a preferred example to: calculating the difference value between the current detection data and the rest detection data, comparing the difference value with a preset difference value to obtain a comparison result, and determining error data according to the comparison result comprises:
calculating a difference value and a preset difference value to obtain a comparison difference value, wherein the comparison difference value is regarded as a comparison result;
and determining error data according to the comparison result and the preset difference value floating range information.
The present application may be further configured in a preferred example to: the determining error data according to the comparison result and the preset difference value floating range information comprises the following steps:
determining a comparison difference value according to the comparison result;
determining a preset difference value floating range value according to the preset difference value floating range information;
judging whether the comparison difference value is within the preset difference value floating range value or not;
if yes, temporarily storing the comparison process, and outputting error data pending information;
otherwise, the detection data of the corresponding remaining flexible sensors are regarded as error data.
The present application may be further configured in a preferred example to: after temporarily storing the comparison process and outputting the error data pending information, the method further comprises the steps of:
after the cycle time, carrying out overall analysis on all temporary comparison processes;
determining the number of identical flexible sensors in the temporary storage data;
trend analysis is performed on flexible sensors greater than a preset number.
In summary, the present application includes at least one of the following beneficial technical effects:
in the application, each flexible sensor is taken as a center, and detection data of other flexible sensors in a preset range are received; then obtaining the detection data of the current flexible sensor; analyzing the detection data of the current flexible sensor and the detection data of the other flexible sensors by using a preset data analysis rule, so as to judge error data; then analyzing the crossing range of each flexible sensor, and determining whether error data are in the crossing range, so that whether error data exist in the other flexible sensors can be directly judged; therefore, the detection process of each flexible sensor is avoided, and the detection convenience is improved; the accuracy of the detection data of the flexible sensor is ensured; thereby improving the accuracy of the data of human body detection.
Drawings
FIG. 1 is a flow chart of a method performed in a multifunctional microfluidic flexible sensor according to an embodiment of the present application.
Detailed Description
The present embodiment is only for explanation of the present application and is not to be construed as limiting the present application, and modifications to the present embodiment, which may not creatively contribute to the present application as required, are within the scope of the claims of the present application as far as they are protected by patent law.
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Embodiments of the application are described in further detail below with reference to the drawings.
The application provides a multifunctional microfluidic flexible sensor, wherein the flexible sensor is internally provided with a method, and the main flow of the method is described as follows.
As shown in fig. 1:
step S101: and taking the current flexible sensor as a center, and receiving the rest detection data of the rest flexible sensors in a preset range.
Step S102: and acquiring current detection data of the current flexible sensor.
Step S103: and analyzing the rest detection data and the current detection data according to a preset data analysis rule to determine error data.
Step S104: an error center flexible sensor is determined from the error data.
Step S105: and calculating intersection flexible sensors contained in intersection of preset ranges of each error center flexible sensor, and determining a data detection error result according to the intersection flexible sensors.
In the embodiment of the present application, analyzing the remaining detection data and the current detection data according to a preset data analysis rule to determine error data includes: judging whether the current detection data and the rest detection data are the same type of data according to a preset data analysis rule; if yes, calculating the difference value between the current detection data and the rest detection data, comparing the difference value with a preset difference value to obtain a comparison result, and determining error data according to the comparison result; otherwise, determining error data according to the data types of the current flexible sensor and the data types of the rest flexible sensors.
Determining error data based on the data type of the current flexible sensor and the data types of the remaining flexible sensors includes: the standard data types of the current flexible sensors of the rest flexible sensors with different data types in a preset range are called; judging whether the data type of the current flexible sensor is the same as the standard data type; if the data types of the flexible sensors are the same, determining error data according to the data types of the other flexible sensors; otherwise, the detection data of the rest flexible sensors different from the current flexible sensor data type are regarded as error data.
Calculating the difference value between the current detection data and the rest detection data, comparing the difference value with a preset difference value to obtain a comparison result, and determining error data according to the comparison result comprises the following steps: calculating a difference value and a preset difference value to obtain a comparison difference value, wherein the comparison difference value is regarded as a comparison result; determining error data according to the comparison result and the preset difference value floating range information; specifically, determining error data based on the comparison result and the preset difference floating range information includes: determining a comparison difference value according to the comparison result; determining a preset difference value floating range value according to the preset difference value floating range information; judging whether the comparison difference value is within the preset difference value floating range value or not; if yes, temporarily storing the comparison process, and outputting error data pending information; otherwise, the detection data of the corresponding remaining flexible sensors are regarded as error data.
It will be appreciated that in embodiments of the present application, including centering on the current flexible sensor, each flexible sensor is considered to be the current flexible sensor.
In the practical application scene, human body detection comprises a plurality of aspects, and is mainly applied to the field of medical treatment and health; the human body posture detection system can comprise multiple functions of human body health detection, human body posture detection and the like; the functions are realized by the cooperation of a plurality of flexible sensors, and the functions can be embodied in the modes of intelligent equipment, electronic skin, intelligent clothes and the like, so that in the process of acquiring human body detection data by using the equipment, the situation that errors occur in the detection data of one or more flexible sensors possibly exists, and each flexible sensor can only be detected independently in the conventional mode; however, the method is long in time consumption, consumes more manpower and material resources and is low in efficiency; in order to solve this problem, the present application adopts the following means.
Specifically, the current flexible sensor is taken as the center, the detection data of the rest flexible sensors in a preset range are received,
It will be appreciated that each flexible sensor is considered herein to be the current flexible sensor; and the remaining flexible sensors within the preset range at least comprise one remaining flexible sensor.
The flexible sensor is internally provided with a microprocessor and a data receiver; in this way, each flexible sensor can collect the detection data of the sensor and can also receive the detection data of the other flexible sensors in a preset range.
Then, the rest detection data and the current detection data can be analyzed by utilizing a preset data analysis rule; the specific analysis process comprises the steps of judging whether the current detection data and the rest detection data are the same type of data according to a preset data analysis rule; the same type of data refers to whether or not the same area of data is acquired.
It can be understood that when the human body is detected, the flexible sensor is connected to different parts and positions of the human body, so that when the current flexible sensor receives the rest flexible sensors in a preset range, the situation that the data types are the same or different may exist; for example, in an application scenario of the dynamic capturing device, a device wearer needs to wear the dynamic capturing device, and then the worn dynamic capturing device is used for capturing dynamic data of a human body at different positions, and then for a flexible sensor in the dynamic capturing device, the flexible sensor receives data sent by the rest flexible sensors in a preset range, and may possibly include different types of detection data.
Therefore, when judging whether the current detection data and the rest detection data are of the same type or not by utilizing a preset data analysis rule, if so, calculating the difference value of the current detection data and the rest detection data, comparing the difference value with a preset difference value to obtain a comparison result, and determining error data according to the comparison result; it will be appreciated that if the current test data and the remaining test data are of the same type, then it is stated that the two test data can be compared and calculated because the types are the same, and therefore only the data itself can be checked for problems.
Judging whether the current detection data and the rest detection data are of the same type or not by utilizing a preset data analysis rule, if not, determining error data according to the data type of the current flexible sensor and the data type of the rest flexible sensor; specifically, firstly, standard data types of the current flexible sensors of the rest flexible sensors with different data types in a preset range are called; it can be understood that the data types of the rest flexible sensors within the preset range of each flexible sensor are recorded in the database, and then only different types of rest flexible sensors exist within the preset range of the appointed several flexible sensors; therefore, only the data type of the current flexible sensor is compared with the standard data type, whether the data type and the standard data type are the same is judged, and if the data type is the same, the data type of the rest flexible sensors is wrong; if not, the detection data of the rest flexible sensors are error data.
In the above process, if there is data that the detection data of the flexible sensor is abnormal or possibly erroneous, the data itself needs to be judged; specifically, firstly, analyzing the data difference value of the current flexible sensor and the Yu Rouxing sensor; it can be understood that when errors occur in the detection data of the other flexible sensors, the data types of the current flexible sensor and the Yu Rouxing sensor are the same, so that the two sensors can be calculated, and the difference value of the two sensors is compared; comparing the difference value with a preset difference value, and determining error data according to a comparison result; it will be appreciated that in the actual calculation process, there must be a certain gap in the data between each flexible sensor, but the difference in the detected data of the flexible sensors in the same range should be a fixed floating range; therefore, the concept of the floating range information of the preset difference value is introduced, and the objectivity and the accuracy in the process of analyzing the difference value are ensured; analyzing and comparing whether the difference value is within a preset difference value floating range value, if so, indicating that the detection data of the flexible sensor corresponding to the comparison process and the flexible sensor within the preset range have no problem temporarily; and if the detection data are not in the floating range, indicating that the detection data of the corresponding other flexible sensors are error data.
In the embodiment of the application, the service time of the flexible sensor applying human body detection is longer, and more data are acquired, so that in the process, if the flexible sensor and the flexible sensor within the preset range are judged to have no problem temporarily, the comparison process and the detection data need to be temporarily stored; after the cycle time, carrying out overall analysis on all temporary storage comparison processes; determining the number of the same flexible sensors in the temporary storage data, and carrying out specific analysis on the flexible sensors with the number larger than the preset number; although the comparison difference value in each comparison process is within the preset floating range, the comparison difference value can be analyzed according to the change trend of the time axis comparison poor value to judge whether the comparison difference value is in a regular trend, if so, the flexible sensor and the flexible sensor within the preset range are proved to have problems, and detection is needed.
It can be appreciated that in the above process, by specifically analyzing the flexible sensor, when judging the trend of the comparison difference values, each comparison difference value can be screened, so as to remove some influencing factors, and as long as the general trend can be judged to show the regular trend, the flexible sensor is indicated to have a certain problem, and the flexible sensor needs to be detected.
Through the process, the small-range and small-number flexible sensors can be detected, whether errors occur or not is judged, data detection is not needed for each flexible sensor, the quality inspection efficiency of the sensor is improved, the quality inspection time is shortened, the quality inspection accuracy and flexibility are improved, and the accuracy of human body data detection is further improved.
The application also provides a system as an environment for carrying the execution method in the multifunctional microfluidic flexible sensor, which comprises a receiving module, a processing module and a processing module, wherein the receiving module is used for receiving the rest detection data of the rest flexible sensors in a preset range by taking the current flexible sensor as the center; the acquisition module is used for acquiring current detection data of the current flexible sensor; the analysis module is used for analyzing the rest detection data and the current detection data according to a preset data analysis rule to determine error data; the determining module is used for determining an error center flexible sensor according to the error data; the computing module is used for computing the intersection flexible sensor contained in the intersection of the preset range of each error center flexible sensor, and determining a data detection error result according to the intersection flexible sensor; by adopting the mode, the receiving module receives the detection data of the rest flexible sensors in the preset range through the combination of the modules; the acquisition module is used for acquiring detection data of the current flexible sensor; the analysis module analyzes the detection data of the current flexible sensor and the detection data of the rest flexible sensors by utilizing a preset data analysis rule; a determination module to determine an error center flexible sensor from the error data; finally, analyzing the crossing range of each flexible sensor, and determining whether error data are in the crossing range, so that whether error data exist in the other flexible sensors can be directly judged; therefore, the detection process of each flexible sensor is avoided, and the detection convenience is improved; the accuracy of the detection data of the flexible sensor is ensured; thereby improving the accuracy of the data of human body detection.
In order to better execute the program of the method, the application also provides a terminal, which comprises a memory and a processor.
Wherein the memory may be used to store instructions, programs, code, sets of codes, or sets of instructions. The memory may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function, instructions for implementing the method of executing within the multifunctional microfluidic flexible sensor described above, and the like; the data storage area may store data and the like involved in the method of performing the multifunctional microfluidic flexible sensor.
The processor may include one or more processing cores. The processor performs the various functions of the application and processes the data by executing or executing instructions, programs, code sets, or instruction sets stored in memory, calling data stored in memory. The processor may be at least one of an application specific integrated circuit, a digital signal processor, a digital signal processing device, a programmable logic device, a field programmable gate array, a central processing unit, a controller, a microcontroller, and a microprocessor. It will be appreciated that the electronics for implementing the above-described processor functions may be other for different devices, and embodiments of the present application are not particularly limited.
The present application also provides a computer-readable storage medium, for example, comprising: a U-disk, a removable hard disk, a Read Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes. The computer readable storage medium stores a computer program that can be loaded by a processor and that performs the method of performing within the multifunctional microfluidic flexible sensor described above.
The above description is only illustrative of the preferred embodiments of the present application and the principles of the technology being employed. It will be appreciated by persons skilled in the art that the scope of the disclosure referred to in the present application is not limited to the specific combinations of technical features described above, but also covers other technical features which may be formed by any combination of the technical features described above or their equivalents without departing from the spirit of the disclosure. Such as the above-mentioned features and the technical features disclosed in the present application (but not limited to) having similar functions are replaced with each other.
Claims (8)
1. A multi-functional microfluidic flexible sensor, wherein the flexible sensor has performed therein a method comprising:
taking the current flexible sensor as a center, and receiving the rest detection data of the rest flexible sensors in a preset range;
acquiring current detection data of a current flexible sensor;
analyzing the rest detection data and the current detection data according to a preset data analysis rule to determine error data;
determining an error center flexible sensor from the error data;
and calculating intersection flexible sensors contained in intersection of preset ranges of each error center flexible sensor, and determining a data detection error result according to the intersection flexible sensors.
2. The multi-functional microfluidic flexible sensor of claim 1, wherein the centering around the current flexible sensor comprises, each flexible sensor being considered a current flexible sensor.
3. The multifunctional microfluidic flexible sensor of claim 1, wherein the remaining flexible sensors within the predetermined range comprise at least one remaining flexible sensor within the predetermined range.
4. The multifunctional microfluidic flexible sensor according to claim 1, wherein the analyzing the remaining detection data and the current detection data according to a preset data analysis rule to determine error data comprises:
judging whether the current detection data and the rest detection data are the same type of data according to a preset data analysis rule;
if yes, calculating the difference value between the current detection data and the rest detection data, comparing the difference value with a preset difference value to obtain a comparison result, and determining error data according to the comparison result;
otherwise, determining error data according to the data types of the current flexible sensor and the data types of the rest flexible sensors.
5. The multi-functional microfluidic flexible sensor of claim 4, wherein the determining error data based on the data type of the current flexible sensor and the data types of the remaining flexible sensors comprises:
the standard data types of the current flexible sensors of the rest flexible sensors with different data types in a preset range are called;
judging whether the data type of the current flexible sensor is the same as the standard data type;
if the data types of the flexible sensors are the same, determining error data according to the data types of the other flexible sensors;
otherwise, the detection data of the rest flexible sensors different from the current flexible sensor data type are regarded as error data.
6. The sensor of claim 4, wherein calculating a difference between the current test data and the remaining test data, comparing the difference with a predetermined difference to obtain a comparison result, and determining error data based on the comparison result comprises:
calculating a difference value and a preset difference value to obtain a comparison difference value, wherein the comparison difference value is regarded as a comparison result;
and determining error data according to the comparison result and the preset difference value floating range information.
7. The multifunctional microfluidic flexible sensor according to claim 6, wherein the determining error data according to the comparison result and the preset difference floating range information comprises:
determining a comparison difference value according to the comparison result;
determining a preset difference value floating range value according to the preset difference value floating range information;
judging whether the comparison difference value is within the preset difference value floating range value or not;
if yes, temporarily storing the comparison process, and outputting error data pending information;
otherwise, the detection data of the corresponding remaining flexible sensors are regarded as error data.
8. The multifunctional microfluidic flexible sensor according to claim 7, wherein after temporarily storing the comparison process and outputting error data pending information, further comprising:
after the cycle time, carrying out overall analysis on all temporary comparison processes;
determining the number of identical flexible sensors in the temporary storage data;
trend analysis is performed on flexible sensors greater than a preset number.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311466188.4A CN117213532B (en) | 2023-11-07 | 2023-11-07 | Multifunctional microfluidic flexible sensor |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311466188.4A CN117213532B (en) | 2023-11-07 | 2023-11-07 | Multifunctional microfluidic flexible sensor |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117213532A true CN117213532A (en) | 2023-12-12 |
| CN117213532B CN117213532B (en) | 2024-01-23 |
Family
ID=89042914
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311466188.4A Active CN117213532B (en) | 2023-11-07 | 2023-11-07 | Multifunctional microfluidic flexible sensor |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117213532B (en) |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101394556B1 (en) * | 2013-02-27 | 2014-05-14 | 창원대학교 산학협력단 | Apparatus and method for rotor position sensor fault detection of permanent magnet synchronous motor |
| CA2897791A1 (en) * | 2013-01-25 | 2014-07-31 | Vanderbilt Universtiy | Smart mobile health monitoring system and related methods |
| WO2015109938A1 (en) * | 2014-01-24 | 2015-07-30 | 北京奇虎科技有限公司 | Apparatus and method for judging effectiveness of operations of head-mounted smart device and effectiveness of authentication information |
| US20170231573A1 (en) * | 2016-02-16 | 2017-08-17 | Bruce Reiner | Method and apparatus for embedded sensors in diagnostic and therapeutic medical devices |
| US9852599B1 (en) * | 2015-08-17 | 2017-12-26 | Alarm.Com Incorporated | Safety monitoring platform |
| US20190000384A1 (en) * | 2017-06-30 | 2019-01-03 | Myant Inc. | Method for sensing of biometric data and use thereof for determining emotional state of a user |
| CN112399823A (en) * | 2018-07-17 | 2021-02-23 | 索尼公司 | Biological information processing apparatus and information processing method |
| CN113176011A (en) * | 2021-04-30 | 2021-07-27 | 南京安控易创润滑科技有限公司 | Intelligent temperature measuring method and system of surface mounted sensor based on Internet of things |
| CN113316413A (en) * | 2018-10-31 | 2021-08-27 | 西北大学 | Sensor network for measuring physiological parameters of mammalian subjects and use thereof |
| US20220031241A1 (en) * | 2020-07-28 | 2022-02-03 | Xsensor Technology Corporation | Foot sensor and other sensor pads |
| CN114280450A (en) * | 2021-12-10 | 2022-04-05 | 北京航天测控技术有限公司 | Butt joint detection device and method |
| CN115238716A (en) * | 2022-07-26 | 2022-10-25 | 宁波爱科特环境电器有限公司 | Sensor control method, system, storage medium and intelligent terminal |
| US20230147160A1 (en) * | 2021-03-31 | 2023-05-11 | The Johns Hopkins University | Blunt Force Sensor Array |
| CN116153505A (en) * | 2023-04-21 | 2023-05-23 | 苏州森斯缔夫传感科技有限公司 | Intelligent critical patient sign identification method and system based on medical pressure sensor |
-
2023
- 2023-11-07 CN CN202311466188.4A patent/CN117213532B/en active Active
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2897791A1 (en) * | 2013-01-25 | 2014-07-31 | Vanderbilt Universtiy | Smart mobile health monitoring system and related methods |
| KR101394556B1 (en) * | 2013-02-27 | 2014-05-14 | 창원대학교 산학협력단 | Apparatus and method for rotor position sensor fault detection of permanent magnet synchronous motor |
| WO2015109938A1 (en) * | 2014-01-24 | 2015-07-30 | 北京奇虎科技有限公司 | Apparatus and method for judging effectiveness of operations of head-mounted smart device and effectiveness of authentication information |
| US9852599B1 (en) * | 2015-08-17 | 2017-12-26 | Alarm.Com Incorporated | Safety monitoring platform |
| US20170231573A1 (en) * | 2016-02-16 | 2017-08-17 | Bruce Reiner | Method and apparatus for embedded sensors in diagnostic and therapeutic medical devices |
| US20190000384A1 (en) * | 2017-06-30 | 2019-01-03 | Myant Inc. | Method for sensing of biometric data and use thereof for determining emotional state of a user |
| CN112399823A (en) * | 2018-07-17 | 2021-02-23 | 索尼公司 | Biological information processing apparatus and information processing method |
| CN113316413A (en) * | 2018-10-31 | 2021-08-27 | 西北大学 | Sensor network for measuring physiological parameters of mammalian subjects and use thereof |
| US20220031241A1 (en) * | 2020-07-28 | 2022-02-03 | Xsensor Technology Corporation | Foot sensor and other sensor pads |
| US20230147160A1 (en) * | 2021-03-31 | 2023-05-11 | The Johns Hopkins University | Blunt Force Sensor Array |
| CN113176011A (en) * | 2021-04-30 | 2021-07-27 | 南京安控易创润滑科技有限公司 | Intelligent temperature measuring method and system of surface mounted sensor based on Internet of things |
| CN114280450A (en) * | 2021-12-10 | 2022-04-05 | 北京航天测控技术有限公司 | Butt joint detection device and method |
| CN115238716A (en) * | 2022-07-26 | 2022-10-25 | 宁波爱科特环境电器有限公司 | Sensor control method, system, storage medium and intelligent terminal |
| CN116153505A (en) * | 2023-04-21 | 2023-05-23 | 苏州森斯缔夫传感科技有限公司 | Intelligent critical patient sign identification method and system based on medical pressure sensor |
Non-Patent Citations (2)
| Title |
|---|
| 刘少华;徐超;许金林;许胜强;元沐南;: "基于柔性力敏传感器的便携式坐姿监测与提醒***", 计算机***应用, no. 07 * |
| 徐小力;刘秀丽;蒋章雷;任彬;: "基于主观贝叶斯推理的多传感器分布式故障检测融合方法", 机械工程学报, no. 07 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117213532B (en) | 2024-01-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| WO2018176348A1 (en) | Wearable device, wearing quality detection method and apparatus | |
| CN108324271B (en) | Electrocardiosignal identification method and system and electrocardiosignal monitoring equipment | |
| CN102551701A (en) | System and method of detecting abnormal movement of a physical object | |
| CN111631715B (en) | Method for predicting early cognitive function decline of Alzheimer's disease | |
| CN108937866B (en) | Sleep state monitoring method and device | |
| CN112861947B (en) | Sensor data processing method and device and computing equipment | |
| CN116196013B (en) | Electrocardiogram data processing method, device, computer equipment and storage medium | |
| CN110909826A (en) | Diagnosis monitoring method and device for energy equipment and electronic equipment | |
| CN105630158A (en) | Sensor data processing method and apparatus, and terminal device | |
| WO2019121655A1 (en) | A probability-based detector and controller apparatus, method, computer program | |
| CN117213532B (en) | Multifunctional microfluidic flexible sensor | |
| CN105389575A (en) | Processing method and device for biological data | |
| CN110796697B (en) | General surgery ward object size identification platform and method | |
| CN112102837B (en) | Household electrical appliance and pickup detection method and device thereof | |
| US20120270192A1 (en) | Behavior estimation apparatus, behavior estimation method, and computer readable medium | |
| CN114533010A (en) | Heart rate detection method and device | |
| CN112799911A (en) | Node health state detection method, device, equipment and storage medium | |
| CN113974575B (en) | Sleep staging method and device, electronic equipment and storage medium | |
| CN117860238A (en) | Exercise function test method, system, terminal and storage medium | |
| JP3726825B2 (en) | Heart rate signal correction method | |
| CN110706803A (en) | Method, device, readable medium and electronic equipment for determining myocardial fibrosis | |
| CN116912203B (en) | Abnormal fundus image low-consumption detection method and system based on combination of multiple intelligent models | |
| CN116965785A (en) | Vital sign monitoring and analyzing method, system, terminal and storage medium | |
| JP2019158426A (en) | Presence determination method, program, sensor processing system, and sensor system | |
| CN116895360B (en) | Drug curative effect prediction method, system, terminal and storage medium applied to MCI patient |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |