Wrist workload prediction method and device based on multi-modal physiological data acquisition

A technology of physiological data and workload, applied in the direction of diagnostic signal processing, diagnostic recording/measurement, medical science, etc., to achieve the effect of preventing the occurrence of cumulative trauma diseases

Active Publication Date: 2021-01-29
北京中科心研科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The embodiment of the present application provides a wrist workload prediction method based on multimodal physiological data collection, which solves the problem caused by long-term overload work of the wrist. The technical problem of the occurrence of traumatic diseases has achieved the technical effect of preventing the occurrence of cumulative traumatic diseases through the collection of various physiological data of the wrist

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  • Wrist workload prediction method and device based on multi-modal physiological data acquisition
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  • Wrist workload prediction method and device based on multi-modal physiological data acquisition

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Embodiment 1

[0023] Such as figure 1 As shown, the embodiment of the present application provides a method for predicting wrist workload based on multimodal physiological data collection, wherein the method is applied to a wrist smart wearable device, and the wrist smart wearable device can pass The electrodes are connected to the wrist of the first user, the method comprising:

[0024] Step S100: Obtaining a first myoelectric signal, a second myoelectric signal, a third myoelectric signal and a fourth myoelectric signal according to the electrodes;

[0025] Specifically, the wrist workload is collected based on the wrist smart wearable device, and the wrist smart wearable device can be connected to the wrist of the first user through four electrodes for data collection. The first myoelectric signal is the muscle electrical signal of the flexor carpi ulnaris, the second myoelectric signal is the muscle electrical signal of the flexor carpi radialis, the third myoelectric signal is the mus...

Embodiment 2

[0079] Based on the same inventive concept as the method for predicting wrist workload based on multimodal physiological data collection in the foregoing embodiments, the present invention also provides a wrist workload prediction device based on multimodal physiological data collection, Such as figure 2 As shown, the device includes:

[0080] The first obtaining unit 11: the first obtaining unit 11 is used to obtain the first myoelectric signal, the second myoelectric signal, the third myoelectric signal and the fourth myoelectric signal according to the electrodes;

[0081] The second obtaining unit 12: the second obtaining unit 12 is configured to obtain first input information according to the first myoelectric signal;

[0082] The third obtaining unit 13: the third obtaining unit 13 is configured to obtain second input information according to the second myoelectric signal;

[0083] The fourth obtaining unit 14: the fourth obtaining unit 14 is configured to obtain thir...

Embodiment 3

[0120] Refer below image 3 An electronic device according to an embodiment of the present application will be described.

[0121] image 3 A schematic structural diagram of an electronic device according to an embodiment of the present application is shown.

[0122] Based on the inventive concept of a wrist workload prediction method based on multimodal physiological data collection in the foregoing embodiments, the present invention also provides a wrist workload prediction device based on multimodal physiological data collection, which A computer program is stored on the computer, and when the program is executed by the processor, the steps of any one of the aforementioned methods for predicting wrist workload based on multimodal physiological data collection are implemented.

[0123] Among them, in image 3 In, bus architecture (represented by bus 300), bus 300 may include any number of interconnected buses and bridges, bus 300 will include one or more processors repres...

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Abstract

The invention discloses a wrist workload prediction method based on multi-modal physiological data acquisition. The method comprises the steps: obtaining a first electromyographic signal, a second electromyographic signal, a third electromyographic signal and a fourth electromyographic signal according to electrodes; obtaining first input information, second input information, third input information and fourth input information according to the first electromyographic signal, the second electromyographic signal, the third electromyographic signal and the fourth electromyographic signal respectively; inputting the first input information, the second input information, the third input information and the fourth input information into a motion prediction model to obtain a first motion index;obtaining a predetermined wrist load threshold; judging whether the first motion index is within a preset wrist load threshold value or not; and if the first motion index is not within the predetermined wrist load threshold, obtaining first early warning information. The technical problem of traumatic diseases caused by long-term overload work of the wrist is solved.

Description

technical field [0001] The present invention relates to the technical field of wrist workload prediction, in particular to a wrist workload prediction method and device based on multimodal physiological data collection. Background technique [0002] At present, more and more evidence shows that long-term use of computers, playing musical instruments, sports, etc. are closely related to certain wrist diseases, such as wrist pain and carpal tunnel syndrome. Changes in modern lifestyles have given more and more people the opportunity to use computers and engage in various physical activities, and more and more people suffer from wrist-related diseases. [0003] However, in the process of realizing the technical solution of the invention in the embodiment of the present application, the inventor of the present application found that the above-mentioned technology has at least the following technical problems: [0004] The long-term increase in wrist joint activity makes the wri...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/397A61B5/296A61B5/11A61B5/00
CPCA61B5/11A61B5/1121A61B5/1126A61B5/459A61B5/6802A61B5/72A61B5/7275A61B5/746A61B5/7267
Inventor 许子卿赵国朕
Owner 北京中科心研科技有限公司
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