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A real-time gait analysis method based on motor current and sensor feedback

A technology of motor current and analysis method, which is applied in the direction of sensors, passive exercise equipment, medical science, etc., can solve the problems of difficult wide application, cumbersome operation and high user requirements, and achieve reliable training basis, accurate data and easy analysis, Simple and convenient operation

Active Publication Date: 2022-03-15
NANJING VISHEE MEDICAL TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, although the time-domain characteristics are easy to extract, a large number of studies have shown that when the muscle contraction force changes slightly, the time-domain characteristics of the surface EMG signal change greatly and are not stable.
Moreover, in actual clinical applications, the requirements for users are relatively high, it is difficult to locate, and the operation and use are relatively cumbersome, so it is difficult to be widely used clinically.
In addition, the method of directly detecting muscle signals requires the patient to actively move, and the gait of the patient in passive mode cannot be accurately analyzed

Method used

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  • A real-time gait analysis method based on motor current and sensor feedback
  • A real-time gait analysis method based on motor current and sensor feedback
  • A real-time gait analysis method based on motor current and sensor feedback

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0057] S1 obtains patient medical history data:

[0058] Basic Information:

[0059] Name: Wang Xiaoshu; Gender: Male; Height: 173cm Weight: 65kg;

[0060] vital signs:

[0061] Heart rate: 76 beats / min; blood pressure: 120 / 80mmHg;

[0062] Quiet breathing: 18 times / min; Body temperature: 36.8°C;

[0063] Physical examination:

[0064] Skin Integrity: Complete;

[0065] Does the range of motion of the joint affect the wearing of the machine: No;

[0066] Functional assessment:

[0067] Hip range of motion: normal; knee range of motion: normal; ankle range of motion: normal;

[0068] Fugl-Meyer motor function evaluation: 23 / 34 points;

[0069] Modified Barthel index: 20 points;

[0070] Strength: Hip flexion: Grade 1; Hip extension: Grade 2; Hip adduction: Grade 2; Hip abduction: Grade 1

[0071] Knee flexion: grade 1; knee extension: grade 2;

[0072] Ankle flexion: grade 1; ankle extension: grade 0;

[0073] Disease diagnosis: cerebral hemorrhage;

[0074] Course...

Embodiment 2

[0103] S1 obtains patient medical history data:

[0104] Basic Information:

[0105]Name: Chen Ying; Gender: Female; Height: 161cm Weight: 55kg;

[0106] vital signs:

[0107] Heart rate: 88 beats / min; blood pressure: 132 / 80mmHg;

[0108] Quiet breathing: 18 times / min; Body temperature: 36.6°C;

[0109] Physical examination:

[0110] Skin Integrity: Complete;

[0111] Does the range of motion of the joint affect the wearing of the machine: No;

[0112] Functional assessment:

[0113] Hip range of motion: normal; knee range of motion: normal; ankle range of motion: normal;

[0114] Fugl-Meyer motor function evaluation: 15 / 34 points;

[0115] Modified Barthel index: 50 points;

[0116] Strength: Hip flexion: Grade 3; Hip extension: Grade 3+; Hip adduction: Grade 2; Hip abduction: Grade 2

[0117] Knee flexion: Grade 2+; Knee extension: Grade 2+;

[0118] Ankle flexion: grade 1; ankle extension: grade 0;

[0119] Disease diagnosis: cerebral hemorrhage;

[0120] Cours...

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Abstract

The invention discloses a real-time gait analysis method based on motor current and sensor feedback, comprising the following steps: 1) debugging equipment; 2) wearing equipment: making the human body to be tested complete the wearing of the lower limb exoskeleton robot; 3) setting the motion mode , step length, step height, and gait cycle to form motion parameter data; the motion mode is passive mode, and the gait trajectory of the human body to be tested is controlled by the lower extremity exoskeleton robot; 4) Obtain walking gait data: including the joints in the walking process , and the current value of the motor corresponding to each joint and / or the torque value of each joint; 5) Integrate the data and display it in a chart; 6) According to the chart, analyze the gait function or ability of the human body to be tested. The state analysis method is standardized and integrated, and automatic analysis is realized at the same time. The output results provide reliable medical data for doctors and therapists, and provide a reliable training basis for subsequent adjustments to rehabilitation training programs.

Description

technical field [0001] The invention relates to a real-time gait analysis method based on motor current and sensor feedback, belonging to the technical field of gait analysis. Background technique [0002] At present, there are various gait analysis equipment for patients (such as patients in the recovery period of lower limb motor dysfunction caused by stroke, spinal cord injury, etc.) in clinical practice, such as the EMG used in the early stage, all of which have direct functions. This is achieved by detecting muscle signals. The method of EMG signal processing is to treat the EMG signal as a random signal with a mean value of zero and a variance that changes with the signal strength. The extraction of time domain features is relatively simple. However, although the time-domain characteristics are easy to extract, a large number of studies have shown that when the muscle contraction force changes slightly, the time-domain characteristics of the surface electromyography ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): A61B5/11A61H1/02
CPCA61B5/112A61B5/6802A61H1/0262A61B2560/0468A61B2560/0266A61B2562/06A61H2201/1223A61H2201/5061A61H2201/5007
Inventor 徐海东黄河
Owner NANJING VISHEE MEDICAL TECH
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