Rehabilitation training motion state monitoring method and system fusing electrocardiogram and myoelectricity characteristics

A technology of motion state and rehabilitation training, applied in the field of rehabilitation training, can solve the problems of restricting the movement of testers, reducing the signal-to-noise ratio, and prone to fatigue, etc., to improve generalization performance and classification accuracy, reduce coupling and redundancy, and improve The effect of representational ability

Pending Publication Date: 2020-04-10
QUFU NORMAL UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the state of exercise is a complex phenomenon. During the rehabilitation process of patients who have lost part or all of their exercise capacity, they are prone to fatigue and insufficient strength due to their incomplete motor function. Therefore, the signal-to-noise ratio decreases with the increase of training time. , the classification results of pure EMG signals are unstable and the accuracy is low
In addition, due to the large individual differences, the high complexity of EMG signals, and the characteristics of being susceptible to noise interference, the reliability

Method used

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  • Rehabilitation training motion state monitoring method and system fusing electrocardiogram and myoelectricity characteristics
  • Rehabilitation training motion state monitoring method and system fusing electrocardiogram and myoelectricity characteristics
  • Rehabilitation training motion state monitoring method and system fusing electrocardiogram and myoelectricity characteristics

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Embodiment 1

[0048] This embodiment discloses a method for monitoring the exercise state of rehabilitation training that combines ECG and EMG features, such as figure 1 shown, including the following steps:

[0049] Step 1: Receive the ECG signal and EMG signal transmitted by the physiological signal acquisition device, as well as the corresponding exercise state, and store and preprocess them.

[0050] Wherein, the preprocessing specifically includes: respectively preprocessing the two signals collected by the signal acquisition device per second according to the order of sampling time, and the signal monitoring terminal performs preprocessing on the two signals collected by the signal acquisition device every second The processing methods for collecting the two signals are the same, and the preprocessing process mainly includes signal filtering, time window processing, and ECG R wave marking.

[0051] In this embodiment, the myoelectric signal collected is the lower limb myoelectric sig...

Embodiment 2

[0084] A rehabilitation training exercise state monitoring system that integrates electrocardiogram and electromyography features includes: a host computer, and a physiological signal acquisition device connected to the host computer. in,

[0085] The physiological signal acquisition device is used to collect the ECG and EMG signals of the tester according to the set sampling frequency, and transmit the collected signals to the host computer synchronously.

[0086] Specifically, according to the physiological structure of the human body, the position of the main relevant muscles used for rehabilitation training is determined, wherein the position of the determined muscle belly is the collection position of the wireless sensor, and the collection position of the central electrical sensor is the left midline of the clavicle and the fifth rib intersection between. In order to ensure the integrity of the signal under the premise of ensuring the communication rate between the inst...

Embodiment 3

[0096] The purpose of this embodiment is to provide an electronic device.

[0097] An electronic device, comprising a memory, a processor, and a computer program stored on the memory and operable on the processor, when the processor executes the program, the following steps are implemented, including:

[0098] Step 1: Receive the ECG signal and EMG signal transmitted by the physiological signal acquisition device, identify the corresponding exercise state, and store and preprocess it.

[0099] Step 2: Perform feature extraction on the ECG signal and EMG signal.

[0100] Step 3: Based on the random fusion coefficient vector, the features of the ECG signal and the EMG signal are fused to obtain the fused feature vector.

[0101] Step 4: According to the fusion feature vector and based on the support vector machine, learn the multi-classification motion state recognition model; and use the particle swarm optimization algorithm to optimize the fusion coefficient vector to obtain ...

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Abstract

The invention discloses a rehabilitation training motion state monitoring method and system fusing electrocardiogram and myoelectricity characteristics. The method comprises the following steps: obtaining an electrocardiogram signal and a myoelectricity signal and performing characteristic extraction respectively; performing characteristic fusion based on a random fusion coefficient vector to obtain a fusion characteristic vector; learning a multi-classification motion state recognition model based on a support vector machine by adopting the fusion characteristic vector; performing iterative optimization on the fusion coefficient vector by adopting a particle swarm algorithm to obtain an optimal fusion coefficient vector and a multi-classification motion state recognition offline model; and performing motion state recognition based on the fusion characteristic vector of the electrocardiogram signal and the myoelectricty signal collected in real time. According to the invention, electrocardiogram and myoelectricity signals are fused for motion state detection, so accuracy and reliability are greatly improved, and real-time monitoring of the motion state of rehabilitation training ofa patient is achieved; the motion state can be used as the basis for real-time adjustment of rehabilitation training task intensity and a control strategy, the rehabilitation training effect is enhanced, and secondary injuries caused by excessive training are avoided.

Description

technical field [0001] The invention belongs to the technical field of rehabilitation training, in particular to a rehabilitation training exercise state monitoring method and system which integrates electrocardiogram and myoelectric characteristics. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art. [0003] With the aging population and the increasing number of stroke patients in our country, traditional medical rehabilitation specialists are far from being able to meet the needs of the market. Rehabilitation training robots combined with robotics, biomedicine, intelligent control and other multidisciplinary technologies have emerged as the times require. Its It has greatly alleviated the current situation of resource shortage of rehabilitation trainers. However, traditional program-controlled rehabilitation robots such as exoskeleton robots and ...

Claims

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Application Information

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IPC IPC(8): A61B5/0402A61B5/0488A61B5/00
CPCA61B5/7235A61B5/7267A61B5/7271A61B5/7203A61B5/725A61B5/316A61B5/318A61B5/389
Inventor 曹佃国武玉强解学军苑尧尧陈威王加帅张敬宇
Owner QUFU NORMAL UNIV
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