Arm ring for neuromuscular disease detection and use method thereof

Abstract

The invention discloses an armlet structure for neuromuscular disease detection and a signal acquisition and processing method thereof. The armlet comprises a muscle force sensing module, a myoelectricity-electrical impedance sensing module, a signal conditioning module, a main control module, a signal processing module and a fixing module. The main control module is used for controlling the working state of the system and sending information collected by the sensing module to the signal processing module; the signal processing module is used for processing the acquired information and judging the progress of the neuromuscular disease; the fixing module is an elastic rubber belt, and the sensor is completely attached to arm muscles. According to the invention, the position of an armlet is determined by using an EIT signal, and muscle position sub-calibration is carried out; determining the contact state of the armlet and the skin by using the muscle force signal, and pre-calibrating the electromyographic signal; and disease detection is carried out through transmission characteristics of myoelectricity and muscle force signals. The armlet system has the advantages of being portable, easy to operate and high in accuracy.

Description

technical field [0001] The invention relates to the technical field of medical devices, and more particularly to a wearable armband with a neuromuscular disease detection function and a method for using the same. Background technique [0002] Neuromuscular disease is a kind of abnormal motor control caused by the transmission disorder between nerve and muscle, mainly including myositis, metabolic myopathy, neuromuscular junction disease, myasthenia gravis and so on. Sports training is one of the important rehabilitation methods for neuromuscular diseases, which requires long-term strength training and rehabilitation tracking detection. The current clinical detection methods are mainly clinical observation by doctors and biochemical index detection, which are invasive measurements, and the process is complicated and needs to be carried out in the hospital. Therefore, the development of convenient and non-invasive neuromuscular detection methods to monitor the rehabilitation ...

AI Technical Summary

Problems solved by technology

However, this invention only realizes the measurement of muscle activation state, but lacks the tracking of muscle force, making it difficult to provide comprehensive clinical data for the detection of neuromuscular diseases

Moreover, the device cannot identify the muscle position independently, and it is necessary to align each sensor with the anatomical detection position in advance, which is complicated to use

[0004] Existing methods have the problems of poor portability and complicated measurement process

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