Tremor detection system based on bidirectional long-short-term memory neural network

Abstract

The invention provides a tremor detection system based on a bidirectional long-short-term memory neural network, relates to the field of artificial intelligence, and aims to solve the problem of low accuracy of tremor detection in the prior art. The tremor detection system comprises a hand detection module and a model prediction module, wherein the hand detection module comprises a tremor data acquisition unit and a tremor data processing unit; the tremor data acquisition unit is used for acquiring a hand three-axis acceleration signal; the tremor data processing unit is used for converting the hand three-axis acceleration signal into hand three-axis acceleration data; the model prediction module comprises a hand tremor data processing unit and a model training unit; the hand tremor data processing unit is used for processing the received three-axis acceleration data to obtain a training set and a test set; and the model training unit is used for training a model by utilizing the training set and the test set to obtain a trained model. The tremor detection system is used for tremor detection and is high in detection efficiency.

Description

technical field [0001] The invention relates to the field of artificial intelligence, in particular to a tremor detection system based on a bidirectional long-short-term memory neural network. Background technique [0002] Hand tremor is a common clinical manifestation, seen in a variety of neurological diseases, including essential tremor, Parkinson's disease, psychogenic tremor, dystonic tremor, cerebellar tremor, metabolic tremor, peripheral neuropathic tremor, Hepatolenticular degeneration and other diseases. Although the frequency and amplitude of tremors in different diseases are not the same, for example, essential tremor usually has a low amplitude and fast frequency (8-10Hz), and the tremor frequency of Parkinson's disease is usually 4-6Hz. It is easily affected by the subjective factors of the tester, the evaluation cannot be objective and accurate, the sensitivity is not high, and small changes cannot be measured. [0003] In recent years, the development of mac...

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Problems solved by technology

[0004] The purpose of the present invention is: aiming at the problem of low accuracy of tremor detection in the prior art, a tremor detection system based on bidirectional long-short-term memory neural network is proposed

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