Qi Liu1, Zihao Wu1,*, Xiaodong Liu2
Journal on Internet of Things, Vol.4, No.3, pp. 169-181, 2022, DOI:10.32604/jiot.2022.040368
Abstract This study proposed a lightweight but high-performance convolution network for accurately classifying five upper limb movements of arm, involving forearm flexion and rotation, arm extension, lumbar touch and no reaction state, aiming to monitoring patient’s rehabilitation process and assist the therapist in elevating patient compliance with treatment. To achieve this goal, a lightweight convolution neural network TMCA-Net (Time Multiscale Channel Attention Convolutional Neural Network) is designed, which combines attention mechanism, uses multi-branched convolution structure to automatically extract feature information at different scales from sensor data, and filters feature information based on attention mechanism. In particular, channel separation convolution is used… More >
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