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Classification of Abnormal Gait Based on Improved Two-Stream CNN

Gait is a guidance of clinical diagnosis and an evaluation index for disease rehabilitation. Various diseases such as Parkinson's disease, hemiplegia and cerebellar ataxia can cause gait abnormalities. In this paper, we proposed an algorithm based on two-stream convolution neural network and attention mechanism. The algorithm can classify abnormal gait from input gait videos. Our proposed method achieved 86.28% accuracy in our gait data set.