Based on Convolutional Long-Short Term Memory Neural Network,the authors proposed a deep learning method PressureConvLSTM to extract features during walking in both spatial and temporal dimensions.Classi-fication based on plantar pressure of anterior cruciate ligament deficiency(ACLD)was applied to distinguish walking gait information.Experiment results combined with clinical data showed that PressureConvLSTM model obtained 95%test accuracy when diagnosing ACLD,which was well performed over other traditional deep learning models.
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