fig5

Figure 5. (A) Schematic flowchart of the AES-128 encryption algorithm; (B) Representative sEMG signal waveforms before and after encryption; (C) Representative strain-sensing signal waveforms before and after encryption; (D) Software workflow of the gait-based identity recognition system; (E) Architecture of the proposed ByteEmbedded-TCN model; (F) t-distributed stochastic neighbor embedding (t-SNE) visualization of identity recognition clustering results; (G) Training and validation loss curves of the neural network model; (H) Training and validation accuracy curves of the neural network model; (I) Confusion matrix illustrating the recognition performance of the proposed system. AES-128: Advanced Encryption Standard-128; sEMG: Surface electromyography; ByteEmbedded-TCN: ByteEmbedded Temporal Convolutional Network; EMG: electromyography; Train_Acc: training accuracy; Val_Acc: validation accuracy.