ViT-LLMR: Vision Transformer-based lower limb motion recognition from fusion signals of MMG and IMU

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End-to-End Lower Limb Motion Recognition with Modal-Channel Attention and Dual-Branch Adaptive Fusion Network via sEMG and Kinematic Data

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Lower Limb Movement Recognition Based on a Hybrid Deep Learning Model Using Surface Electromyography

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Recognizing Lower Limb Motion Intention through the Fusion of Multimodal sEMG and VMG Signals

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Hybrid CNN-LSTM Framework for Upper-Limb Motion Recognition Using Wearable IMU Sensors

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Interpretable Res-ViTNet with Multiview Interaction and Multiobjective Optimization for sEMG-based LLMI Recognition

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