The surface electromyogram (sEMG) based motion intent recognition has been considered as a promising approach for prosthetic hand control. However, the variations of EMG signals in daily applications and the insufficient residual muscles of amputees make the clinical application of EMG-based prosthesis remain a challenge. Tactile signals provide critical haptic information for human beings during object manipulation, which is expected to serve as a signal source for motion intent recognition. In this study, a novel tactile-triggered method of motion intent recognition and prosthetic hand control was proposed. This method is implemented by a finite state machine (FSM) using a multi-axis tactile sensor and is deployed in an integrated system. Validation consisted of three evaluation tests, the last involving both able-bodied and transradial-amputee participants. For comparison, the EMG pattern recognition (EMG-PR) control method was also implemented in all three tests. The experimental results demonstrate that the tactile-triggered control strategy provides an effective approach for prosthetic hand opening/closing control, enabling stable grasping of diverse objects of varying shapes and sizes. Compared to EMG-PR, this method substantially eliminates control performance degradation caused by arm posture changes and exhibits superior grasping stability. Additionally, it avoids muscle fatigue in users. This approach offers a promising prosthetic control strategy that can either function as a non-EMG control paradigm or serve as a complementary modality to myoelectric control.
Lan et al. (2026) studied this question.