Miniaturized Wearable Ultrasound System for Simultaneous Prediction of Wrist Angle and Grip Force During Dynamic Reaching - Rima, Afsana Hossain; Taghizadeh, Zahra; Bashatah, Ahmed; Aher, Abhishek; Sikdar, Siddhartha (IEEE International Conference on Rehabilitation Robotics, 2025)
Predicting grip force and wrist angle during dynamic hand movements is crucial for advancing upper-limb prosthetic systems, enabling simultaneous and proportional control of multiple degrees of freedom (DOFs). This study introduces a novel wearable ultrasound-based system that leverages M-mode data from four single-element transducers placed on the forearm to capture muscle activity for the concurrent prediction of grip force and wrist angle. A multi-layer perceptron (MLP) regressor was utilized for the simultaneous prediction of both parameters, and a comparative analysis was conducted using a Gaussian process regressor (GPR), which is commonly adopted previously in similar studies. The system was validated on unseen data from five participants without limb loss. The MLP demonstrated superior performance compared to GPR, achieving R^{2} values of 0.85 ± 0.06 for wrist angle prediction and 0.74 ± 0.07 for grip force. These findings underscore the challenges of predicting simultaneous grip force and wrist angle during dynamic hand movements and highlight the need to address these issues for intuitive and practical prosthetic control in real-world scenarios.