Kinematic and Dynamic Analysis of the Human Hand’s Articulation for Wearable Soft-Robotic Device Applications

Robot-assisted therapy, particularly hand exoskeletons, has emerged as a promising approach to address hand function limitations caused by neurological diseases that can significantly impact mobility, balance, and posture, leading to physical, psychological, and societal challenges. Traditional rigid-body robots, while helpful, have limitations in safety and dexterity, spurring research into soft robotics in neurorehabilitation. The research presented in this manuscript focuses on the advancement of a Soft Robotic Glove prototype developed for neurorehabilitation, integrated into the NeuroSuitUp Body-Machine Interface. This glove, composed of five PneuNet pneumatic actuators and a multi-sensor system, is designed to facilitate natural hand movements. To optimize the glove's functionality, kinematic and dynamic analyses of the human hand was conducted. Specifically, a kinematic model of the hand, with 19 links representing human bones (phalanges) and 24 joints connecting them, was developed indicating the 24 degrees of freedom of the human hand. By understanding the forces applied to the finger phalanges, the movement of the entire finger can be predicted. This knowledge aids in designing personalized exoskeletal hand devices tailored to individual patient needs. Further research aims to combine this model with a dynamic model of the actuators and investigate the device's effect on hand performance through computer simulations.