Development of Wearable Assistive Robots Using Artificial Muscle for Older Adults

Abstract

Age-related sarcopenia weakens balance in older adults, highlighting the need for effective assistive robots. How-ever, existing assistive technologies often suffer from mechanical, kinematic, and control incompatibilities with the human body. Here, we present a wearable assistive robotic system that integrates muscle-like actuation and control algorithms to directly compensate for impaired muscle force generation at the physiological level. To address mechanical incompatibility, the system employs artificial muscle actuators that replicate the contraction dynamics of human muscles. By mimicking the natural direction of muscle force generation and the anatomical anchor points of muscle attachment, it also resolves kinematic incompatibility. Furthermore, the system uses real-time electromyography (EMG) signals for neuromuscular sensing and implements a muscle-like recruitment and rate coding algorithm to control twisted fiber soft actuators, thereby addressing control incompatibility through human-in-the-loop signal integration. A comprehensive evaluation using the Functional Reach Test (FRT) with ten older adults demonstrated a 16.6% average increase in total ankle joint torque and a statistically significant improvement in forward reach distance (from 66.4 ± 17.4 cm in the OFF condition to 77.2 ± 16.6 cm in the ON condition). These findings highlight the system’s potential to mitigate age-related muscle decline and establish a novel muscle-like actuation–motion–control paradigm for wearable assistive robotics.