Session: 07-10-02: Medical Robotics, Rehabilitation, and Surgery II

Paper Number: 166983

Design and Implementation of a Feedback Controller for a Bio-Inspired Hand Exoskeleton 

This project presents an innovative approach to the design and control of a hand exoskeleton for post-stroke rehabilitation. With approximately 795,000 stroke cases occurring annually and over 1.6 million people worldwide living with stroke-related disabilities, there is a critical need for effective rehabilitation technologies. Stroke survivors often experience limited mobility in their hands, making it difficult to perform everyday tasks. Traditional rehabilitation methods, such as physical therapy, require continuous supervision and extended treatment periods, which may not always be accessible or affordable. As a result, assistive devices like hand exoskeletons have emerged as promising solutions to enhance rehabilitation by providing controlled assistance and resistance during hand movements. In the early stages of rehabilitation, patients may lack the ability to move their hands independently, requiring passive control systems in hand exoskeletons to assist with movement and prevent muscle atrophy. In later stages, as patients regain partial muscle function, they may still require external support. The exoskeleton can then provide resistance, helping to strengthen muscles and improve coordination.

This study focuses on developing a feedback-controlled hand exoskeleton that integrates a linear servo actuator with enhanced capabilities to address these rehabilitation needs. The base mechanical design is adapted from a synergy-based mechanism, which enables the movement of three groups of five fingers using only two actuators. These two synergies, identified in literature based on hand anatomy, ensure natural and efficient hand motion. Some modifications were made to the mechanical design to accommodate the new actuator installation and improve overall performance. The updated design includes an actuator casing, a refined mechanism that preserves the synergy-based movement, and an improved strap system for securely attaching the exoskeleton to the patient’s hand. All mechanical components are 3D-printed using PLA material, making the device lightweight, cost-effective, and customizable. The new actuator, IR MightyZap 12Lf-17PT-53, features a maximum load capacity of 34N, a 53 mm stroke length, a maximum speed of 84 mm/s, and an operating voltage range of 7 to 12V. These improvements potentially enhance the exoskeleton’s efficiency by 2.5 times compared to previous models. The actuator is controlled by an Arduino microcontroller using TTL communication, with input data provided by controller gloves equipped with potentiometers to record finger angles. Additionally, a proportional-derivative (PD) controller is implemented to accurately regulate force, position, and current feedback in response to finger movements. The actuator's reaction time is approximately 0.3 sec to initiate movement and 0.7 sec to reach full extension. The entire system is controlled via Hiwonder wireless gloves, which transmit potentiometer signals through Bluetooth to the Arduino microcontroller, enabling real-time data processing and precise actuator control. Future developments will focus on optimizing control algorithms, enhancing comfort and adaptability for different hand sizes, and conducting user trials to validate its effectiveness in real-world rehabilitation settings.

Presenting Author: Mojtaba Sharifi San Jose State University

Presenting Author Biography: Mojtaba Sharifi has been an Assistant Professor at the Department of Mechanical Engineering, San Jose State University, San Jose, California, USA, since January 2022. He leads research projects on the design, control, and autonomy of assistive and rehabilitation robotics including lower-limb and upper-limb exoskeletons for safe, compliant, and intelligent interaction with humans.
Prior to this, he was a Postdoctoral Research Fellow working on autonomous control of physical human-robot interaction (pHRI), medical robotics, haptics, collaborative robotics, tele-robotics, and assistive technology at the University of Alberta, Canada. He was with the Department of Electrical and Computer Engineering and the Department of Medicine.

Authors:

Rui Takita San Jose State University
Mojtaba Sharifi San Jose State University