CPS- Synergy- Sensor Network-Based Lower-Limb Prosthetic Optimization and Control

Objective: A powered prosthesis is one of typical cyber-physical systems (CPS) with a human-in-the-loop. The human and prosthesis interaction is highly complicated; although the human user could learn to manipulate the prosthesis, increased effort from the user would be required. The prosthesis requires tuning to minimize the user’s energy expenditure such that the user can use of and interact with the prosthesis effortlessly and with comfort. Moreover, a smooth cooperation between the amputee user and the prosthesis is needed in order to adapt to altered situations and environments. If the prosthesis can ‘intelligently’ understand the user’s volition and subsequently provide adaptive support to the user, the user will use and interact with the prosthesis more comfortably with less effort owing to the reduced effort and load for the prosthesis manipulation and control. This brings a unique CPS challenge on the intelligent sensor technology to enable a robotic sense of the user’s volition. This project will develop CPS technology for the prosthesis optimization to minimize the user’s energy expenditure and for extending the capacity of prosthesis to adapt to dynamic situations and environments.

Impact: More than one million people are living with lower-limb amputation in the United States. The prosthesis optimization as well as the user’s control of prosthesis will promote a natural gait and minimize an amputee’s energy expenditure in prosthetics use. An optimized prosthesis with user control capability will increase equal force distribution and decrease the risk of damage to the intact limb from the musculoskeletal imbalance or pathologies. Maintenance of health in these areas is essential for the amputee’s quality of life and well-being.

Project Preliminary Results: We have conducted hardware and software design, algorithm development and experimental studies for achieving the goal, i.e., to develop a wearable body area sensor network system and computational algorithms for real-time measurement of the user’s physical load and mental effort to support personalized prosthesis optimization for the goal of maximally reducing the user’s energy expenditure during level walking. We have completed the following projects: (1) A Wi-Fi-based ‘CyberSens’ device to support wireless, high-speed, and real-time human gait analysis; (2) In-shoe sensor using piezoelectric for walking-balance evaluation; (3) Multi-channel EMG observation during normal gait and loaded gait from subjects with normal gait evaluation; (4) Muscle activity while operating active prosthetic knee for non-amputee subjects; (5) Active prosthetic limb calibration using the muscle activity from residual limb and the sound leg of amputee subjects; (6) Surface EMG and IMU signals processing and modeling the energy expenditure; and (7) Modeling balanced walking using in-sole sensors.