CPS: Synergy: Sensor Network-based Lower-Limb Prosthesis Optimization and Control

Abstract: 

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. Specific Aims and Approaches: (1) Design of 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 will employ multi-channel electromyography (EMG) sensors to measure the user’s muscular activations of multiple body areas associated with walking, multi-channel electroencephalography (EEG) sensors to measure the user’s mental load during the interaction with and use of the prosthesis, and inertia measurement units (IMU) to measure the prosthetic and intact limb movement. Furthermore, a machine learning technology-based automatic prosthesis tuning system will be developed using the body area sensor network readings as the inputs to support in-home tuning and retuning of the prosthesis by users themselves; (2) Development of volitional prosthesis control technology for comfortable and effortless user control of prosthesis for the adaptation to altered situations and environments: volitional prosthesis control will be developed by leveraging the brain-machine interface-based human volition-recognition technology established in the PI’s Lab. to support comfortable and effortless user-control of the prosthesis, in which users can control the prosthesis (parameter intervention) proactively by their ‘thought’ alone. The automatic recognition of the user’s volition with subsequent automatic adjustment of prosthetic control parameters will bring amputee gait closer to normal gait patterns which can help the amputee increase motion functions (e.g. upslope/downslope) and reduce energy expenditure in altered situations and environments. Meanwhile, the recognition of user’s conscious intent with subsequent prosthetic control will provide the user an ownership sense of ‘I am the one in control of prosthetic adaptation’. 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.