Nearly all Americans participate in physical rehabilitation therapy at some point in their lifespan. Physical therapy can be highly effective in alleviating pain and restoring function, however only a third of physical therapy patients fully adhere to their plans of care. Future gains in improving the effectiveness of physical therapy will require patient-specific monitoring of the accuracy and frequency of therapeutic exercises. However, low-cost ways to accurately monitor therapeutic exercise do not currently exist. The goal of this project is to use cutting-edge advances in nano-composite sensor, artificial intelligence, and communication technologies to develop an affordable, wearable, sensing system for monitoring physical rehabilitative therapy exercises for patients who have recently had a total knee replacement (TKR). These key characteristics will be used to provide instant biofeedback to patients and clinicians, inside or outside of the traditional physical therapy clinic. The new wearable sensing system will be used to monitor therapeutic exercise on an individual and population scale, facilitating the creation of a massive and previously unattainable database of therapeutic exercise characteristics. Further, results from this project will have application in any context where real-life characterization of human movement is important, for example, worksite safety or athletic performance. This project will involve numerous graduate and undergraduate research assistants pursuing careers in engineering or science, as well as undergraduate research assistants pursuing careers in medicine or physical therapy. It is also anticipated that the resulting wearable sensing system will be used as a teaching tool in physical therapy curricula, an application that will be evaluated in this project.
The goal of this project is to engineer and evaluate a wearable nano-biosensing system that leverages recent development by the investigators in the area of skin-like nano-composite sensors, as a new approach to characterize the biomechanics of physical rehabilitation performed by patients during self-guided and clinician controlled physical therapy. The guiding hypotheses to be tested are: 1) Wearable nano-biosensing systems based upon a 3D network of piezoresponsive sensors can be designed with adequate resolution of kinematics to identify and characterize physical rehabilitation exercises; 2)The mechanical characteristics of self-guided physical rehabilitation exercises are fundamentally different from the mechanical characteristics of physical rehabilitation exercises performed under the direct supervision of a clinician and 3) Combining biofeedback with a wearable nano-biosensing system can quantitatively and qualitatively decrease differences between self-guided and clinician-supervised physical rehabilitation. The Research Plan is organized under three objectives related to these hypotheses. The FIRST Objective is to undertake the materials science and engineering research required to create and validate a 3D wearable, nanocomposite biosensing system whose hardware and software components will be encapsulated into a Mobile Environment of Nanosensors for Tracking Out-of-clinic Rehabilitation (MENTOR). The system will be designed to fully capture the kinematics and kinetics of rehabilitation exercises for post total knee replacement (TKR) recovery. High sensitivity, elastomer-based nanocomposite strain sensors will be positioned in a system of 2D sensing membranes whose response can be accurately interpreted in terms of 3D joint kinematics. Smart insoles to capture ground reaction forces (GRF)) will be expanded to include piezoresistive pressure sensing of static forces in order to detect stance during rehabilitation exercises in addition to GRF while walking and running. The SECOND Objective is to measure, validate, and compare lower-extremity biomechanics of clinician-guided outpatient rehabilitation exercises with that of the same patients performing the same exercises in a self-guided setting independent of direct clinician supervision. Biomechanics will be measured using both traditional motion analysis tools and the MENTOR wearable sensing system. The THIRD Objective is to measure and compare the biomechanics of clinician-guided outpatient rehabilitation exercises with that of the same patients performing the same exercises, self-guided, with and without realtime biofeedback when using the MENTOR wearable sensing system. The wearable MENTOR system will be combined with a simple, smartphone-based biofeedback system whose purpose is to assist the patients in correctly performing the rehabilitation exercises at the desired quality (similar biomechanical characteristics) and quantity (e.g., desired number of sets and repetitions). A simple Knee Motion Dashboard will provide the patient and clinician with quantitative sensor information regarding rehabilitation progress.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
