Musculoskeletal impairments are common in the US, many of which result in the need for surgery and/or physical therapy. The total knee replacement (TKR) is one surgical proceedure that has increased in recent years due to a growing number of aging baby boomers and obese individuals. Physical therapy plays a key role in recovering from TKR surgery. Studies have shown that physical rehabilitation is a very successful and cost-effective path to recovery, but is limited by the amount of time that patients can spend with their clinicians. For a better chance of successful rehabilitation, remedial exercises are assigned to be done at the homes of patients. However, clinicians lose total control outside of the clinic and must rely on patient self-reporting to evaluate quality and quantity of at-home exercises. These reports can be inaccurate and be detrimental to recovery time. If clinicians were able to monitor patient exercises outside of the treatment center, patients would be able to enjoy more effective home exercises and faster rehabilitation. This research focuses on developing a sensing system to track patient joint mechanics during home exercise. &nbsp; Elastomer-based nano-composite piezoresponsive sensors appear to be a fitting solution for sensing rehabilitation mechanics. Our research involves developing a wearable nano-biosensing system that leverages a 3D network of the aforementioned sensors, thereby characterizing the biomechanics of patient physical rehabilitation during both clinical and self-guided physical therapy. Development and optimization of these sensors guides the design of the wearable apparatus, including placement of sensors in high-strain areas on or near the patella.&nbsp; Through a mobile app that analyzes the data provided from our system, clinicians and patients will be able to obtain the angle of the knee joint and verify that exercises are done on schedule and correctly. A successful implementation of the sensors would create a new understanding between both self-guided and clinician-controlled physical rehabilitation, and the relationship each has with TKR recovery.&nbsp;&nbsp; &nbsp; The design of the sensing system involved several parallel efforts, such as optimizing the sensors, developing a sensor configuration to accurately capture lower extremity kinematics, and designing a method to attach the sensor array to the subject’s knee. The nanocomposite sensors are made of a mixture of silicone, nickel-coated carbon fibers (NCCF), and nickel nanostrands (NiNS). A detailed optimization process was used to determine a formula to maximize elasticity and sensitivity and to minimize creep and signal drift. A 12-camera motion capture system was used to collect knee kinematic data from both healthy individuals and those recovering from TKR, and to generate a model relating knee joint kinematics to skin strain over the knee. This model informed the design of the sensor configuration. Physical prototyping went through several iterations to arrive at a final design that fulfills system requirements. &nbsp; Initial testing indicates that the new system is capable of accurately measuring knee flexion, which is a key metric used in evaluating TKR recovery. If successful, our system would benefit clinicians in their ability to treat their patients, as well as the patients themselves in their rehabilitation. While our project is specifically aimed at TKR rehabilitation, the sensing system could prove to be transformative in fields that require accurate measurement of any human joint, potentially changing the paradigm for rehabilitation therapy.


Elastomer-Based Nano-Composite Piezoresponsive Sensor System for Aiding Total Knee Replacement Rehabilitation

Division / Sponsors: 
Aerospace, Bioengineering, Applied Mechanics, Design Engineering Division, Advanced Energy Systems, Manufacturing Engineering Division, Noise Control and Acoustics, Nondestructive Evaluation, Diagnosis, and Prognosis (NDPD), Nuclear Engineering Division, Process Industries Division, Fluids Engineering, Heat Transfer, Materials, Microelectromechanical Systems, Safety Engineering and Risk Analysis, Computers & Information in Engineering


Paper Proceedings: https://asmedigitalcollection.asme.org/IMECE/IMECE2020/volume/84478

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