Capacitive Sensing for Natural Environment Biomechanics Monitoring

Abstract

Inexpensive wearable sensors could transform how we monitor patient movement outside of the laboratory and help personalize the treatment of mobility impairments[1]. To meet these expectations, wearable sensors must be benchmarked against clinical standards, provide reliable data over extended periods of time, be robust to placement errors by non-experts, and offer tangible translational potential. Inertial sensing is one of the only wearable technologies that have been comprehensively characterized and benchmarked against gold-standard biomechanical measurements, but it remains sensitive to both drift and placement error[2–4] and does not capture muscle activity, which is relevant to both mobility impairments and the development of assistive wearables. Here we investigate capacitive sensing[5] as a muscle-activity monitoring technology, finding for the first time that it can accurately track changes in muscle bulging and fiber length with the fidelity of laboratory tools, in natural environments, over long durations, on multiple body parts, and across people of varying compositions. We also demonstrate translational potential in two clinical applications and show that capacitive sensing complements inertial sensing better than electromyography in multimodal wearable-sensing systems, achieving state-of-the-art accuracy for wearable motion tracking. Our results indicate that capacitive sensing wearables could be used synergistically with other emerging wearable technologies to provide real-time feedback and make rehabilitation monitoring outside of laboratory environments more feasible[6]. We expect this foundational study of capacitive sensing for natural environment biomechanics monitoring—combining wearable sensor design, human experiments, biomechanical modeling, multimodal data fusion, magnetic resonance imaging, and clinical research—to be applicable to a wide range of mobility-related pathologies and emerging human-in-the-loop assistive devices[7–9].