Omer T. Inan, PhD (Georgia Institute of Technology)
Young-Hui Chang, PhD (Georgia Institute of Technology)
Geza Kogler, PhD, CPO (Georgia Institute of Technology)
Gregory Sawicki, PhD (Georgia Institute of Technology)
Aaron Young, PhD (Georgia Institute of Technology)
Joint Load Estimation Using Multimodal Wearable Sensing
Mechanical loading plays a key role in the pathogenesis and treatment of many forms of joint dysfunction. Proper manipulation of joint load is critical for accelerating rehabilitation from injury and improving assistive strategies for functional impairments. Tools to assess these loading conditions (e.g., joint torques, internal reaction forces, brace mechanics) are almost exclusively the domain of clinical and scientific research, and few techniques exist that are feasible for use in wearable, out-of-clinic settings. The focus of this work is to explore the use of wearable sensing approaches—in particular, instrumented orthoses and joint acoustical emissions—to estimate the loading conditions that affect joint function in the lower limbs. The latter, which involves detecting small skin-surface vibrations produced by joint articulation, has recently been demonstrated as a viable means of assessing the health status (e.g., injured vs. intact) of and mechanical stress borne by the knee. Successful completion of the proposed work will demonstrate that, by coupling joint acoustical information with that of other wearable sensors, joint loads can be estimated using accessible, noninvasive techniques, paving the way for longitudinal, at-home monitoring of joint health and function.