Smart Crutches: Towards Instrumented Crutches for Rehabilitation and Exoskeletons-Assisted Walking

Abstract

Recording 3D ground reaction forces through instrumented crutches can assist patients undergoing ambulatory rehabilitation as well as help roboticists develop new assistive controllers for their exoskeletons. Current methods to measure the amount of weight a patient exerts on their limbs are either inaccurate, or not feasible outside of ideal laboratory conditions. This paper introduces Smart Crutches, an instrumented crutch system capable of measuring the weight that a patient places on his/her lower extremities and providing vibratory feedback in response to the measured weight. The device was calibrated using a motion capture system and force plates. Linear regression and support vector regression (SVR) were used for calibration, and 10-fold cross-validation was applied to estimate the system's accuracy. Results indicate that machine learning regression methods may lead to improved accuracy, but the choice of the kernel function is critical. Gaussian kernel yielded root-mean-square errors (RSME) of 2.5N or less relative to force plates, while other kernel functions produced more inconsistent and less accurate results. Instrumented crutches may be a valid alternative to force plates for estimating ground reaction forces in crutch gait.