Parametric and Noise Effects on Magnetic Sensing System for Monitoring Human-Joint Motion of Lower Extremity in Sagittal Plane

Abstract

This article presents a three-degree-of-freedom (3-DOF) magnetic sensor, referred to here as a pantographic exoskeleton (PGE) sensor, for monitoring in real time the internal human-joint motion in the sagittal plane. With two sets of embedded magnetic sensors and a permanent magnet, the PGE wearable on a healthy leg or lower extremity exoskeleton (LEE) independently measures the 2-DOF translations and the joint angle. Two sensor estimation methods, which are the model-based and the artificial neural network (ANN), are experimentally analyzed in the presence of measurement noise. As an illustration, the PGE sensors are evaluated for sit-to-stand (STS) exercises, where the real-time measurements are verified by comparing with the joint angles determined by a commercial VICON motion capture system, and the translational deviations measured on a 4-DOF platform manipulated to follow a specified internal motion trajectory of an ankle joint during STS. With the ANNs appropriately trained to account for measurement noise, the PGE sensors can track the joint angles while measuring the internal motions of both legs with or without the LEE demonstrating that the PGE sensor has the potential to serve as an indicator of stroke rehabilitation where patients lack force perception and suffer an increased risk of falls due to the weak affected leg.