IMU sensors beneath walking surface for ground reaction force prediction in gait

Abstract

Objective: Utilization of inertial measurement units (IMU) data for ground reaction force (GRF) prediction has been widely studied and documented when these sensors attach to the body segments. However, it was inconvenient and required people's cooperation. A novel approach of the current study was setting IMU sensors mounted underneath the walking surface to measure footstep induced structural vibration. We aimed to conduct the force plate to validate the prediction accuracy of this approach. Methods: Fifteen hundred steps were recorded from five individuals. Twentyfour measured features from four IMU sensors were treated as inputs to the long short-term memory model for multidimensional GRF predictions. The GRF data from the force plate were considered as the ground truth for comparisons. The accuracy performance was determined by the normalized root mean square error (NRMSE) method. Results: The averaged NRMSE was 6.05%, 3.93%, and 4.37% for Fx, Fy, and Fz, respectively. Conclusion: The accuracy was comparable with IMU sensors attached to the body, particularly in the vertical direction. The current study demonstrated the feasibility of this approach and successfully predicted ground reaction force with high accuracy. Significance: The validation of IMU sensors mounted underneath the walking surface for GRF prediction provides an alternative method for biometrics in gait.

Multiple Inertial Measurement Unit Combination and Location for Center of Pressure Prediction in Gait

“…However, for the other directions, it has been reported that the medial/lateral GRF could result in substantial variation (John et al, 2012) or overestimation using the IMU approach (Ancillao et al, 2018;Wu et al, 2020). Indeed, higher error rates of GRF prediction in the AP and ML directions were observed by using IMU data when sensors are located beneath the walking surface (Wu et al, 2020). In the current study, the greater deviation of COP prediction was also observed in the ML direction compared to the AP direction.…”

“…IMU data have been widely employed to predict GRF and show robust performance in the vertical direction (Charry et al, 2013;Guo et al, 2017;Shahabpoor and Pavic, 2018). However, for the other directions, it has been reported that the medial/lateral GRF could result in substantial variation (John et al, 2012) or overestimation using the IMU approach (Ancillao et al, 2018;Wu et al, 2020). Indeed, higher error rates of GRF prediction in the AP and ML directions were observed by using IMU data when sensors are located beneath the walking surface (Wu et al, 2020).…”

Real-Time Vertical Ground Reaction Force Estimation in a Unified Simulation Framework Using Inertial Measurement Unit Sensors

“…IMUs have recently become even more reliable as several methods to estimate GRFs using IMUs have been developed [9,10,[18][19][20][21][22]. A recent study analyzed the feasibility of using an IMU mounted underneath the walking surface and measured comparable accuracy to IMUs attached to the body [18]. One argument that is used against IMUs is the loss of accuracy due to drift in highly dynamic motions.…”

Remote Identity Verification Using Gait Analysis and Face Recognition

“…From a biomechanical point of view, ground reaction forces can be explained by Newton's third law-for every action, there is an equal and opposite reaction of the human foot pressure, which is a way of describing human gait [26]. State-of-the-art studies find that the ground reaction addresses the evaluation of muscle forces, joint torques, and stiffness of damping associated with leg-surface contact [27]. Specifically, the ground reaction force (GRF) measurement is noninvasive and easy to implement.…”