A pilot study on locomotion training via biomechanical models and a wearable haptic feedback system

Abstract

Locomotion is a fundamental human skill. Real-time sensing and feedback is a promising strategy for motion training to reconstruct healthy locomotion patterns lost due to aging or disease, and to prevent injuries. In this paper, we present a pilot study on locomotion training via biomechanical modeling and a wearable haptic feedback system. In addition, a novel simulation framework for motion tracking and analysis is introduced. This unified framework, implemented within the Unity environment, is used to analyze subject's baseline and performance characteristics, and to provide real-time haptic feedback during locomotion. The framework incorporates accurate musculoskeletal models derived from OpenSim, closed-form calculations of muscle routing kinematics and kinematic Jacobian matrices, dynamic performance metrics (i.e., muscular effort), human motion reconstruction via inertial measurement unit (IMU) sensors, and real-time visualization of the motion and its dynamics. A pilot study was conducted in which 6 healthy subjects learned to alter running patterns to lower the knee flexion moment (KFM) through haptic feedback. We targeted three gait parameters (trunk lean, cadence, and foot strike) that previous studies had identified as having an influence on reducing the knee flexion moment and associated with increased risk of running injuries. All subjects were able to adopt altered running patterns requiring simultaneous changes to these kinematic parameters and reduced their KFM to 30-85% of their baseline values. The muscular effort during motion training stayed comparable to subjects' baseline. This study shows that biomechanical modeling, together with real-time sensing and wearable haptic feedback can greatly increase the efficiency of motion training.

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A Wearable Sensor System for Physical Ergonomics Interventions Using Haptic Feedback

“…These systems typically lack real-time feedback and there is still a clear emphasis on capturing data for analysis performed in hindsight, and the feedback is often limited to visual presentations in graphical form on a screen [ 65 , 66 , 67 ]. One exception is a pilot study on locomotion training where real-time haptic feedback was introduced [ 68 ]. Here vibrotactile actuators were used for immediate feedback on cadence and foot-drop angle during running.…”

Wearable Real-Time Haptic Biofeedback Foot Progression Angle Gait Modification to Assess Short-Term Retention and Cognitive Demand

“…For implementing the presented methodology in practice, subjects could be trained with haptic biofeedback to modify the FPA outside of the lab either on a treadmill or during straight line overground walking. In addition to FPA, several recent wearable haptic systems have been proposed for a variety of biomechanics applications [38]- [42], and thus it is feasible that the portable movement retention and cognitive demand findings presented here could potentially be expanded more generally to other movement parameters.…”