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A Subject-Specific Kinematic Model to Predict Human Motion in Exoskeleton-Assisted Gait

2018; Frontiers Media; Volume: 12; Linguagem: Inglês

10.3389/fnbot.2018.00018

1662-5218

Diego Torricelli, Camilo Cortés, Nerea Lete, Álvaro Bertelsen, José González-Vargas, Antonio J. del‐Ama, I. Dimbwadyo, Juan C. Moreno, J. Flórez, José L. Pons,

Stroke Rehabilitation and Recovery

The relative motion between human and exoskeleton is a crucial factor that has remarkable consequences on the efficiency, reliability and safety of human-robot interaction. Unfortunately, its quantitative assessment has been largely overlooked in the literature. Here, we present a methodology that allows predicting the motion of the human joints from the knowledge of the angular motion of the exoskeleton frame. Our method combines a subject-specific skeletal model with a kinematic model of a lower limb exoskeleton (H2, Technaid), imposing specific kinematic constraints between them. To calibrate the model and validate its ability to predict the relative motion in a subject-specific way, we performed experiments on seven healthy subjects during treadmill walking tasks. We demonstrate a prediction accuracy lower than 3.5° globally, and around 1.5° at the hip level, which represent an improvement up to 66% compared to the traditional approach assuming no relative motion between the user and the exoskeleton.