Details

Autor(en) / Beteiligte

• Torricelli, Diego
• Cortés, Camilo
• Lete, Nerea
• Bertelsen, Álvaro
• Gonzalez-Vargas, Jose E
• Del-Ama, Antonio J
• Dimbwadyo, Iris
• Moreno, Juan C
• Florez, Julian
• Pons, Jose L

Titel

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

Ist Teil von

• Frontiers in neurorobotics, 2018-04, Vol.12, p.18-18

Ort / Verlag

Switzerland: Frontiers Research Foundation

Erscheinungsjahr

2018

Link zum Volltext

Quelle

EZB Free E-Journals

Beschreibungen/Notizen

• 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.