Passive Elbow Joint Impedance Identification with the use of an Elbow Device

Master Thesis (2023)
Author(s)

K. Papa (TU Delft - Mechanical Engineering)

Contributor(s)

Suzanne Filius – Mentor (TU Delft - Biomechatronics & Human-Machine Control)

J Harlaar – Mentor (TU Delft - Biomechatronics & Human-Machine Control)

G. Radaelli – Graduation committee member (TU Delft - Mechatronic Systems Design)

Faculty
Mechanical Engineering
Copyright
© 2023 Kyriacos Papa
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 Kyriacos Papa
Graduation Date
22-08-2023
Awarding Institution
Delft University of Technology
Programme
['Biomedical Engineering']
Faculty
Mechanical Engineering
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Abstract

Neuromuscular diseases often result in elevated passive joint impedance (PJI), impacting the daily lives of affected individuals. To be able to apply assistive devices that compensate for PJI, it is essential to identify the PJI correctly. This study aims to identify and model the PJI of the elbow joint, to improve the control of force-based controlled active-assistance exoskeleton devices by distinguishing the voluntary from the passive forces. We used an elbow device to measure the PJI in twelve healthy males with the shoulder abducted at a 90˚ angle. The study investigates both static and dynamic conditions, encompassing various contraction velocities (≤ 0.20 rad/s) and shoulder flexion positions (0˚ and ±45˚). The analysis estimates the hysteresis, equilibrium position, and elastic property. Subsequently, based on the average elbow PJI, we developed a regression model, with the statistical analysis revealing no significant differences between the conditions, except for the observed hysteresis under varying velocities. Based on the tested conditions, the findings indicate that a single low-velocity dynamic measurement can serve as the basis for deriving a general elbow PJI regression model.

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