Kinematic and Dynamic Analysis of Lower Limb Movement: Towards the Design of a Wearable Rehabilitation Assistant Device

This study outlines a comprehensive approach to the kinematic and dynamic analysis of lower limb movement, with the express purpose of designing an efficient wearable rehabilitation assistant device for the lower body. The approach begins by conducting a kinematic analysis of the lower limbs, presenting the degrees of freedom and each joint’s range of motion. A kinematic model is designed by deciding on a kinematic chain configuration and calculating the Denavit Hartenberg (DH) parameters. Next, differential kinematic analysis is employed to calculate the velocity of the limbs, generated by the corresponding muscle groups during different types of movements. This can provide significant insights into the design of a device that can accurately track and assist these movements. Furthermore, a dynamic analysis is performed to calculate joint moments and forces. This analysis provides insights into the forces that the joints experience during movement. When combined with electromyography (EMG) data, it allows for a more holistic description of muscle activity and a more accurate estimation of individual muscle forces and joint loads. The research also lays out a plan for the wearable device's implementation. Based on OpenSenseRT [1] an open-source software and hardware project, that utilized the OpenSim [2] API, real-time inverse kinematics of a movement can be calculated using data from inertial measurement units (IMUs). This data is then used to compute the error in a person's movement during lower limb rehabilitation exercises. This error, along with the error derived from real-time dynamic analysis and EMG data, can be integrated to improve the control accuracy of the wearable device.

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Publication Details

Journal
Global Clinical Engineering Journal
Published
2024-12-31
DOI
https://doi.org/10.31354/globalce.v6isi6.266
Primary Topic
Muscle activation and electromyography studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Kinematic and Dynamic Analysis of Lower Limb Movement: Towards the Design of a Wearable Rehabilitation Assistant Device

Konstantinos Mitsopoulos, Kostas Nizamis, Alkinoos Athanasiou, Panagiotis D. Bamidis et al.
Global Clinical Engineering Journal
Muscle activation and electromyography studies
article

Kinematic and Dynamic Analysis of Lower Limb Movement: Towards the Design of a Wearable Rehabilitation Assistant Device

Konstantinos Mitsopoulos, Kostas Nizamis, Alkinoos Athanasiou, Panagiotis D. Bamidis, Filippos Margaritis
article en

Abstract

This study outlines a comprehensive approach to the kinematic and dynamic analysis of lower limb movement, with the express purpose of designing an efficient wearable rehabilitation assistant device for the lower body. The approach begins by conducting a kinematic analysis of the lower limbs, presenting the degrees of freedom and each joint’s range of motion. A kinematic model is designed by deciding on a kinematic chain configuration and calculating the Denavit Hartenberg (DH) parameters. Next, differential kinematic analysis is employed to calculate the velocity of the limbs, generated by the corresponding muscle groups during different types of movements. This can provide significant insights into the design of a device that can accurately track and assist these movements. Furthermore, a dynamic analysis is performed to calculate joint moments and forces. This analysis provides insights into the forces that the joints experience during movement. When combined with electromyography (EMG) data, it allows for a more holistic description of muscle activity and a more accurate estimation of individual muscle forces and joint loads. The research also lays out a plan for the wearable device's implementation. Based on OpenSenseRT [1] an open-source software and hardware project, that utilized the OpenSim [2] API, real-time inverse kinematics of a movement can be calculated using data from inertial measurement units (IMUs). This data is then used to compute the error in a person's movement during lower limb rehabilitation exercises. This error, along with the error derived from real-time dynamic analysis and EMG data, can be integrated to improve the control accuracy of the wearable device.

Global Clinical Engineering JournalVol. 6(SI6)
Aristotle University of Thessaloniki (GR), University of Twente (NL)
University of Twente, Aristotle University of Thessaloniki, Hellenic Foundation for Research and Innovation
Peace, Justice and strong institutions
Openalex Percentile: Top 77%
Muscle activation and electromyography studies
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