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Design of the Cooperative Actuation in Hybrid Orthoses: A Theoretical Approach Based on Muscle Models.
- Source :
-
Frontiers in neurorobotics [Front Neurorobot] 2019 Jul 31; Vol. 13, pp. 58. Date of Electronic Publication: 2019 Jul 31 (Print Publication: 2019). - Publication Year :
- 2019
-
Abstract
- Hybrid orthoses or rehabilitation exoskeletons have proven to be a powerful tool for subjects with gait disabilities due to their combined use of electromechanical actuation to provide motion and support, and functional electrical stimulation (FES) to contract muscle tissue so as to improve the rehabilitation process. In these devices, each degree of freedom is governed by two actuators. The main issue arises in the design of the two actuation profiles for there to be natural or normative gait motion in which the two actuators are transparent to each other. Hybrid exoskeleton control solutions proposed in the literature have been based on tracking the desired kinematics and applying FES to maintain the desired motion rather than to attain the values expected for physiological movement. This work proposes a muscle-model approach involving inverse dynamics optimization for the design of combined actuation in hybrid orthoses. The FES profile calculated in this way has the neurophysiological meaningfulness for the device to be able to fulfill its rehabilitative purpose. A general scheme is proposed for a hybrid hip-knee-ankle-foot orthosis. The actuation profiles, when muscle tissue is fatigued due to FES actuation are analyzed, and an integrated approach is presented for estimating the actuation profiles so as to overcome muscle peak force reduction during stimulation. The objective is to provide a stimulation profile for each muscle individually that is compatible with the desired kinematics and actuation of the orthosis. The hope is that the results may contribute to the design of subject-specific rehabilitation routines with hybrid exoskeletons, improving the exoskeleton's actuation while maintaining its rehabilitative function.
Details
- Language :
- English
- ISSN :
- 1662-5218
- Volume :
- 13
- Database :
- MEDLINE
- Journal :
- Frontiers in neurorobotics
- Publication Type :
- Academic Journal
- Accession number :
- 31417390
- Full Text :
- https://doi.org/10.3389/fnbot.2019.00058