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Biomechanical Signals of Varied Modality and Location Contribute Differently to Recognition of Transient Locomotion

Intent recognition in lower-limb assistive devices typically relies on neuromechanical sensing of an affected limb acquired through embedded device sensors. It remains unknown whether signals from more widespread sources such as the contralateral leg and torso positively influence intent recognition...

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Autores principales: Kazemimoghadam, Mahdieh, Fey, Nicholas P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7570574/
https://www.ncbi.nlm.nih.gov/pubmed/32967072
http://dx.doi.org/10.3390/s20185390
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author Kazemimoghadam, Mahdieh
Fey, Nicholas P.
author_facet Kazemimoghadam, Mahdieh
Fey, Nicholas P.
author_sort Kazemimoghadam, Mahdieh
collection PubMed
description Intent recognition in lower-limb assistive devices typically relies on neuromechanical sensing of an affected limb acquired through embedded device sensors. It remains unknown whether signals from more widespread sources such as the contralateral leg and torso positively influence intent recognition, and how specific locomotor tasks that place high demands on the neuromuscular system, such as changes of direction, contribute to intent recognition. In this study, we evaluated the performances of signals from varying mechanical modalities (accelerographic, gyroscopic, and joint angles) and locations (the trailing leg, leading leg and torso) during straight walking, changes of direction (cuts), and cuts to stair ascent with varying task anticipation. Biomechanical information from the torso demonstrated poor performance across all conditions. Unilateral (the trailing or leading leg) joint angle data provided the highest accuracy. Surprisingly, neither the fusion of unilateral and torso data nor the combination of multiple signal modalities improved recognition. For these fused modality data, similar trends but with diminished accuracy rates were reported during unanticipated conditions. Finally, for datasets that achieved a relatively accurate (≥90%) recognition of unanticipated tasks, these levels of recognition were achieved after the mid-swing of the trailing/transitioning leg, prior to a subsequent heel strike. These findings suggest that mechanical sensing of the legs and torso for the recognition of straight-line and transient locomotion can be implemented in a relatively flexible manner (i.e., signal modality, and from the leading or trailing legs) and, importantly, suggest that more widespread sensing is not always optimal.
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spelling pubmed-75705742020-10-28 Biomechanical Signals of Varied Modality and Location Contribute Differently to Recognition of Transient Locomotion Kazemimoghadam, Mahdieh Fey, Nicholas P. Sensors (Basel) Article Intent recognition in lower-limb assistive devices typically relies on neuromechanical sensing of an affected limb acquired through embedded device sensors. It remains unknown whether signals from more widespread sources such as the contralateral leg and torso positively influence intent recognition, and how specific locomotor tasks that place high demands on the neuromuscular system, such as changes of direction, contribute to intent recognition. In this study, we evaluated the performances of signals from varying mechanical modalities (accelerographic, gyroscopic, and joint angles) and locations (the trailing leg, leading leg and torso) during straight walking, changes of direction (cuts), and cuts to stair ascent with varying task anticipation. Biomechanical information from the torso demonstrated poor performance across all conditions. Unilateral (the trailing or leading leg) joint angle data provided the highest accuracy. Surprisingly, neither the fusion of unilateral and torso data nor the combination of multiple signal modalities improved recognition. For these fused modality data, similar trends but with diminished accuracy rates were reported during unanticipated conditions. Finally, for datasets that achieved a relatively accurate (≥90%) recognition of unanticipated tasks, these levels of recognition were achieved after the mid-swing of the trailing/transitioning leg, prior to a subsequent heel strike. These findings suggest that mechanical sensing of the legs and torso for the recognition of straight-line and transient locomotion can be implemented in a relatively flexible manner (i.e., signal modality, and from the leading or trailing legs) and, importantly, suggest that more widespread sensing is not always optimal. MDPI 2020-09-21 /pmc/articles/PMC7570574/ /pubmed/32967072 http://dx.doi.org/10.3390/s20185390 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kazemimoghadam, Mahdieh
Fey, Nicholas P.
Biomechanical Signals of Varied Modality and Location Contribute Differently to Recognition of Transient Locomotion
title Biomechanical Signals of Varied Modality and Location Contribute Differently to Recognition of Transient Locomotion
title_full Biomechanical Signals of Varied Modality and Location Contribute Differently to Recognition of Transient Locomotion
title_fullStr Biomechanical Signals of Varied Modality and Location Contribute Differently to Recognition of Transient Locomotion
title_full_unstemmed Biomechanical Signals of Varied Modality and Location Contribute Differently to Recognition of Transient Locomotion
title_short Biomechanical Signals of Varied Modality and Location Contribute Differently to Recognition of Transient Locomotion
title_sort biomechanical signals of varied modality and location contribute differently to recognition of transient locomotion
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7570574/
https://www.ncbi.nlm.nih.gov/pubmed/32967072
http://dx.doi.org/10.3390/s20185390
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