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Analysis of Interrelationships among Voluntary and Prosthetic Leg Joint Parameters Using Cyclograms

The walking mechanism of a prosthetic leg user is a tightly coordinated movement of several joints and limb segments. The interaction among the voluntary and mechanical joints and segments requires particular biomechanical insight. This study aims to analyze the inter-relationship between amputees&#...

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Autores principales: Jasni, Farahiyah, Hamzaid, Nur Azah, Mohd Syah, Nor Elleeiana, Chung, Tze Y., Abu Osman, Noor Azuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5403952/
https://www.ncbi.nlm.nih.gov/pubmed/28487630
http://dx.doi.org/10.3389/fnins.2017.00230
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author Jasni, Farahiyah
Hamzaid, Nur Azah
Mohd Syah, Nor Elleeiana
Chung, Tze Y.
Abu Osman, Noor Azuan
author_facet Jasni, Farahiyah
Hamzaid, Nur Azah
Mohd Syah, Nor Elleeiana
Chung, Tze Y.
Abu Osman, Noor Azuan
author_sort Jasni, Farahiyah
collection PubMed
description The walking mechanism of a prosthetic leg user is a tightly coordinated movement of several joints and limb segments. The interaction among the voluntary and mechanical joints and segments requires particular biomechanical insight. This study aims to analyze the inter-relationship between amputees' voluntary and mechanical coupled leg joints variables using cyclograms. From this analysis, the critical gait parameters in each gait phase were determined and analyzed if they contribute to a better powered prosthetic knee control design. To develop the cyclogram model, 20 healthy able-bodied subjects and 25 prosthesis and orthosis users (10 transtibial amputees, 5 transfemoral amputees, and 10 different pathological profiles of orthosis users) walked at their comfortable speed in a 3D motion analysis lab setting. The gait parameters (i.e., angle, moment and power for the ankle, knee and hip joints) were coupled to form 36 cyclograms relationship. The model was validated by quantifying the gait disparities of all the pathological walking by analyzing each cyclograms pairs using feed-forward neural network with backpropagation. Subsequently, the cyclogram pairs that contributed to the highest gait disparity of each gait phase were manipulated by replacing it with normal values and re-analyzed. The manipulated cyclograms relationship that showed highest improvement in terms of gait disparity calculation suggested that they are the most dominant parameters in powered-knee control. In case of transfemoral amputee walking, it was identified using this approach that at each gait sub-phase, the knee variables most responsible for closest to normal walking were: knee power during loading response and mid-stance, knee moment and knee angle during terminal stance phase, knee angle and knee power during pre-swing, knee angle at initial swing, and knee power at terminal swing. No variable was dominant during mid-swing phase implying natural pendulum effect of the lower limb between the initial and terminal swing phases. The outcome of this cyclogram adoption approach proposed an insight into the method of determining the causal effect of manipulating a particular joint's mechanical properties toward the joint behavior in an amputee's gait by determining the curve closeness, C, of the modified cyclogram curve to the normal conventional curve, to enable quantitative judgment of the effect of changing a particular parameter in the prosthetic leg gait.
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spelling pubmed-54039522017-05-09 Analysis of Interrelationships among Voluntary and Prosthetic Leg Joint Parameters Using Cyclograms Jasni, Farahiyah Hamzaid, Nur Azah Mohd Syah, Nor Elleeiana Chung, Tze Y. Abu Osman, Noor Azuan Front Neurosci Neuroscience The walking mechanism of a prosthetic leg user is a tightly coordinated movement of several joints and limb segments. The interaction among the voluntary and mechanical joints and segments requires particular biomechanical insight. This study aims to analyze the inter-relationship between amputees' voluntary and mechanical coupled leg joints variables using cyclograms. From this analysis, the critical gait parameters in each gait phase were determined and analyzed if they contribute to a better powered prosthetic knee control design. To develop the cyclogram model, 20 healthy able-bodied subjects and 25 prosthesis and orthosis users (10 transtibial amputees, 5 transfemoral amputees, and 10 different pathological profiles of orthosis users) walked at their comfortable speed in a 3D motion analysis lab setting. The gait parameters (i.e., angle, moment and power for the ankle, knee and hip joints) were coupled to form 36 cyclograms relationship. The model was validated by quantifying the gait disparities of all the pathological walking by analyzing each cyclograms pairs using feed-forward neural network with backpropagation. Subsequently, the cyclogram pairs that contributed to the highest gait disparity of each gait phase were manipulated by replacing it with normal values and re-analyzed. The manipulated cyclograms relationship that showed highest improvement in terms of gait disparity calculation suggested that they are the most dominant parameters in powered-knee control. In case of transfemoral amputee walking, it was identified using this approach that at each gait sub-phase, the knee variables most responsible for closest to normal walking were: knee power during loading response and mid-stance, knee moment and knee angle during terminal stance phase, knee angle and knee power during pre-swing, knee angle at initial swing, and knee power at terminal swing. No variable was dominant during mid-swing phase implying natural pendulum effect of the lower limb between the initial and terminal swing phases. The outcome of this cyclogram adoption approach proposed an insight into the method of determining the causal effect of manipulating a particular joint's mechanical properties toward the joint behavior in an amputee's gait by determining the curve closeness, C, of the modified cyclogram curve to the normal conventional curve, to enable quantitative judgment of the effect of changing a particular parameter in the prosthetic leg gait. Frontiers Media S.A. 2017-04-25 /pmc/articles/PMC5403952/ /pubmed/28487630 http://dx.doi.org/10.3389/fnins.2017.00230 Text en Copyright © 2017 Jasni, Hamzaid, Mohd Syah, Chung and Abu Osman. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Jasni, Farahiyah
Hamzaid, Nur Azah
Mohd Syah, Nor Elleeiana
Chung, Tze Y.
Abu Osman, Noor Azuan
Analysis of Interrelationships among Voluntary and Prosthetic Leg Joint Parameters Using Cyclograms
title Analysis of Interrelationships among Voluntary and Prosthetic Leg Joint Parameters Using Cyclograms
title_full Analysis of Interrelationships among Voluntary and Prosthetic Leg Joint Parameters Using Cyclograms
title_fullStr Analysis of Interrelationships among Voluntary and Prosthetic Leg Joint Parameters Using Cyclograms
title_full_unstemmed Analysis of Interrelationships among Voluntary and Prosthetic Leg Joint Parameters Using Cyclograms
title_short Analysis of Interrelationships among Voluntary and Prosthetic Leg Joint Parameters Using Cyclograms
title_sort analysis of interrelationships among voluntary and prosthetic leg joint parameters using cyclograms
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5403952/
https://www.ncbi.nlm.nih.gov/pubmed/28487630
http://dx.doi.org/10.3389/fnins.2017.00230
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