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Automated extraction and validation of children’s gait parameters with the Kinect
BACKGROUND: Gait analysis for therapy regimen prescription and monitoring requires patients to physically access clinics with specialized equipment. The timely availability of such infrastructure at the right frequency is especially important for small children. Besides being very costly, this is a...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4667433/ https://www.ncbi.nlm.nih.gov/pubmed/26626555 http://dx.doi.org/10.1186/s12938-015-0102-9 |
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author | Motiian, Saeid Pergami, Paola Guffey, Keegan Mancinelli, Corrie A Doretto, Gianfranco |
author_facet | Motiian, Saeid Pergami, Paola Guffey, Keegan Mancinelli, Corrie A Doretto, Gianfranco |
author_sort | Motiian, Saeid |
collection | PubMed |
description | BACKGROUND: Gait analysis for therapy regimen prescription and monitoring requires patients to physically access clinics with specialized equipment. The timely availability of such infrastructure at the right frequency is especially important for small children. Besides being very costly, this is a challenge for many children living in rural areas. This is why this work develops a low-cost, portable, and automated approach for in-home gait analysis, based on the Microsoft Kinect. METHODS: A robust and efficient method for extracting gait parameters is introduced, which copes with the high variability of noisy Kinect skeleton tracking data experienced across the population of young children. This is achieved by temporally segmenting the data with an approach based on coupling a probabilistic matching of stride template models, learned offline, with the estimation of their global and local temporal scaling. A preliminary study conducted on healthy children between 2 and 4 years of age is performed to analyze the accuracy, precision, repeatability, and concurrent validity of the proposed method against the GAITRite when measuring several spatial and temporal children’s gait parameters. RESULTS: The method has excellent accuracy and good precision, with segmenting temporal sequences of body joint locations into stride and step cycles. Also, the spatial and temporal gait parameters, estimated automatically, exhibit good concurrent validity with those provided by the GAITRite, as well as very good repeatability. In particular, on a range of nine gait parameters, the relative and absolute agreements were found to be good and excellent, and the overall agreements were found to be good and moderate. CONCLUSION: This work enables and validates the automated use of the Kinect for children’s gait analysis in healthy subjects. In particular, the approach makes a step forward towards developing a low-cost, portable, parent-operated in-home tool for clinicians assisting young children. |
format | Online Article Text |
id | pubmed-4667433 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-46674332015-12-03 Automated extraction and validation of children’s gait parameters with the Kinect Motiian, Saeid Pergami, Paola Guffey, Keegan Mancinelli, Corrie A Doretto, Gianfranco Biomed Eng Online Research BACKGROUND: Gait analysis for therapy regimen prescription and monitoring requires patients to physically access clinics with specialized equipment. The timely availability of such infrastructure at the right frequency is especially important for small children. Besides being very costly, this is a challenge for many children living in rural areas. This is why this work develops a low-cost, portable, and automated approach for in-home gait analysis, based on the Microsoft Kinect. METHODS: A robust and efficient method for extracting gait parameters is introduced, which copes with the high variability of noisy Kinect skeleton tracking data experienced across the population of young children. This is achieved by temporally segmenting the data with an approach based on coupling a probabilistic matching of stride template models, learned offline, with the estimation of their global and local temporal scaling. A preliminary study conducted on healthy children between 2 and 4 years of age is performed to analyze the accuracy, precision, repeatability, and concurrent validity of the proposed method against the GAITRite when measuring several spatial and temporal children’s gait parameters. RESULTS: The method has excellent accuracy and good precision, with segmenting temporal sequences of body joint locations into stride and step cycles. Also, the spatial and temporal gait parameters, estimated automatically, exhibit good concurrent validity with those provided by the GAITRite, as well as very good repeatability. In particular, on a range of nine gait parameters, the relative and absolute agreements were found to be good and excellent, and the overall agreements were found to be good and moderate. CONCLUSION: This work enables and validates the automated use of the Kinect for children’s gait analysis in healthy subjects. In particular, the approach makes a step forward towards developing a low-cost, portable, parent-operated in-home tool for clinicians assisting young children. BioMed Central 2015-12-02 /pmc/articles/PMC4667433/ /pubmed/26626555 http://dx.doi.org/10.1186/s12938-015-0102-9 Text en © Motiian et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Motiian, Saeid Pergami, Paola Guffey, Keegan Mancinelli, Corrie A Doretto, Gianfranco Automated extraction and validation of children’s gait parameters with the Kinect |
title | Automated extraction and validation of children’s gait parameters with the Kinect |
title_full | Automated extraction and validation of children’s gait parameters with the Kinect |
title_fullStr | Automated extraction and validation of children’s gait parameters with the Kinect |
title_full_unstemmed | Automated extraction and validation of children’s gait parameters with the Kinect |
title_short | Automated extraction and validation of children’s gait parameters with the Kinect |
title_sort | automated extraction and validation of children’s gait parameters with the kinect |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4667433/ https://www.ncbi.nlm.nih.gov/pubmed/26626555 http://dx.doi.org/10.1186/s12938-015-0102-9 |
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