Cargando…

Development and Validation of 2D-LiDAR-Based Gait Analysis Instrument and Algorithm

Acquiring gait parameters from usual walking is important to predict clinical outcomes including life expectancy, risk of fall, and neurocognitive performance in older people. We developed a novel gait analysis tool that is small, less-intrusive and is based on two-dimensional light detection and ra...

Descripción completa

Detalles Bibliográficos
Autores principales: Yoon, Seongjun, Jung, Hee-Won, Jung, Heeyoune, Kim, Keewon, Hong, Suk-Koo, Roh, Hyunchul, Oh, Byung-Mo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7826665/
https://www.ncbi.nlm.nih.gov/pubmed/33430161
http://dx.doi.org/10.3390/s21020414
_version_ 1783640574787584000
author Yoon, Seongjun
Jung, Hee-Won
Jung, Heeyoune
Kim, Keewon
Hong, Suk-Koo
Roh, Hyunchul
Oh, Byung-Mo
author_facet Yoon, Seongjun
Jung, Hee-Won
Jung, Heeyoune
Kim, Keewon
Hong, Suk-Koo
Roh, Hyunchul
Oh, Byung-Mo
author_sort Yoon, Seongjun
collection PubMed
description Acquiring gait parameters from usual walking is important to predict clinical outcomes including life expectancy, risk of fall, and neurocognitive performance in older people. We developed a novel gait analysis tool that is small, less-intrusive and is based on two-dimensional light detection and ranging (2D-LiDAR) technology. Using an object-tracking algorithm, we conducted a validation study of the spatiotemporal tracking of ankle locations of young, healthy participants (n = 4) by comparing our tool and a stereo camera with the motion capture system as a gold standard modality. We also assessed parameters including step length, step width, cadence, and gait speed. The 2D-LiDAR system showed a much better accuracy than that of a stereo camera system, where mean absolute errors were 46.2 ± 17.8 mm and 116.3 ± 69.6 mm, respectively. Gait parameters from the 2D-LiDAR system were in good agreement with those from the motion capture system (r = 0.955 for step length, r = 0.911 for cadence). Simultaneous tracking of multiple targets by the 2D-LiDAR system was also demonstrated. The novel system might be useful in space and resource constrained clinical practice for older adults.
format Online
Article
Text
id pubmed-7826665
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-78266652021-01-25 Development and Validation of 2D-LiDAR-Based Gait Analysis Instrument and Algorithm Yoon, Seongjun Jung, Hee-Won Jung, Heeyoune Kim, Keewon Hong, Suk-Koo Roh, Hyunchul Oh, Byung-Mo Sensors (Basel) Article Acquiring gait parameters from usual walking is important to predict clinical outcomes including life expectancy, risk of fall, and neurocognitive performance in older people. We developed a novel gait analysis tool that is small, less-intrusive and is based on two-dimensional light detection and ranging (2D-LiDAR) technology. Using an object-tracking algorithm, we conducted a validation study of the spatiotemporal tracking of ankle locations of young, healthy participants (n = 4) by comparing our tool and a stereo camera with the motion capture system as a gold standard modality. We also assessed parameters including step length, step width, cadence, and gait speed. The 2D-LiDAR system showed a much better accuracy than that of a stereo camera system, where mean absolute errors were 46.2 ± 17.8 mm and 116.3 ± 69.6 mm, respectively. Gait parameters from the 2D-LiDAR system were in good agreement with those from the motion capture system (r = 0.955 for step length, r = 0.911 for cadence). Simultaneous tracking of multiple targets by the 2D-LiDAR system was also demonstrated. The novel system might be useful in space and resource constrained clinical practice for older adults. MDPI 2021-01-08 /pmc/articles/PMC7826665/ /pubmed/33430161 http://dx.doi.org/10.3390/s21020414 Text en © 2021 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
Yoon, Seongjun
Jung, Hee-Won
Jung, Heeyoune
Kim, Keewon
Hong, Suk-Koo
Roh, Hyunchul
Oh, Byung-Mo
Development and Validation of 2D-LiDAR-Based Gait Analysis Instrument and Algorithm
title Development and Validation of 2D-LiDAR-Based Gait Analysis Instrument and Algorithm
title_full Development and Validation of 2D-LiDAR-Based Gait Analysis Instrument and Algorithm
title_fullStr Development and Validation of 2D-LiDAR-Based Gait Analysis Instrument and Algorithm
title_full_unstemmed Development and Validation of 2D-LiDAR-Based Gait Analysis Instrument and Algorithm
title_short Development and Validation of 2D-LiDAR-Based Gait Analysis Instrument and Algorithm
title_sort development and validation of 2d-lidar-based gait analysis instrument and algorithm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7826665/
https://www.ncbi.nlm.nih.gov/pubmed/33430161
http://dx.doi.org/10.3390/s21020414
work_keys_str_mv AT yoonseongjun developmentandvalidationof2dlidarbasedgaitanalysisinstrumentandalgorithm
AT jungheewon developmentandvalidationof2dlidarbasedgaitanalysisinstrumentandalgorithm
AT jungheeyoune developmentandvalidationof2dlidarbasedgaitanalysisinstrumentandalgorithm
AT kimkeewon developmentandvalidationof2dlidarbasedgaitanalysisinstrumentandalgorithm
AT hongsukkoo developmentandvalidationof2dlidarbasedgaitanalysisinstrumentandalgorithm
AT rohhyunchul developmentandvalidationof2dlidarbasedgaitanalysisinstrumentandalgorithm
AT ohbyungmo developmentandvalidationof2dlidarbasedgaitanalysisinstrumentandalgorithm