Evaluating the efficacy of singular spectrum transformation in detecting working posture changes in a time series

In the current workplace, most manual labor is composed of high-frequency tasks with low physical workloads. Moreover, traditional ergonomic evaluation methods often have difficulty identifying slight variations in working postures and physical workloads in manual tasks. The aim of this study is to...

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Autores principales:	Kazuki HIRANAI, Akisue KURAMOTO, Akihiko SEO
Formato:	article
Lenguaje:	EN
Publicado:	The Japan Society of Mechanical Engineers 2019
Materias:	anomaly detection singular spectrum transformation working posture measurement work analysis human motion analysis movement variability Mechanical engineering and machinery TJ1-1570
Acceso en línea:	https://doaj.org/article/0c237e6ac40b4a6b97bc970033b16974
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spelling	oai:doaj.org-article:0c237e6ac40b4a6b97bc970033b169742021-11-29T05:52:02ZEvaluating the efficacy of singular spectrum transformation in detecting working posture changes in a time series2187-974510.1299/mej.19-00464https://doaj.org/article/0c237e6ac40b4a6b97bc970033b169742019-12-01T00:00:00Zhttps://www.jstage.jst.go.jp/article/mej/7/1/7_19-00464/_pdf/-char/enhttps://doaj.org/toc/2187-9745In the current workplace, most manual labor is composed of high-frequency tasks with low physical workloads. Moreover, traditional ergonomic evaluation methods often have difficulty identifying slight variations in working postures and physical workloads in manual tasks. The aim of this study is to determine whether singular spectrum transformation (SST) can detect changes in human posture during manual tasks. In an experiment, eleven male participants performed lightweight material handling tasks under differing work conditions and task intervals, and an electromagnetic motion-tracking system measured their working postures. An anomaly score for each joint angle was calculated using SST, and the means, coefficients of variation (CV), and over-threshold values recorded during each experimental condition were compared. Lag is an important SST parameter for detecting how working posture differs between tasks. Therefore, the effects of changes in lag on the anomaly score were investigated. For each joint angle, the mean anomaly scores were greater under random task intervals than under constant intervals. In contrast, the CV of the anomaly score was smaller under random intervals than under constant intervals. The number of over-threshold values was significantly larger under random intervals than under constant intervals when SST was applied to the elbow flexion angle. The lag was determined according to the time of the work cycle and agreed with lag times observed in previous studies. This study concludes that the efficacy of SST was shown through detection of working posture changes in a time series, and that lag should be selected in accordance with the work cycle.Kazuki HIRANAIAkisue KURAMOTOAkihiko SEOThe Japan Society of Mechanical Engineersarticleanomaly detectionsingular spectrum transformationworking posture measurementwork analysishuman motion analysismovement variabilityMechanical engineering and machineryTJ1-1570ENMechanical Engineering Journal, Vol 7, Iss 1, Pp 19-00464-19-00464 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	anomaly detection singular spectrum transformation working posture measurement work analysis human motion analysis movement variability Mechanical engineering and machinery TJ1-1570
spellingShingle	anomaly detection singular spectrum transformation working posture measurement work analysis human motion analysis movement variability Mechanical engineering and machinery TJ1-1570 Kazuki HIRANAI Akisue KURAMOTO Akihiko SEO Evaluating the efficacy of singular spectrum transformation in detecting working posture changes in a time series
description	In the current workplace, most manual labor is composed of high-frequency tasks with low physical workloads. Moreover, traditional ergonomic evaluation methods often have difficulty identifying slight variations in working postures and physical workloads in manual tasks. The aim of this study is to determine whether singular spectrum transformation (SST) can detect changes in human posture during manual tasks. In an experiment, eleven male participants performed lightweight material handling tasks under differing work conditions and task intervals, and an electromagnetic motion-tracking system measured their working postures. An anomaly score for each joint angle was calculated using SST, and the means, coefficients of variation (CV), and over-threshold values recorded during each experimental condition were compared. Lag is an important SST parameter for detecting how working posture differs between tasks. Therefore, the effects of changes in lag on the anomaly score were investigated. For each joint angle, the mean anomaly scores were greater under random task intervals than under constant intervals. In contrast, the CV of the anomaly score was smaller under random intervals than under constant intervals. The number of over-threshold values was significantly larger under random intervals than under constant intervals when SST was applied to the elbow flexion angle. The lag was determined according to the time of the work cycle and agreed with lag times observed in previous studies. This study concludes that the efficacy of SST was shown through detection of working posture changes in a time series, and that lag should be selected in accordance with the work cycle.
format	article
author	Kazuki HIRANAI Akisue KURAMOTO Akihiko SEO
author_facet	Kazuki HIRANAI Akisue KURAMOTO Akihiko SEO
author_sort	Kazuki HIRANAI
title	Evaluating the efficacy of singular spectrum transformation in detecting working posture changes in a time series
title_short	Evaluating the efficacy of singular spectrum transformation in detecting working posture changes in a time series
title_full	Evaluating the efficacy of singular spectrum transformation in detecting working posture changes in a time series
title_fullStr	Evaluating the efficacy of singular spectrum transformation in detecting working posture changes in a time series
title_full_unstemmed	Evaluating the efficacy of singular spectrum transformation in detecting working posture changes in a time series
title_sort	evaluating the efficacy of singular spectrum transformation in detecting working posture changes in a time series
publisher	The Japan Society of Mechanical Engineers
publishDate	2019
url	https://doaj.org/article/0c237e6ac40b4a6b97bc970033b16974
work_keys_str_mv	AT kazukihiranai evaluatingtheefficacyofsingularspectrumtransformationindetectingworkingposturechangesinatimeseries AT akisuekuramoto evaluatingtheefficacyofsingularspectrumtransformationindetectingworkingposturechangesinatimeseries AT akihikoseo evaluatingtheefficacyofsingularspectrumtransformationindetectingworkingposturechangesinatimeseries
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Evaluating the efficacy of singular spectrum transformation in detecting working posture changes in a time series

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