Measuring elemental time and duty cycle using automated video processing.
A marker-less 2D video algorithm measured hand kinematics (location, velocity and acceleration) in a paced repetitive laboratory task for varying hand activity levels (HAL). The decision tree (DT) algorithm identified the trajectory of the hand using spatiotemporal relationships during the exertion...
| Publicado en: | Ergonomics Vol. 59; no. 11; pp. 1514 - 1526 |
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| Autores principales: | , , , , |
| Formato: | equations & formulas pictorial research tables/charts tracings Journal Article |
| Publicado: |
Taylor & Francis Ltd
Nov2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=119304039&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 119304039 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00140139 ERO jtl: Ergonomics issn: 00140139 maglogo: Y pubinfo: dt: Nov2016 vid: 59 iid: 11 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 119304039 119304039 119304039 10.1080/00140139.2016.1146347 119304039 ppf: 1514 ppct: 12 formats: tig: atl: Measuring elemental time and duty cycle using automated video processing. aug: au: Akkas, Oguz Lee, Cheng-Hsien Hu, Yu Hen Yen, Thomas Y. Radwin, Robert G. affil: Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, WI, USA sug: subj: Hand Kinematics Task Performance and Analysis Human Motion Analysis Systems Algorithms P-Value Decision Trees ab: A marker-less 2D video algorithm measured hand kinematics (location, velocity and acceleration) in a paced repetitive laboratory task for varying hand activity levels (HAL). The decision tree (DT) algorithm identified the trajectory of the hand using spatiotemporal relationships during the exertion and rest states. The feature vector training (FVT) method utilised the k-nearest neighbourhood classifier, trained using a set of samples or the first cycle. The average duty cycle (DC) error using the DT algorithm was 2.7%. The FVT algorithm had an average 3.3% error when trained using the first cycle sample of each repetitive task, and had a 2.8% average error when trained using several representative repetitive cycles. Error for HAL was 0.1 for both algorithms, which was considered negligible. Elemental time, stratified by task and subject, were not statistically different from ground truth (p < 0.05). Both algorithms performed well for automatically measuring elapsed time, DC and HAL. Practitioner Summary: A completely automated approach for measuring elapsed time and DC was developed using marker-less video tracking and the tracked kinematic record. Such an approach is automatic, repeatable, objective and unobtrusive, and is suitable for evaluating repetitive exertions, muscle fatigue and manual tasks. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts tracings Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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