The influence of training on decision times and errors associated with classifying trunk postures using video-based posture assessment methods

The purpose of this study was to examine the influence of training on the decision times and errors associated with video-based trunk posture classifications. Altogether, 30 amateur and 30 knowledge-based participants completed a three-phase study (pre-training, training, post-training) that require...

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Bibliographic Details
Published in:Ergonomics 2011-02, Vol.54 (2), p.197-205
Main Authors: Weir, Patricia L., Andrews, David M., van Wyk, Paula M., Callaghan, Jack P.
Format: Article
Language:English
Subjects:
Analysis of Variance
Applied physiology
Biological and medical sciences
Boundaries
Classification
Decision analysis
Decision Making
decision time
Ergonomics
Ergonomics. Work place. Occupational physiology
Errors
Feasibility studies
Female
Health risks
Human performance
Human physiology applied to population studies and life conditions. Human ecophysiology
Humans
Image classification
Joints - physiology
Knowledge
Knowledge bases (artificial intelligence)
Male
Medical sciences
Posture
Posture - physiology
posture classification errors
posture matching
Space life sciences
Studies
Thorax - physiology
Time Factors
Training
trunk posture perception
video
Video data
Young Adult
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Summary:The purpose of this study was to examine the influence of training on the decision times and errors associated with video-based trunk posture classifications. Altogether, 30 amateur and 30 knowledge-based participants completed a three-phase study (pre-training, training, post-training) that required them to classify static trunk postures in images on a computer screen into a posture category that represented the angle of the trunk depicted. Trunk postures were presented in both flexion/extension and lateral bend views and at several distances from the boundaries of the posture categories. Both decision time and errors decreased as distance from the boundaries increased. On average, amateur analysts experienced a larger decrease in decision time per posture classification than knowledge-based analysts (amateur: 0.79 s, knowledge-based: 0.60 s; p
ISSN:0014-0139
1366-5847
DOI:10.1080/00140139.2010.547603