Classification of Whole-Body Postural Discomfort Using Cluster Analysis
Author ORCID Identifier
Jaejin Hwang:https://orcid.org/0000-0001-5831-9688
Publication Title
International Journal of Environmental Research and Public Health
ISSN
16617827
E-ISSN
16604601
Document Type
Article
Abstract
The objectives of this study were to evaluate the effect of gender and postures of the neck, trunk, and knee on overall postural discomfort, and to classify combined postures into different postural discomfort groups. A total of 95 participants (42 males and 53 females) performed 45 different static postures, which were a combination of 3 neck angles, 5 trunk angles, and 3 knee angles, and rated the perceived postural discomfort. Non-hierarchical K-means cluster analysis was employed to classify the 45 different combined postures into several postural discomfort groups. Postural discomfort was significantly affected by gender and postures of the neck, trunk, and knee (p < 0.001). Three clusters (high, medium, and low discomfort) were identified and the postural discomfort was significantly different between clusters (p < 0.001). The high discomfort group consisted of mostly males with high knee and trunk flexion angles and a moderate neck flexion angle. The low discomfort group was female-dominant with low neck and trunk flexion angles and a moderate knee flexion angle. The different flexibility (stiffness) of the joint motions between genders may affect the gender difference in postural discomfort. The knee and trunk postures were critical to the postural balance, which may affect the perception of whole-body discomfort. This result will be useful for developing and improving postural observation tools.
First Page
1
Last Page
9
Publication Date
11-2-2020
DOI
10.3390/ijerph17228314
PubMed ID
33182760
Keywords
Classification, Cluster analysis, Discomfort, Joint angle, Whole-body posture
Recommended Citation
Hwang, Jaejin and Lee, Kyung Sun, "Classification of Whole-Body Postural Discomfort Using Cluster Analysis" (2020). NIU Bibliography. 248.
https://huskiecommons.lib.niu.edu/niubib/248
Department
Department of Industrial and Systems Engineering