This research presents the development and evaluation of a fuzzy linguistic model designated to predict the risk of carpal tunnel syndrome (CTS) in an occupational setting. CTS has become one of the largest problems facing ergonomists and the medical community because it is developing in epidemic proportions within the occupational environment. In addition, practitioners are interested in identifying accurate methods for evaluating the risk of CTS in an occupational setting. It is hypothesized that many factors impact an individual's likelihood of developing CTS and the eventual development of CTS. This disparity in the occurrence of CTS for workers with similar backgrounds and work activities has confused researchers and has been a stumbling block in the development of a model for widespread use in evaluating the development of CTS. Thus this research is an attempt to develop a method that can be used to predict the likelihood of CTS risk in a variety of environments. The intent is that this model will be applied eventually in an occupational setting, thus model development was focused on a method that provided a usable interface and the desired system inputs can also be obtained without the benefit of a medical practitioner. The methodology involves knowledge acquisition to identify and categorize a holistic set of risk factors that include task-related, personal, and organizational categories. The determination of relative factor importance was accomplished using analytic hierarchy processing (AHP) analysis. Finally a mathematical representation of the CTS risk was accomplished by utilizing fuzzy set theory in order to quantify linguistic input parameters. An evaluation of the model including determination of sensitivity and specificity is conducted and the results of the model indicate that the results are fairly accurate and this method has the potential for widespread use. A significant aspect of this research is the comparison of this technique to other methods for assessing presence of CTS. The results of this evaluation technique are compared with more traditional methods for assessing the presence of CTS.
[1]
Michio Sugeno,et al.
Fuzzy systems theory and its applications
,
1991
.
[2]
Michael D. McNeese,et al.
Knowledge acquisition of tactical air-to-ground mission information using concept mapping
,
1992,
Proceedings of the IEEE 1992 National Aerospace and Electronics Conference@m_NAECON 1992.
[3]
Pamela Rochelle McCauley-Bell.
A fuzzy linguistic artificial intelligence model for assessing risks of cumulative trauma disorders of the forearm and hand
,
1993
.
[4]
Michael D. McNeese,et al.
Knowledge as Design: A Methodology for Overcoming Knowledge Acquisition Bottlenecks in Intelligent Interface Design
,
1991
.
[5]
Adedeji B. Badiru,et al.
Fuzzy modeling and analytic hierarchy processing to quantify risk levels associated with occupational injuries. I. The development of fuzzy-linguistic risk levels
,
1996,
IEEE Trans. Fuzzy Syst..
[6]
Adedeji B. Badiru,et al.
Fuzzy modeling and analytic hierarchy processing-means to quantify risk levels associated with occupational injuries. II. The development of a fuzzy rule-based model for the prediction of injury
,
1996,
IEEE Trans. Fuzzy Syst..