Abstract
The objective of this paper is to introduce the application of Data Dependent Systems (DDS) methodology to the fields of ergonomics. Many current techniques in ergonomics utilize static models, which can have significant limitations. DDS is a stochastic modeling and analysis technique which can be used to capture the system dynamics through quantitative analysis of the available data. DDS has been successfully applied to understand systems dynamics in a number of domains such as manufacturing, weather forecasting, and agriculture. In this research, DDS was used to analyze two sets of ergonomics data: time-based hand-skin temperature data for the evaluation of two types of glove liners in the recent past, and comparison of two lifting styles in the distant past. In both cases DDS was able to capture the differences between the experimental conditions and, more importantly was able to enumerate subject differences. The implications of the results and the potential of the DDS methodology are discussed.
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