55 UTAH ERGO ANALYZER POSTURE CLASSIFICATION TOOL VS. PEAK MOTUS® MOTION ANALYSIS IN 2D WRIST FLEXION/EXTENSION AND ULNAR/RADIAL DEVIATION Andrew S. Merryweather, University of Utah Richard F. Sesek, University of Utah Joel Daniels II, University of Utah Donald S. Bloswick, University of Utah a.merryweather@utah.edu ABSTRACT The Utah Ergo Analyzer is a computer software program developed at the University of Utah for the purpose of posture classification and ergonomics job analysis using videotape of jobs. As part of a NIOSH supported study to identify risk factors associated with Distal Upper Extremity (DUE) illnesses and disorders, the Utah Ergo Analyzer (UTEA) provides a systematic approach for classifying DUE postures. The purpose of this study is to determine the validity and agreement between postures categorized by analysts using the Utah Ergo Analyzer and those categorized using motion analysis software developed by Vicon-Peak Performance Technologies, Inc. The Utah Ergo Analyzer restricts classification of postures using preset categories, while the PEAK system tracks a continuous measure of posture. Postures were assigned to each task using both UTEA and PEAK using the same guidelines. This allowed for a direct comparison between analysis methods to be performed. The Utah Ergo Analyzer provides a systematic approach for calculating postural related data that may be used for determining risk factors associated with DUE illnesses and disorders. INTRODUCTION Background Videotape analysis methods have been widely adopted by ergonomic analysts in the study of risk factors associated with jobs. Electronic goniometers can be used to quantify posture; however it is important to obtain these measurements without interfering with the work being done. Therefore, most measurements are taken from videotape instead of directly from the worker. Unfortunately, this introduces a greater probability for error. Parallax created from improper camera setup or wide-angle camera views required to capture the entire process can create problems when attempting to accurately quantifying orthopedic angles from videotape (Radwin, 1999). Past and current research has identified specific factors that contribute to the development of musculoskeletal disorders (MSDs). These factors include, but may not be limited to: awkward posture, force, repetitive motion, temperature, and vibration (NIOSH, 1997). It is apparent that high forces combined with awkward posture and long duration increase the risk of developing an