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While the psychophysics of weight perception may help assess the effort needed in manual material handling tasks, the perception of weight is subjective and not necessarily accurate. The purpose of this study was to examine weight perception during standing and walking. Participants (n=10) performed a series of weight comparison trials against a reference load while holding loads (standing) or carrying loads (walking). Polynomial logistic regression models were built to examine the effects of walking, box weight ratio, and reference weight level on the probability of detecting a weight difference. The results showed that weight ratio and reference weight level had statistically significant effects on the detection probability while walking did not have a significant effect. Findings from this study can help inform the design of subjective evaluation of job demands involving motion, and it can be further extended to the gradual increase in load of strengthening tasks in therapeutic exercises. 

Conventional work posture training tools included pamphlets, one-time training orientation, and/or videos. These tools did not always yield satisfactory training outcomes, and the incident rate of work-related musculoskeletal disorders did not substantially lower. In this research, modern augmented reality (AR) technology was leveraged to deliver interactive, holistic, whole-body visual information to convey safe work postures. The developmental procedure followed DMAIC by first defining specifications of training content, which led to the development of the training tool, including 3D reconstruction of a virtual instructor and building of user interface based on user-centered framework. This AR training tool was measured and analyzed through usability evaluation, and quantitative and qualitative data were obtained for cross-validation and usability issue source identification. Findings revealed the utility of 3D reconstruction of a virtual instructor and practicality of adopting conventional usability evaluation method for AR user interface usability evaluation. Feedback from the usability evaluation via questionnaire, think aloud, and post-task open-ended responses are employed to iteratively design the next version of the AR posture training tool.