Abstract
ABSTRACT Traditional gesture elicitation studies generally adopted the frequency ratio to select popular gestures among users. However, the chosen gestures were not always optimal and might pose a potential risk of musculoskeletal disorder under long-term use. The purpose of our research was to apply a novel assessment system combining the indices of electromyography (EMG), electrogoniometry, and subjective preference to the end-user elicitation experiment. In this study, we conducted a two-stage experiment to compare and analyze the results of the physiological and psychological measures for 33 candidate gestures of 16 given commands. Our results indicated that this assessment system could effectively determine the candidate gestures with lower physiological loads for all given commands except Maximize, and most of the selected gestures were in line with users’ mental models. Finally, we developed an optimal user-defined gesture set for the commands accommodated to human-computer interaction (HCI).
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