Investigating Body Gestures as Means of Input Modalities in Crowdsourced Microtasks

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Abstract

Microtask crowdsourcing has grown in popularity in recent years. Microtasking is a form of crowdsourcing in which typically small, simple tasks are distributed over the Internet to a large number of people, also known as workers. Workers are highly susceptible to developing musculoskeletal disorders due to prolonged computer use and the monotonous, performance-oriented nature of microtasking. Fortunately, it has been demonstrated that exercise can remedy these health issues. Since some body gestures resemble low-intensity exercise, the use of gestures as input in crowdsourced microtasks has the potential to improve the health of the worker. The purpose of this study was to determine which gestures are effective for controlling microtask workflows in terms of health benefits and usability. In an effort to maximize the positive impact on health, a total of 12 gestures were developed for four distinct microtask workflow elements. Then, we incorporated these gestures into a survey to evaluate the subjective perceptions of usability. On the basis of the survey results, we ranked these gestures for each workflow element and proposed three gesture-command dictionaries optimized for maximum efficiency. Due to the numerous limitations of this study, it is strongly recommended that the outcomes be enhanced. The primary contribution of this study is, therefore, the establishment of new research directions for gestural input in microtasking and in all human-computer interaction.