A Human-Centered Activity Tracking System: Toward a Healthier Workplace

Lost productivity from lower back injuries in workplaces costs billions of U.S. dollars per year. A significant fraction of such workplace injuries are the result of workers not following best practices. In this paper, we present the design, implementation, and evaluation of a novel computer-vision-based system that aims to increase the workers' compliance to best practices. The system consists of inexpensive programmable depth sensors, wearable devices, and smart phones. The system is designed to track the activities of consented workers using the depth sensors, alert them discreetly on detection of noncompliant activities, and produce cumulative reports on their performance. Essentially, the system provides a valuable set of services for both workers and administrators toward a healthier and, therefore, more productive workplace. This study advances the state of the art in the following ways: 1) a set of mechanisms that enable nonintrusive privacy-aware selective tracking of consented workers in the presence of people that should not be tracked; 2) a single sign-on worker identification mechanism; 3) a method that provides realtime detection of noncompliant activities; and 4) a usability study that provides invaluable feedback regarding system design and deployment, as well as future areas of improvements.