Research Article
Clara: Design of a New System for Passive Sensing of Depression, Stress and Anxiety in the Workplace
@INPROCEEDINGS{10.1007/978-3-030-25872-6_2, author={Juwon Lee and Megan Lam and Caleb Chiu}, title={Clara: Design of a New System for Passive Sensing of Depression, Stress and Anxiety in the Workplace}, proceedings={Pervasive Computing Paradigms for Mental Health. 9th International Conference, MindCare 2019, Buenos Aires, Argentina, April 23--24, 2019, Proceedings}, proceedings_a={MINDCARE}, year={2019}, month={7}, keywords={Workplace mental health Passive sensing Machine learning Depression Stress Anxiety}, doi={10.1007/978-3-030-25872-6_2} }
- Juwon Lee
Megan Lam
Caleb Chiu
Year: 2019
Clara: Design of a New System for Passive Sensing of Depression, Stress and Anxiety in the Workplace
MINDCARE
Springer
DOI: 10.1007/978-3-030-25872-6_2
Abstract
Collective evidence from research on the detriment of mental ill-health in the workplace consistently points to the need for better management of workplace mental health. However, difficulty in making a reliable, unobtrusive measurement of an employee’s mental health remains an obstacle in the way of effective interventions at an organizational level. In this paper, a system named Clara is proposed with aims to enable passive measurement, and hence effective management, of workplace mental health. A literature review of different approaches to measure depression, stress, and anxiety is presented, followed by a discussion on the design principles that guided the development of Clara. The overarching system architecture is then outlined, and individual components of the system are explored in finer details. The paper illustrates how Clara, with its passive measurement techniques, has the potential to enable objective assessment of workplace depression, stress and anxiety, allowing for delivery of timely interventions.