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Clara: Design of a New System for Passive Sensing of Depression, Stress and Anxiety in the Workplace

  • Juwon LeeEmail author
  • Megan Lam
  • Caleb Chiu
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 288)

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.

Keywords

Workplace mental health Passive sensing Machine learning Depression Stress Anxiety 

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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019

Authors and Affiliations

  1. 1.The University of Hong KongPokfulamHong Kong
  2. 2.Neurum HealthSheung WanHong Kong

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