Developing A Machine Vision Eye-Blink Detection Application For The Monitoring Of Zoom Fatigue

Developing A Machine Vision Eye-Blink Detection Application For The Monitoring Of Zoom Fatigue

Developing A Machine Vision Eye-Blink Detection Application For The Monitoring Of Zoom Fatigue


Dr. Francesco Biondi

University of Windsor

 

COVID-19 has sparked a drastic yet sudden transition from primarily on-site to entirely remote work conditions with an estimated 59% of Canadian workers working from home during the pandemic. With teleworking, or the practice of performing job duties from a remote location, becoming instantaneously more prevalent among the workforce an emerging and serious concern is the sense of exhaustion following long virtual meetings. The combined occurrence of grossly prolonged screen engagement together with the lack of face-to-face interaction during videoconferencing has contributed to a newly coined condition known as Zoom fatigue. Nearly 40% of teleworkers report having experienced Zoom fatigue over the past year. The clinical community also acknowledges the threat that this condition poses to mental health with complaints about increased anxiety and muscular tension due to high-intensity virtual interactions becoming more commonplace. However, despite the widespread nature of this condition, little evidence-based knowledge exists for strategies that mitigate these harmful Zoom fatigue-associated acute effects.

This overarching objective of this exploratory research project is to develop a proof-of-concept eye blink-based system capable of monitoring increasing levels of Zoom fatigue from a ubiquitous webcam video feed. 

Related Programs:
Nucleus Cores:

FUNDER:

Faculty of Engineering, University of Windsor

Faculty of Human Kinetics, University of Windsor

Office of Research and Innovation Services, University of Windsor

GRANT DURATION:

2021-2022

CO-INVESTIGATOR

University of Windsor

  • Dr. Balakumar Balasingam

COLLABORATOR

Ergonow Inc.

  • Susanne Brunet, CCPE

 

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