Atena Roshan Fekr

Atena Roshan Fekr

Assistant Professor

PhD (McGill)

Research Stream: Engineering in a Clinical Setting | Neural, Sensory Systems & Rehabilitation

 

Contact Information

Toronto Rehabilitation Institute
550 University Avenue, Room 1-121-1
Toronto, Ontario M5G 2A2 Canada
+1 416 597-3422, extension 7622 (office)
atena.roshanfekr@uhn.ca (email)

Main Appointments

  • Affiliate Scientist, Toronto Rehabilitation Institute (TRI), University Health Network (UHN)
  • Department of Mechanical & Industrial Engineering

Additional Appointments

  • Institute of Biomaterials & Biomedical Engineering

Research Interests

My current primary research interest is to combine ubiquitous sensing technologies with machine learning, optimization and signal processing techniques to solve real-world, practical problems. This includes but not limited to:

  • Development of new technological solutions for Slips, Trips and Falls (STF) prevention powered by Artificial Intelligent (AI),
  • Physiological and biomechanical analysis of patients with mobility impairment to provide smart solutions for in/outdoor environment,
  • Designing affordable smart technologies for remote monitoring of community-dwelling older adults.

We are designing, validating, testing, and commercializing ideas in collaboration with partners and policy makers.

Select Publications

Roshan Fekr, G. Evans, G. Fernie. Walkway Safety Evaluation and Hazards Investigation for Trips and Stumbles Prevention. International Ergonomics Association 2018, Advances in Intelligent Systems and Computing, vol 819,Springer.

Janidarmian, A. Roshan Fekr, K. Radecka, Z. Zilic, Z. A Comprehensive Analysis on Wearable Acceleration Sensors in Human Activity Recognition. Sensors2017, 17, 529.

Roshan Fekr, M. Janidarmian, K. Radecka and Z. Zilic. Respiration Disorders Classification With Informative Features for m-Health Applications. IEEE Journal of Biomedical and Health Informatics, vol. 20, no. 3, pp. 733-747, May 2016.

Roshan Fekr, K. Radecka and Z. Zilic. Design and Evaluation of an Intelligent Remote Tidal Volume Variability Monitoring System in E-Health Applications. IEEE Journal of Biomedical and Health Informatics, vol. 19, no. 5, pp. 1532-1548, Sept. 2015.

Roshan Fekr, M. Janidarmian, K. Radecka, Z. Zilic. Movement analysis of the chest compartments and a real-time quality feedback during breathing therapy. Netw Model Anal Health Inform Bioinforma (2015) 4: 21.