Mahsa Khalili
Postdoctoral Fellow
As a member of the Canadians Saving Arrest Victims Everywhere (CanSAVE) Novel Biosensor project, Mahsa's research is focused on developing wearable technologies to detect out-of-hospital sudden cardiac arrest incidents. This work involves (1) designing wearable sensors to collect bio-signals associated with cardiac arrest conditions (e.g., electrocardiogram, breathing rate); and (2) using machine learning to identify appropriate combinations of collected bio-signals to detect a sudden cardiac arrest event. The outcome of this research may contribute to rapid recognition of out-of-hospital cardiac arrest, which can summon bystanders and Emergency Medical Services to provide the required emergent life-saving interventions.
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Publications
- A Comparison Between Conventional and Terrain-Specific Adaptive Pushrim-Activated Power-Assisted Wheelchairs (2021)
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 29, 2550--2558 - A Comparison Between Conventional and User-Intention-Based Adaptive Pushrim-Activated Power-Assisted Wheelchairs (2021)
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 29, 2511--2520 - Perception of autonomy among people who use wheeled mobility assistive devices: dependence on environment and contextual factors (2021)
Disability and Rehabilitation: Assistive Technology, - Perception of autonomy among people who use wheeled mobility assistive devices: dependence on the type of wheeled assistive technology (2021)
Assistive Technology, , 1--9 - Perceptions of power-assist devices: interviews with manual wheelchair users (2021)
Disability and Rehabilitation: Assistive Technology, , 1--11
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