Intelligent Assistive Technology and Systems Lab - click to go to homepage
IATSL develops assistive technology that is adaptive, flexible, and intelligent, enabling users to participate fully in their daily lives. Learn more about our research

Visit us:

Room 438

500 University Ave.

Toronto, Canada

P 416.946.8573

F 416.946.8570

 

Send us mail:

160 - 500 University Ave.

Toronto, ON, M5G 1V7

Canada

 

email us!

 

Follow IATSL on Twitter

Shehroz Khan

Photo of Shehroz
Assistant Professor (status)

BME, University of Toronto

Scientist

Toronto Rehabilitation Institute

shehroz.khan@uhn.ca

 


Wearable Data Sharing News

Dr. Shehroz Khan is currently leading a project on agitation detection in people with dementia. The team has collected agitation data using Empatica E4 in a dementia care unit with 20 people with dementia. This data can now be shared with interested researchers. The data include the time stamp (EST_time), Electrodermal Activity (EDA), acceleration along x, y and z axes (i.e., accx, accy and accz), Blood Volume Pulse (BVP), skin temperature (temp), and Label (i.e., whether agitation occurs). If you want to access this sensor data, please email the study manager Bing Ye @ bing.ye@utoronto.ca with the subject line “Access to wearable data for agitation detection study.” Requiring researcher would also need to provide the following information: full name, professional email address, the reason for using the data, and institute/organization affiliation.

Please note that external researchers are responsible for obtaining their own REB/IRB approval if their institution requires it.


Biography

Dr. Shehroz Khan currently works as a Scientist in the Artificial Intelligence & Robotics for Rehab lab at the Toronto Rehabilitation Institute (TRI). He obtained his PhD degree from the University of Waterloo, Canada in 2016 and Master’s degree in 2010 from the National University of Ireland Galway, Ireland. He did his post-doctoral research from the University of Toronto and TRI. Prior to his academic work, he worked in the industry for around 10 years in various scientific and engineering roles. His main research focus is the development of machine learning and deep learning algorithms within the realms of ARIAL - Aging, Rehabilitation, and Intelligent Assisstive Living. His main research focus areas are: a) creating non-invasive fall detection methods, b) building models for predicting agitation and aggression in people living with dementia, and c) developing Intelligent Homes strategies to enhance physical and cognitive health among older adults.