Biography

Ahmad Akl holds a Masters of Applied Science in Electrical and Computer Engineering from the University of Toronto. His Master’s work was in the field of communications and signal processing and his work focused on developing a novel accelerometer-based gesture recognition system. Ahmad pursued his undergraduate studies at the American University of Sharjah, in the United Arab Emirates, and majored in Electrical Engineering. His undergraduate project, a two-semester project, entitled, “EEG Signal Classification for English Alphabet and Digit Classification,” was to develop a brain-computer interface that would be able to classify the English alphabet (A to Z) and digits (1 – 9 plus the underscore) based on target and non-target responses.

Ahmad joined IATSL in September 2010 as a Ph.D. Student. His work will focus on the problem of detecting mild cognitive impairment in older adults using unobtrusive sensing technologies. More specifically, Ahmad will target designing and implementing a smart system that can predict mild cognitive impairment in older adults by devising a novel approach to modeling the subjects’ daily activities and in-home walking speed. Significant changes in the subjects’ models of daily activities and in-home walking speed will signal a potential change in the subjects’ cognition. Such a system is of great significance since it would enable the family to gain a measure of control over the situation, and would set the stage for planning for financial and future health care needs. Furthermore, even if no effective treatment for cognitive decline exists, interventions that enhance daily functioning and safety and reduce emotional distress, individual fear, and uncertainty about the future are certainly available.

Select Publications

Peer Reviewed Journal Articles

A. Akl, J. Snoek, A. Mihailidis (2014). "Generalized Linear Models of Home Activity and In-home Waking Speed for Automatic Detection of Mild Cognitive Impairment in Older Adults," submitted to IEEE Transactions on Biomedical Engineering.

A. Akl, B. Taati, A. Mihailidis (2014). "Autonomous Unobtrusive Detection of Mild Cognitive Impairment in Older Adults," submitted to IEEE Transactions on Biomedical Engineering.

A. Akl, C. Feng, and S. Valaee. (2011). "A Novel Accelerometer-based Gesture Recognition System," IEEE Transactions on Signal Processing, 59(12), 6197-6205.

Peer Reviewed Conference Proceedings

A. Akl, J. Snoek, and A. Mihailidis, "Generalized linear models of home activity for automatic detection of mild cognitive impairment in older adults," IEEE EMBC 2014, August 26 – 30, pp. 680 – 683, Chicago, Illinois, USA.

A. Akl, S. Valaee, “Gesture Recognition via Dynamic Time Warping, Affinity Propagation, & Compressive Sensing,” IEEE ICASSP 2010, March 14 – 19, Dallas, Texas, USA.

Master’s Thesis

Akl, A. (2010) A Novel Accelerometer-based Gesture Recognition System. University of Toronto. 1-82. Masters Thesis.