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Dr. Thomas E. Doyle

Director, McMaster eHealth Graduate Program

McMaster University

Associate Professor

McMaster School of Biomedical Engineering

Associate Professor

Department of Electrical & Computer Engineering

Expertise:
Biomedical signal processing; Human-computer interfacing (HCI); Brain computer interfacing (BCI); Machine learning for the augmentation, rehabilitation, and enhancement of human attributes
Research Clusters:

Overview

Thomas Edward Doyle holds a Ph.D. in Electrical and Computer Engineering Science from the University of Western Ontario, Canada. He also holds a Masters of Engineering Science (M.E.Sc) in Electrical and Computer Engineering, a Bachelor of Engineering Science (B.E.Sc) in Electrical and Computer Engineering, a Bachelor of Science (B.Sc) in Computer Science. Dr. Doyle has taught at McMaster University, the University of Western Ontario, and the University of Ontario Institute of Technology.

In recognition of his contribution to engineering education, Dr. Doyle was awarded the 2013 McMaster President's Award for Outstanding Contributions to Teaching and Learning. The President's Award for Outstanding Contributions to Teaching and Learning recognizes those who have significantly enhanced the quality of their students' learning experience through innovative teaching methods. It is an award that appreciates and celebrates an educators achievements over time. The award citation may be read here.and the related McMaster University News article may be read here .

Electrical, Computer, and Biomedical Engineering Research a.k.a Cybranetics

My technical domain research areas include biomedical signal processing, health informatics, human-computer interfacing (HCI), brain computer interfacing (BCI), and machine learning for the augmentation, rehabilitation, and enhancement of human attributes.

My research investigates the communication channel between the man and the machine for the enhancement of assistive and rehabilitative computing technology. Recent research has focused on the hearing prosthetic and the use of electrophysiological signals for improved autonomous control. Given that the traditional hearing aid is adorned about the ear, I measured and employed the electrical signals from both the brain and the eye. The measurement and analysis of the signals were performed using hardware and software that were fully designed and implemented by the author. This research has resulted in the development of a model that successfully classifies its users affective response by using a learning algorithm on several hearing related electrophysiological signals.

Perhaps the best description of my research is derived from the term cybernetics, which was defined by Norbert Wiener as the study of communication and control in the animal and the machine. I believe that the focus of my work is best defined as cybranetics, or the study of communication and control between the animal and machine.

Pedagogical Research

Educational research requires reflection and analysis on current practices to create new pedagogy and structure experimental methods and data collection. Dr. Doyle's new approach to teaching and learning first year design was recognized for its innovation by the Higher Education Quality of Ontario (HEQCO) and as such was funded for study of the pedagogical methods. In addition, the work leading up to the current Cornerstone design approach was a large consideration for the McMaster's President's Award for Outstanding Contribution to Teaching and Learning.

In addition to the work being done in Dr. Doyle's classes, he was instrumental in the design of the Experiential Playground and Innovation Classroom (EPIC) for first year engineering. This classroom is devoted to providing year one students learning experiences that are aimed at consolidating what they learning in classes through real world applications. The rapid prototyping machines are run from this classroom and the Engineering Computation course offers voluntary labs in app development, automation, robotics, and game design.

My pedagogical domain research areas are primarily focused on improving engineering education, verification of academic integrity, machine learning algorithms for predictive student retention, distributed interactive simulation, and medical training devices.

Education

B.E.Sc, B.Sc, M.E.Sc, Ph.D. (Western Ontario, Canada)

Achievements

P.Eng. ;  Selected as a 2015 Impact Fellow by the McMaster Institute for Innovation and Excellence in Teaching and Learning (MIIETL) ; President's Award for Outstanding Contributions to Teaching & Learning (McMaster University, 2013) ;