Rory directly drives and coordinates the engineering projects in the lab related to prosthetics including design of training tools, sensory feedback systems, and research platforms. Rory plays a key role as an interface between research at the University of Alberta and clinical implementation at the Glenrose ensuring technologies are clinically relevant and translatable. His research interests include 3D printing, robotics, and device design as well as motor, sensory, and machine learning.
View Rory’s MSc thesis here.
- Clinical Engineer, Glenrose Rehabilitation Hospital, Alberta Health Services.
- The Myoelectric Training Tool (MTT)
- The Bento Arm
- Sensory Feedback Systems
- Schofield JS, Dawson MR, Carey JP, Hebert JS, 2014. “Characterizing the effects of amplitude, frequency and limb position on vibration induced movement illusions: Implications in sensory-motor rehabilitation.”, Technology and Health Care. 2014. [in press, accepted Nov. 2014]
- M.R. Dawson, C. Sherstan, J.P. Carey, J.S. Hebert, P.M. Pilarski, “Development of the Bento Arm: An Improved Robotic Arm for Myoelectric Training and Research,” MEC14: Myoelectric Controls Symposium, Fredericton, New Brunswick, August 18-22, 2014
- J.S. Hebert, K.M. Chan, M.R. Dawson, “Comparative Sensory Outcomes for Three Transhumeral Targeted Reinnervation Cases”. MEC14: Myoelectric Controls Symposium, Fredericton, New Brunswick, August 18-22, 2014.
- A.L. Edwards, M.R. Dawson, J.S. Hebert, R.S. Sutton, K.M. Chan, P.M. Pilarski, “Adaptive Switching in Practice: Improving Myoelectric Prosthesis Performance through Reinforcement Learning,” MEC14: Myoelectric Controls Symposium, Fredericton, New Brunswick, August 18-22, 2014.
- G.W. Melenka, J.S. Schofield, M.R. Dawson, J.P. Carey, “Evaluation of Dimensional Accuracy and Material Properties of the MakerBot 3D Desktop Printer,”Rapid Prototyping Journal, Accepted Jan 4th 2014, in press.
- J.S. Hebert, J.L. Olson, M.J. Morhart M.R. Dawson, P.D. Marasco, T.A. Kuiken, K.M. Chan, , “Novel Targeted Sensory Reinnervation Technique to Restore Functional Hand Sensation after Transhumeral Amputation,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, Accepted Nov 24th 2013, in press.
- A.L. Edwards, A. Kearney, M.R. Dawson, R.S. Sutton, and P.M. Pilarski, “Temporal-Difference Learning to Assist Human Decision Making during the Control of an Artificial Limb,” 1st Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM), Oct. 25-27, Princeton, New Jersey, USA, 2013.
- P.M. Pilarski, M.R. Dawson, T. Degris, J.P. Carey, K.M. Chan, J.S. Hebert, R.S. Sutton, , “Adaptive Artificial Limbs: A Real-Time Approach to Prediction and Anticipation,” IEEE Robotics & Automation Magazine, vol. 20, no.1, pp. 53–64, March 2013.
- P.M. Pilarski, M.R. Dawson, T. Degris, J.P. Carey, and R.S. Sutton, “Dynamic Switching and Real-time Machine Learning for Improved Human Control of Assistive Biomedical Robots,” Proceedings of the 4th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob), June 24-27, Roma, Italy, pp. 296-302, 2012.
- M.R. Dawson, F. Fahimi, J. P. Carey, “The Development of a Myoelectric Training Tool for Above-Elbow Amputees,” The Open Biomedical Engineering Journal, 6:5–15, 2012.
- M.R. Dawson, J. P. Carey, F. Fahimi, “Review of Myoelectric Training Systems,” Expert Reviews of Medical Devices,Vol.8, No.5, Pages 581-589, 2011.
- P.M. Pilarski, M.R. Dawson, T. Degris, F. Fahimi, J.P. Carey, and R.S. Sutton, “Online Human Training of a Myoelectric Prosthesis Controller via Actor-Critic Reinforcement Learning,” Proc. of the 2011 IEEE International Conference on Rehabilitation Robotics, Zurich, Switzerland, pp. 134-140, June 29–July 1, 2011.