I am currently a post doctoral researcher at the University of Toronto, working with the Intelligent Assistive Technologies and Systems Lab. In September of 2007 I defended my thesis, which was titled "Machine Perception for Occupational Therapy" and was advised by Chris Atkeson. A copy can be found here. The work applied computer vision and haptic technologies to occupational therapy after stroke. Functional activity among stroke survivors was perceived by low cost devices and used to make automatic upper extremity assessments. The goal was to prototype a system that could make determinations of functional health accurately, continuously and cheaply, and in environments like the home. journal papers Allin, S., Baker, N., Eckel, E. and Ramanan, D. Robust Tracking of the Upper Limb for Functional Stroke Assessment. IEEE Transactions of Neural Systems and Rehabilitation Engineering, 18(5): 542-550, 2010. Allin, S., Eckel, E., Markham, H. and Brewer, B. Recent Trends in the development and evaluation of assistive robotic manipulation devices. Phys Med Rehabil Clin N Am. 21(1):59-77, 2010. Matsuoka, Y., Allin, S., and Klatzky, R. The Tolerance for Visual Feedback Distortions in a Virtual Environment. Physiology & Behavior, 77(4-5):651-655, 2002. [pdf] conference & workshop papers Allin, S. and Eckel, E. Protocol analysis as a tool to explore functional assessment heuristics. Rehabilitation Engineering and Assistive Technology Society of North America (RESNA), Toronto, ON, Canada, 2011 (to appear). Allin, S., Beach, C., Mitz, A. and Mihailidis, A. Video based analysis of standing balance in a community center. IEEE Engineering in Medicine and Biology Society Conference (EMBC), Vancouver, 2008. [pdf] Allin, S., Beach, C., Mitz, A. and Mihailidis, A. Toward low-cost balance assessments in the elderly. Rehabilitation Engineering and Assistive Technology Society of North America (RESNA), Washington, DC, 2008. Allin, S. and Mihailidis, A. Low-cost, automated assessment of sit-to-stand movement in natural environments. Session on Measurements, Signal Processing, and Models for Human Movement and Posture Analysis. European Medical and Biological Engineering Conference (EMBEC), Antwerp, Belgium, 2008. [pdf] Allin, S. and Mihailidis, A. Automated sit-to-stand detection and analysis. AAAI 2008 Fall Symposium on AI in Eldercare: New Solutions to Old Problems, Arlington, VA, 2008. [pdf] Allin, S. and Ramanan, D. Assessment of Post Stroke Functioning Using Machine Vision. IAPR Conference on Machine Vision Applications, Tokyo, May, 2007. [pdf] Allin, S. and Eckel, E. Machine Perception for Occupational Therapy: Toward Prediction of Post-Stroke Functional Scores in the Home. Conference of the Rehabilitation Engineering Society of North America (RESNA), Atlanta, 2006. Allin, S., Galeotti, J., Dailey, S. and Stetten, G. Enhanced Snake-Based Segmentation of Vocal Folds. IEEE International Symposium on Biomedical Imaging, Washington D.C., 2004. [pdf] Allin, S., Bharucha, A., Zimmerman, J., Wilson, D., Roberson, M., Stevens, S., Wactlar, H. and Atkeson, C. Toward the Automatic Assessment of Behavioral Disturbances of Dementia. Workshop on Ubiquitous Computing for Pervasive Healthcare Applications, Ubicomp, Seattle, 2003. [pdf] Bharucha, A., Allin, S. and Stevens, S. Towards Automated Behavior Analysis in the Nursing Home Setting. The International Psychogeriatric Association Eleventh International Congress, Chicago, 2003.[pdf abstract] Allin, S., Matsuoka, Y. and Klatzky, R. Measuring Just Noticeable Differences For Haptic Force Feedback: A Tool for Rehabilitation. IEEE Haptic Interfaces for Virtual and Teleoperator Systems, Orlando, 2002. [pdf]
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