Marge Coahran

Toronto Rehabilitation Institute, University Health Network

Papers

Total Citations

H-Index

About

Marge Coahran is a researcher whose work sits at the intersection of rehabilitation science and technology, with a primary focus on stroke recovery and upper limb function. Her key contributions lie in developing and validating novel methods to assess and improve rehabilitation outcomes, particularly through the use of robotic and sensor-based technologies. Coahran’s most cited work, "The Toronto Rehab Stroke Pose Dataset to Detect Compensation During Stroke Rehabilitation Therapy" (2017, 49 citations), provides a critical resource for identifying compensatory movements—a major barrier to effective therapy—by using motion capture data. This dataset has become a foundational tool for researchers aiming to automate the detection of maladaptive movement patterns. In her subsequent study, "Smallest Real Differences for Robotic Measures of Upper Extremity Function After Stroke" (2018, 10 citations), Coahran tackled the practical challenge of using robotic assessments to track patient progress over short timeframes, establishing key measurement thresholds that guide clinicians in adjusting therapy. Her work is notable for bridging engineering precision with clinical relevance, directly impacting how stroke rehabilitation is monitored and personalized. Coahran’s research continues to empower therapists and engineers to build more responsive, data-driven rehabilitation tools.