Rachael L'Orsa completed two degrees at the University of British Columbia: a Bachelor of Applied Science in Mechanical Engineering (2010) and a Bachelor of Arts in French and Spanish (with Computer Science minor, 2011). She received a Master of Science in Electrical Engineering from the University of Calgary (2016), and is currently enrolled in their PhD program for Electrical Engineering. She maintains a Primary Care Paramedic license in British Columbia and is very active in youth robotics mentorship.
Her research focus is control systems, specifically for the Robot-Assisted Space Telemetry (RAST) system proposed by the Project neuroArm team to provide the International Space Station with critical medical interventions via a teleoperated surgical robot with some semi-autonomous capabilities.
Student Innovation Challenge on Implementing Haptics in Virtual Reality Environment presented at the IEEE World Haptics Conference, Tokyo, Japan, July 2019, Maria Paola Forte, Rachael L'Orsa, Mayumi Mohan, and Saekwang Nam contributed equally to this publication (misc)
Dysgraphia is a neurological disorder characterized by writing disabilities that affects between 7% and 15% of children. It presents itself in the form of unfinished letters, letter distortion, inconsistent letter size, letter collision, etc. Traditional therapeutic exercises require continuous assistance from teachers or occupational therapists. Autonomous partial or full haptic guidance can produce positive results, but children often become bored with the repetitive nature of such activities. Conversely, virtual rehabilitation with video games represents a new frontier for occupational therapy due to its highly motivational nature. Virtual reality (VR) adds an element of novelty and entertainment to therapy, thus motivating players to perform exercises more regularly. We propose leveraging the HTC VIVE Pro and the EXOS Wrist DK2 to create an immersive spellcasting “exergame” (exercise game) that helps motivate children with dysgraphia to improve writing fluency.
Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to use this understanding to design future systems