Human movements which are rich, and complex are essential for every aspect of human life and can be used to understand many conditions and behaviours. In health care human movement is analysed to assess, diagnose, monitor, and treat many conditions such as childhood development, stroke, cerebral palsy, and Parkinson’s disease. However current techniques of human movement assessment often rely on costly and difficult setups. As a result, these are often not used in clinical settings and alternative subjective and low accuracy methods are used instead. Computer vision is technology that applies algorithms to visual data such as video and photos to understand visual information in a manner similar to a person. They have the potential to overcome the limitations of current movement analysis methods while providing clinically accessible tools to improve accuracy and provide insights not visible to the human eye.
Described as vibrant and vivacious Rahm has a passion for Technology and how it can be used to improve health. He has worked as paediatric physiotherapist for over 10 years where he incorporated consumer technology to improve the outcomes for children and their family. Rahm has worked as a physiotherapist in many other areas of health including ICU, acute hospital care, rehabilitation, sports medicine, community, and aged care. He is interested in computer vision and immersive virtual reality and continues to explore, understand, and validate their use in health care with the hope of making health services more accessible to every individual.
2021 - Current PhD Candidate, School of Optometry and Vision Science, UNSW Sydney, NSW Australia
2020 Master of Health Technology and Innovation (with High Honours), University of Sydney – Sydney, NSW Australia
2010 Bachelor of Physiotherapy, Charles Sturt University - Albury, NSW Australia