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The functional use of the upper limbs is one of the top recovery priorities of individuals with cervical spinal cord injury (cSCI). Wearable cameras and computer vision methods have recently emerged as technological solutions to extract objective outcome measures that reflect hand function in a natural context, overcoming the limitations of accelerometer-based devices. However, previous studies conducted in a highly controlled environment may not be indicative of the actual hand use of individuals with cSCI living in the community. Thus, the validation of this technology in a home environment is necessary. This presentation will focus on the first results obtained in an uncontrolled environment, where participants with cSCI recorded videos at home during their normal daily activities. Moreover, particular attention will be given to the pitfalls of using this technology at home.


Dr. Bandini received his PhD in Bioengineering from the University of Bologna (Italy) in 2016. He has been a postdoctoral research fellow at KITE @ University Health Network since September 2016, working with the Communication and NET teams. His research aims to develop novel and objective tools for the assessment and rehabilitation of motor signs associated with neurological disorders (spinal cord injury, stroke, amyotrophic lateral sclerosis, and Parkinson’s disease), by using computer vision and machine learning techniques. In the last three years, he has been awarded two postdoctoral grants (Heart and Stroke Foundation – Canadian Partnership for Stroke Recovery and Age Well NCE) for his research on video-based face tracking in patients post-stroke.