Abstract
Novel assistive technologies for neurorehabilitation effective for children are highly demanded and the need for paediatric research is essential, given the lack of viable access technologies for children and youth with severe and multiple disabilities. These technologies are especially pertinent to children who are not capable of using speech to communicate or who are limited in motor skills and require mobility aids. Signal processing, computer vision, artificial intelligence, and neural engineering can represent the perfect set of instruments to support children with severe disabilities and their caregivers during daily activities and therapeutic programs. In this seminar, we will explore the fascinating world of paediatric rehabilitation research, talking about how customizable access technologies can give voice to the voiceless using human-machine interaction and advanced computer vision techniques. From wearable sensors and virtual music instruments that can assist motor rehabilitation to vocal cord transmitters, speech analysis and brain-computer interfaces, these innovations have had a profound impact on families, caregivers, and health care providers. Assistive technology can be translated to in-school and at-home training protocols, showing how we can transform disability to ability, developing personalized technologies and ad hoc home rehabilitation techniques.
About the speaker
Silvia Orlandi is currently a Junior Assistant Professor at the Department of Electrical, Electronic, and Information Engineering “Guglielmo Marconi” (DEI) of the Alma Mater Studiorum, University of Bologna. She got a PhD in bioengineering from the University of Bologna in 2015 and she worked as a postdoctoral fellow at Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Canada’s largest children’s rehabilitation hospital. Her research mainly focuses on developing multi-modal intelligent technologies, methods, and models for motor and cognitive neurorehabilitation through artificial intelligence, biomedical signal processing, computer vision, and rehabilitation engineering techniques.