2020/09/01 by Von Ralph Dane Marquez Herbuela, Herbuela, Von Ralph Dane Marquez, Tomonori Karita +11
Computer Science · Health Professions · Medicine · Neuroscience · #Assistive Technology in Communication and Mobility #Autism Spectrum Disorder Research #Cerebral Palsy and Movement Disorders #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #cs.HC
paper · pdf · doi:10.48550/arxiv.2009.00260
arxiv created 2020/09/01 · openalex publication_date 2020/09/01 · arxiv updated 2020/09/02 · openalex created_date 2020/09/11 · openalex updated_date 2026/07/28
Children with profound intellectual and multiple disabilities or severe motor and intellectual disabilities only communicate through movements, vocalizations, body postures, muscle tensions, or facial expressions on a pre- or protosymbolic level. Yet, to the best of our knowledge, hardly any system has been developed to interpret their expressive behaviors. This paper describes the design, development, and testing of ChildSIDE in collecting behaviors of children and transmitting location and environmental data to the database. The movements associated with each behavior were also identified for future system development. ChildSIDE app was pilot tested among purposively recruited child-caregiver dyads. ChildSIDE was more likely to collect correct behavior data than paper-based method and it had >93% in detecting and transmitting location and environment data except for iBeacon data. Behaviors were manifested mainly through hand and body movements and vocalizations.