@inproceedings{2020_HCII_ComputerVisionOnWheelchairs,
   author = {Bai, Lang and Hu, Jun},
   title = {Computer Vision on Wheelchairs: Detecting Sleeping Behavior of People with Intellectual Disabilities},
   booktitle = {HCII 2020: Distributed, Ambient and Pervasive Interactions},
   address = {Cham},
   publisher = {Springer International Publishing},
   pages = {493–504},
   abstract = {There have been few products or research efforts on designing for people with intellectual disabilities. The caretaking companies have no enough caretakers to keep an eye on the clients with intellectual disabilities, who are suffering from circadian rhythm disorder. We report on the design of a system to detect the sleeping behavior of people with intellectual disabilities in the daytime. The system utilizes an inexpensive 2D camera with computer vision techniques to track whether a user is falling asleep. The system wakes up the clients gradually in several steps when a long-time sleeping is detected. Our study explores taking eye aspect ratio, head orientation as inputs, and a support vector machine to managing complex situations in real life.},
   DOI = {10.1007/978-3-030-50344-4_35},
   PDF = {http://www.drhu.eu/publications/2020_HCII_ComputerVisionOnWheelchairs.pdf},
   year = {2020}
}