Computer vision for detection of body expressions of children with cerebral palsy
Cristhian Rosales, Luis Jácome, Jorge Enrique Carrión González, Carlos Jaramillo, Mario Palma · 2017 IEEE Second Ecuador Technical Chapters Meeting (ETCM) · 2017
This article is the result of an investigation to improve the communication with a case study that suffers Cerebral Palsy through the use of Computer Vision. At present, there is a 15% of the world's population that suffers some form of disability which prevents them from complying with the common activities of a normal person in a social environment. The technology can help to facilitate the implementation of processes that support people with special needs to improve their lifestyle; in this project the main objective is to improve the communication with the patient in order to facilitate the patient care. For conducting the investigation it was necessary the development of a prototype that detects body expressions using the OpenCV library with the Python programming language. The results are promising because the computer vision system is able to detect with high accuracy the following body patterns: headache 77%, happiness 75%, hunger 82%, fear 88% and recreation 77%. Finally, when a body pattern is detected it is communicated to the patient's caregiver through a mobile application.