Neural Network for On-bed Movement Pattern Recognition

• Main Authors: Chawakorn Sri-Ngernyuang, Prakarnkiat Youngkong, Duangruedee Lasuka, Kitti Thamrongaphichartkul, Watcharapong Pingmuang
• Format: Conference Proceeding
• Published: 2019
• Subjects: Computer Science; Engineering; Physics and Astronomy
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85062058489&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/63628
• Institution: Chiang Mai University

© 2018 IEEE. One of the critical issues in hospitals is the injury from falling out of patient bed. Some of these cases lead to death. Considering this type of incident, a monitoring and alarming system called NEFs (Never Ever Falls) is introduced to prevent patients from falling out of the bed. In this paper, on-bed pattern recognition is developed by applying Neural Network Pattern Recognition from MATLAB. In the experiment, data from 6 persons in 5 different on-bed patterns (Sitting inside the bed, Supine, Lateral on the left, Lateral on the right and sitting at bedsides and corners) is recorded. According to the confusion matrix, training and validation confusion tables show 99.5% and 89.1% accuracy, respectively.