This project involves the design and implementation of a non-invasive monitoring and alerting system for people with advanced Multiple Sclerosis (MS) who use powered wheelchair because of severe mobility impairment. Several sensors are deployed on an electric wheelchair acquiring vital signs, activity level and ambient information. The collected data will be used to design algorithms to generate alarms and recommendations for residents and caregivers. These alarms and recommendations will be related to vital signs, low mobility problems and heat exposure. For instance, an algorithm was implemented based on the pressure sensors and the accelerometer data to detect pressure relief behavior and the subject’s activity.

I will be analyzing the data that has been collected from the monitoring platform and develop an algorithm generating alarms and recommendation. The data includes Ballistocardiogram (BCG), pressure signals, accelerometers and ambient conditions (temperature and humidity). Based on these signals, we are planning to compute vital signs, and mobility (activity) level. Further, I will take part in building and deploying a central monitoring station for caregivers.