Arias Diego E, Pino Esteban J, Aqueveque Pablo, Curtis Dorothy W
Department of Electrical Engineering, Universidad de Concepción, Concepción, Chile;
Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA.
AMIA Annu Symp Proc. 2013 Nov 16;2013:61-8. eCollection 2013.
This paper reports on a data collection study in a clinical environment to evaluate a new non-invasive monitoring system for people with advanced Multiple Sclerosis (MS) who use powered wheelchairs. The proposed system can acquire respiration and heart activity from ballistocardiogram (BCG) signals, seat and back pressure changes, wheelchair tilt angle, ambient temperature and relative humidity. The data was collected at The Boston Home (TBH), a specialized care residence for adults with advanced MS. 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. We present different cases where it is possible to illustrate the type of information acquired by our system and the possible alarms we will generate.