title: A low-power multi-modal body sensor network with application to epileptic seizure monitoring.
abstract: Monitoring patients' physiological signals during their daily activities in the home environment is one of the challenge of the health care. New ultra-low-power wireless technologies could help to achieve this goal. In this paper we present a low-power, multi-modal, wearable sensor platform for the simultaneous recording of activity and physiological data. First we provide a description of the wearable sensor platform, and its characteristics with respect to power consumption. Second we present the preliminary results of the comparison between our sensors and a reference system, on healthy subjects, to test the reliability of the detected physiological (electrocardiogram and respiration) and electromyography signals.
authors.affiliation: imec / Holst Centre, Eindhoven, The Netherlands. marco.altini imec-nl.nl
authors.forename: Marco
authors.initials: M
authors.lastname: Altini
authors.forename: Silvia
authors.initials: S
authors.lastname: Del Din
authors.forename: Shyamal
authors.initials: S
authors.lastname: Patel
authors.forename: Steven
authors.initials: S
authors.lastname: Schachter
authors.forename: Julien
authors.initials: J
authors.lastname: Penders
authors.forename: Paolo
authors.initials: P
authors.lastname: Bonato
mesh_terms: D056044:Actigraphy / Q000295:instrumentation*; D003195:Computer Communication Networks / Q000295:instrumentation*; D003936:Diagnosis, Computer-Assisted / Q000295:instrumentation*; D011211:Electric Power Supplies; D004562:Electrocardiography / Q000295:instrumentation*; D004867:Equipment Design; D019544:Equipment Failure Analysis; D006801:Humans; D018670:Monitoring, Ambulatory / Q000295:instrumentation*; D015203:Reproducibility of Results; D056152:Respiratory Rate; D012640:Seizures / Q000175:diagnosis*; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation