TY - JOUR PY - 2011// TI - Development of a platform to combine sensor networks and home robots to improve fall detection in the home environment JO - Conference proceedings - IEEE engineering in medicine and biology society A1 - Della Toffola, Luca A1 - Patel, Shyamal A1 - Chen, Bor-Rong A1 - Ozsecen, Yalgin M. A1 - Puiatti, Alessandro A1 - Bonato, Paolo SP - 5331 EP - 5334 VL - 2011 IS - N2 - Over the last decade, significant progress has been made in the development of wearable sensor systems for continuous health monitoring in the home and community settings. One of the main areas of application for these wearable sensor systems is in detecting emergency events such as falls. Wearable sensors like accelerometers are increasingly being used to monitor daily activities of individuals at a risk of falls, detect emergency events and send alerts to caregivers. However, such systems tend to have a high rate of false alarms, which leads to low compliance levels. Home robots can enable caregivers with the ability to quickly make an assessment and intervene if an emergency event is detected. This can provide an additional layer for detecting false positives, which can lead to improve compliance. In this paper, we present preliminary work on the development of a fall detection system based on a combination sensor networks and home robots. The sensor network architecture comprises of body worn sensors and ambient sensors distributed in the environment. We present the software architecture and conceptual design home robotic platform. We also perform preliminary characterization of the sensor network in terms of latencies and battery lifetime.

Language: en

LA - en SN - 1557-170X UR - http://dx.doi.org/10.1109/IEMBS.2011.6091319 ID - ref1 ER -