In this paper, a novel multi-sensor wearable device, called MuSA, is introduced. MuSA aims at integrating in the CARDEA ambient-assisted-living framework: on the one hand, MuSA provides CARDEA with useful ambientintelligence features, such as localization and identification; on the other hand, it may borrow many infrastructural and communication components from the environmental control system, resulting in a less expensive implementation. MuSA exploits on-board sensors and signal processing units for fall, heartbeat and breathing rates detection. At this level too, sharing of part of the circuitry enables power and cost savings. Ubiquitous computing paradigm is followed, carrying out all of the signal processing and decision processes at the wearable node: this makes communication toward supervision levels much less demanding and independent on the actual physical features of the sensors themselves. Tests have been carried out, confirming that the low-cost approach which has been followed still allows for adequate quality of responses. Field test is starting, to evaluate psychological and ergonomic aspect as well. Copyright © 2012 American Scientific Publishers.
Multi Sensor Assistant: A Multisensor Wearable Device for Ambient Assisted Living / Bianchi, Valentina; Grossi, Ferdinando; DE MUNARI, Ilaria; Ciampolini, Paolo. - In: JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS. - ISSN 2156-7018. - 2, Number 1:(2012), pp. 70-75. [10.1166/jmihi.2012.1058]
Multi Sensor Assistant: A Multisensor Wearable Device for Ambient Assisted Living
BIANCHI, Valentina;GROSSI, Ferdinando;DE MUNARI, Ilaria;CIAMPOLINI, Paolo
2012-01-01
Abstract
In this paper, a novel multi-sensor wearable device, called MuSA, is introduced. MuSA aims at integrating in the CARDEA ambient-assisted-living framework: on the one hand, MuSA provides CARDEA with useful ambientintelligence features, such as localization and identification; on the other hand, it may borrow many infrastructural and communication components from the environmental control system, resulting in a less expensive implementation. MuSA exploits on-board sensors and signal processing units for fall, heartbeat and breathing rates detection. At this level too, sharing of part of the circuitry enables power and cost savings. Ubiquitous computing paradigm is followed, carrying out all of the signal processing and decision processes at the wearable node: this makes communication toward supervision levels much less demanding and independent on the actual physical features of the sensors themselves. Tests have been carried out, confirming that the low-cost approach which has been followed still allows for adequate quality of responses. Field test is starting, to evaluate psychological and ergonomic aspect as well. Copyright © 2012 American Scientific Publishers.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.