Body posture/activity detection: path loss characterization for 2.4GHz on-body wireless sensors (Contributo in atti di convegno)

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  • Body posture/activity detection: path loss characterization for 2.4GHz on-body wireless sensors (Contributo in atti di convegno) (literal)
Anno
  • 2009-01-01T00:00:00+01:00 (literal)
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  • Barsocchi P.; Guraliuc A.; Manara G.; Nepa P.; Potortì F.; Serra A. A. (2009)
    Body posture/activity detection: path loss characterization for 2.4GHz on-body wireless sensors
    in IEEE Antennas and Propagation Society International Symposium, North Charleston, South Caroli
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Barsocchi P.; Guraliuc A.; Manara G.; Nepa P.; Potortì F.; Serra A. A. (literal)
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  • Indeed, the RSS indicator is already available in most of low cost transceiver modules designed for WSNs (Smart Dust or Motes). If only a rough classification of body posture/activity is required, additional devices, as for example gyroscopes or accelerometers, could be avoided. The development of the system architecture (number of transceivers and their best placement on the human body) requires accurate path loss models to characterize radio links between a set of transceivers placed on the human body, for a number of body postures and movements [3]-[6]. Therefore, as a first step of the above mentioned algorithm development activity, on-body path loss properties are being studied. Both numerical and experimental results will be presented in this paper. The analysis of the path loss as a function of the distance between two on-body antennas is performed at 2.4 GHz and results are shown for some radio links. (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note
  • In: APSURSI '09 - IEEE Antennas and Propagation Society International Symposium (North Charleston, South Carolina, 1-5 June 2009). Proceedings, pp. 128 - 131. IEEE, 2009. (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#descrizioneSinteticaDelProdotto
  • ABSTRACT: On-body wireless sensor networks (WSNs) are gaining an increasing interest in medical, military as well as entertainment applications. Wireless transceiver modules placed on the body and combined with actuators/sensors can communicate between them and with any other node located in the surrounding environment, without any human body movement constraint with respect to wired connections. A further application of the above on-body WSNs could be in the framework of the human body posture and activity detection. Recognizing people's activities is a key issue in Assisted Living (AL) applications, where it can be required to monitor and detect abnormalities for elderly care, or rate how a person performs routine activities. As an example, in the medical field the patient recovery and rehabilitation can be remotely monitored, controlled and recorded without the presence of a technician [1]. Likewise, in military applications the Soldier Assist System (SAS) that provides recognition of soldier activities can be improved by body activity detection networks [2]. In this context the authors are involved in a research activity aimed at developing algorithms for body posture/activity classification, which are based on RSS (Received Signal Strength) exploiting. (literal)
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  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • CNR-ISTI, Pisa, Dept. of Information Engineering, University of Pisa (literal)
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  • Body posture/activity detection: path loss characterization for 2.4GHz on-body wireless sensors (literal)
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