@inproceedings{2f03c2e919ed4795b78ab27d49e5afac,
title = "Fault Detection for Medical Body Sensor Networks under Bayesian Network Model",
abstract = "We propose a Bayesian network based method for the fault diagnosis problem of medical body sensor networks used to collect physiological signs to monitor the health of patients, We formalize a Bayesian network to describe the body sensor network considering both the spatial and temporal correlation in measurements at different sensors, Then we give the theoretical analysis of the fault detection, false alarm of this method, and the error probability after executing the fault diagnosis algorithm, Finally, Experiments carried out on synthetic medical datasets by injecting faults into real medical datasets show that the simulation performance matches the theoretical analysis closely, and the proposed approach possesses a good detection accuracy with a low false alarm rate.",
keywords = "Bayesian network, body sensor networks, fault diagnosis",
author = "Haibin Zhang and Jiajia Liu and Rong Li",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 11th International Conference on Mobile Ad-Hoc and Sensor Networks, MSN 2015 ; Conference date: 16-12-2015 Through 18-12-2015",
year = "2016",
month = feb,
day = "26",
doi = "10.1109/MSN.2015.21",
language = "英语",
series = "Proceedings - 11th International Conference on Mobile Ad-Hoc and Sensor Networks, MSN 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "37--42",
booktitle = "Proceedings - 11th International Conference on Mobile Ad-Hoc and Sensor Networks, MSN 2015",
}