A multi-modal health data fusion and analysis method based on body sensor network Online publication date: Fri, 30-Aug-2019
by Lei Wang; Yibo Chen; Zhenying Zhao; Lingxiao Zhao; Jin Li; Cuimin Li
International Journal of Services Technology and Management (IJSTM), Vol. 25, No. 5/6, 2019
Abstract: As an important branch of wireless sensor network (WSN) in biomedical field, body sensor network (BSN) could remotely monitor a variety of human health data in real time by means of energy-saving and high-accuracy sensor technology. We proposed a multi-modal health data fusion and analysis method based on the data collected from BSN. Single-modal Holter monitoring and multi-modal health monitoring were performed on 60 patients with confirmed heart disease and proved that the proposed method could effectively improve the detection rate of asymptomatic myocardial ischemia and provide a new auxiliary judgment method for clinical application. Aiming at the requirement of privacy preserving in the data fusion process of wireless body sensor network, a new SMART-RR algorithm was proposed. Simulation results showed that MART-RR was an energy-saving privacy preserving data fusion algorithm with small data communications, high privacy protection and accuracy.
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