Title: A multi-modal health data fusion and analysis method based on body sensor network

Authors: Lei Wang; Yibo Chen; Zhenying Zhao; Lingxiao Zhao; Jin Li; Cuimin Li

Addresses: Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China ' Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China ' Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China ' Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China ' School of Computer Science and Technology, Harbin Engineering University, Harbin, China ' School of Environmental Science and Engineering, Suzhou University of Science and Technology, Suzhou, China

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.

Keywords: body sensor network; BSN; multi-modal; data fusion; privacy preserving; healthcare service.

DOI: 10.1504/IJSTM.2019.101900

International Journal of Services Technology and Management, 2019 Vol.25 No.5/6, pp.474 - 491

Received: 15 Jul 2017
Accepted: 29 Sep 2017
Published online: 30 Aug 2019 *

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