An intelligent information forwarder for healthcare big data systems with distributed wearable sensors

Jiang, Ping; Winkley, Jonathan; Zhao, Can; Munnoch, Robert; Min, Geyong; Yang, Laurence Tianruo

Abstract

© 2016 IEEE. An increasing number of the elderly population wish to live an independent lifestyle, rather than rely on intrusive care programmes. A big data solution is presented using wearable sensors capable of carrying out continuous monitoring of the elderly, alerting the relevant caregivers when necessary and forwarding pertinent information to a big data system for analysis. A challenge for such a solution is the development of context-awareness through the multidimensional, dynamic and nonlinear sensor readings that have a weak correlation with observable human behaviours and health conditions. To address this challenge, a wearable sensor system with an intelligent data forwarder is discussed in this paper. The forwarder adopts a Hidden Markov Model for human behaviour recognition. Locality sensitive hashing is proposed as an efficient mechanism to learn sensor patterns. A prototype solution is implemented to monitor health conditions of dispersed users. It is shown that the intelligent forwarders can provide the remote sensors with context-awareness. They transmit only important information to the big data server for analytics when certain behaviours happen and avoid overwhelming communication and data storage. The system functions unobtrusively, whilst giving the users peace of mind in the knowledge that their safety is being monitored and analysed.

Citation

Jiang, P., Winkley, J., Zhao, C., Munnoch, R., Min, G., & Yang, L. T. (2016). An intelligent information forwarder for healthcare big data systems with distributed wearable sensors. IEEE systems journal, 10(3), 1147-1159. https://doi.org/10.1109/JSYST.2014.2308324

• Journal Article Type: Article
• Acceptance Date: Feb 17, 2014
• Online Publication Date: Mar 19, 2014
• Publication Date: Sep 1, 2016
• Deposit Date: May 19, 2015
• Publicly Available Date: May 19, 2015
• Journal: IEEE systems journal
• Print ISSN: 1932-8184
• Electronic ISSN: 1937-9234
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 10
• Issue: 3
• Pages: 1147-1159
• DOI: https://doi.org/10.1109/JSYST.2014.2308324
• Keywords: Ambient assisted living, Behaviour monitoring, Hidden Markov model, Locality sensitive hashing, Wearable sensors, Big data
• Public URL: https://hull-repository.worktribe.com/output/373933
• Publisher URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6775278
• Additional Information: © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.