A novel framework for a remote patient monitoring (RPM) system with abnormality detection. Issue 2 (June 2019)

• Record Type: Journal Article
• Authors: Su, Chia-Rong; Hajiyev, Jeyhun; Fu, Changjui James; Kao, Kuo-Chin; Chang, Chih-Hao; Chang, Ching-Ter
• Is Part Of: Health policy and technology. Volume 8:Issue 2(2019)
• Page Start: 157
• Page End: 170
• Publication Date: 2019-06
• Subjects: Remote patient monitoring -- Internet of Things -- Machine-to-machine -- Aging people; Medical policy -- Periodicals; Medical technology -- Periodicals; Medical policy; Medical technology; Health Policy -- Periodicals; Biomedical Technology -- Periodicals; Technology Assessment, Biomedical -- Periodicals; Periodicals; 362.105
• DOI: 10.1016/j.hlpt.2019.05.008
• Languages: English
• ISSNs: 2211-8837

Abstract

Highlights: Automated and effective remote patient monitoring (RPM) system that automatically trigger medical alerts, time for medications, visits to hospital, and social support with specific emphasis on aging people. Use of the IoT 3-tier concept to structure a complete sensor management. Reliability of the proposed framework in complex healthcare processes by taking account the equipment management, security management, messaging and diversification of communication protocols. Abstract: Objective: This research aims to build an effective and automated RPM system based on an information communication technology (ICT) framework that automatically triggers medical alerts, hospital visits, medications, and social support in a timely and precise manner, with specific attention to aging people. The goal of the proposed framework is to construct a safe, flexible, and manageable system containing multi-agent, auto-notice, sensor management, and secure transmission of data to allow an autonomous functioning of RPM. Methods: The literature between 2002 and 2018 that introduces healthcare platforms with the technology of the Internet of things (IoT) is reviewed and compared in compliance with various technical and functional features. Eleven healthcare-based IoT platforms are compared. Eight of them utilize the Representational State Transfer Application Programming Interface (REST API), while ten of them have Message Queue Telemetry Transport (MQTT), seven of them have device management, and nine of them have security control. In addition, Kepware's KEPServerEX communication platform containing up to 250 communication protocols is included. Results: The results confirm that the proposed framework reliably operates within the complex healthcare processes, taking into account the equipment management, security management, messaging and diversification of communication protocols. This study uses the concept of IoT 3-tier through which a complete sensor management mechanism is structured. Moreover, secure data connection protects the patient's privacy. Each sensor provides a distinctive notification to construct flawless authority management. Conclusions: The proposed framework can not only reach the machine-to-machine (M2M) realm, but also provide support in emergency cases.