Issues in Implementing a Knowledge-based ECG Analyzer for Personal Mobile Health Monitoring

• Published in: 2006 International Conference of the IEEE Engineering in Medicine and Biology Society Vol. 2006; pp. 6265 - 6268
• Main Authors: Goh, K.W., Kim, E., Lavanya, J., Kim, Y., Soh, C.B.
• Format: Conference Proceeding Journal Article
• Language: English
• Published: United States IEEE 2006
• Subjects: Arrhythmias, Cardiac - diagnosis; Broadband communication; Computer Communication Networks; Computer Simulation; Computers, Handheld; Diagnosis, Computer-Assisted - methods; Electrocardiography; Electrocardiography - instrumentation; Electrocardiography - methods; Electrocardiography, Ambulatory - instrumentation; Electrocardiography, Ambulatory - methods; Equipment Design; Health information management; Humans; Mobile communication; Monitoring, Ambulatory - instrumentation; Monitoring, Ambulatory - methods; Monitoring, Physiologic - methods; Movement; Patient monitoring; Performance analysis; Sensor systems; Software; Technology management; Telemedicine - methods; Wireless communication; Wireless sensor networks
• ISBN: 9781424400324; 1424400325
• ISSN: 1557-170X
• DOI: 10.1109/IEMBS.2006.259632

Advances in sensor technology, personal mobile devices, and wireless broadband communications are enabling the development of an integrated personal mobile health monitoring system that can provide patients with a useful tool to assess their own health and manage their personal health information anytime and anywhere. Personal mobile devices, such as PDAs and mobile phones, are becoming more powerful integrated information management tools and play a major role in many people's lives. We focus on designing a health-monitoring system for people who suffer from cardiac arrhythmias. We have developed computer simulation models to evaluate the performance of appropriate electrocardiogram (ECG) analysis techniques that can be implemented on personal mobile devices. This paper describes an ECG analyzer to perform ECG beat and episode detection and classification. We have obtained promising preliminary results from our study. Also, we discuss several key considerations when implementing a mobile health monitoring solution. The mobile ECG analyzer would become a front-end patient health data acquisition module, which is connected to the Personal Health Information Management System (PHIMS) for data repository