Data Processing of Physiological Sensor Data and Alarm Determination Utilising Activity Recognition

  • James Jin Kang Deakin University
  • Tom Luan Deakin University
  • Henry Larkin Deakin University
Keywords: Body sensors, WBAN, IoT, Activity Recognition, Inference


Current physiological sensors are passive and transmit sensed data to Monitoring centre (MC) through wireless body area network (WBAN) without processing data intelligently. We propose a solution to discern data requestors for prioritising and inferring data to reduce transactions and conserve battery power, which is important requirements of mobile health (mHealth). However, there is a problem for alarm determination without knowing the activity of the user. For example, 170 beats per minute of heart rate can be normal during exercising, however an alarm should be raised if this figure has been sensed during sleep. To solve this problem, we suggest utilising the existing activity recognition (AR) applications. Most of health related wearable devices include accelerometers along with physiological sensors. This paper presents a novel approach and solution to utilise physiological data with AR so that they can provide not only improved and efficient services such as alarm determination but also provide richer health information which may provide content for new markets as well as additional application services such as converged mobile health with aged care services. This has been verified by experimented tests and examples of using vital signs such as heart pulse rate, respiration rate and body temperature with a demonstrated outcome of AR accelerometer sensors integrated with an Android app.

Author Biography

James Jin Kang, Deakin University

James Kang is currently a Ph.D. candidate  at the School of Information Technology in Deakin University, Australia with interests in mHealth networks, IoT, big data and Health Informatics. He has worked in the ICT industry for over 20 years in roles such as solutions design, testing, deployment, operation and technical support. He has specialised in Intelligent Networks for wired and mobile networks during the earlier stages of his career, and later worked on IP, IMS, NGN and VoIP technologies. James has experience with major solutions and service providers such as LG, Telecom NZ, Vodafone, Siemens, Telstra, Alcatel-Lucent and NBN Co. He has recently went to Africa as a volunteer IT advisor sponsored by the Australian government (DFAT) to help NGOs.


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