International Journal of Information, Communication Technology and Applications International Journal of Information, Communication Technology and Applications, ISSN 2205-0930, Volume 2 Number 1 22 September 2016 Copyright © 2016 108 Data ProcessiŶg of Physiological SeŶsor Data aŶd Alarŵ DeterŵiŶatioŶ UtilisiŶg Activity RecogŶitioŶ James Jin Kang School of Information Technology Deakin University Burwood Australia jkang@deakin.edu.au Tom H Luan School of Information Technology Deakin University Burwood Australia tom.luan@deakin.edu.au Henry Larkin School of Information Technology Deakin University Burwood Australia henry.larkin@deakin.edu.au Abstract: 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 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. Introduction The rapid prevalence of wearables and body sensors allows additional services to applications of human activity recognition technologies as seen in Figure 1. AR has become an emerging