Power- and delay-awareness of health telemonitoring services: the mobihealth system case study

Authors:
Katarzyna Wac;Mortaza S. Bargh;Bert-Jan F. Van Beijnum;Richard G. A. Bults;Pravin Pawar;Arjan Peddemors
Affiliations:
Systems Department at University of Geneva, Switzerland and Computer Science Department at University of Twente, the Netherlands;Telematica Instituut, the Netherlands;Computer Science Department at University of Twente, the Netherlands;Computer Science Department at University of Twente, the Netherlands and MobiHealth BV, the Netherlands;Computer Science Department at University of Twente, the Netherlands;Telematica Instituut, the Netherlands
Venue:
IEEE Journal on Selected Areas in Communications - Special issue on wireless and pervasive communications for healthcare
Year:
2009

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Abstract

Emerging healthcare applications rely on personal mobile devices to monitor and transmit patient vital signs to hospital-backend servers for further analysis. However, these devices have limited resources that must be used optimally in order to meet the application user requirements (e.g. safety, usability, reliability, performance). This paper reports on a case study of a Chronic Obstructive Pulmonary Disease telemonitoring application delivered by the MobiHealth system. This system relies on a commercial mobile device with multiple (wireless) Network Interfaces (NI). Our study focuses on how NI activation strategies affect the application end-to-end data delay (important in case of an emergency situation) and the energy consumption of the device (important for device sustainability while a patient is mobile). Our results show the trade-off between end-to-end delay and battery life-time achieved by various NI activation strategies, in combination with application-data flow adaptation for real-time and near real-time data transmission. For a given mobile device, our study shows an increase in battery life-time of 40- 90 %, traded against higher end-to-end data delay. The insights of our studies can be used for application-data flow adaptation aiming to increase battery life-time and device sustainability for mobile patients; which effectively increases the healthcare application usability.