A Study of Cloud Computing Based Context-Aware Healthcare App

Abstract:

This study adopts usability evaluation method for evaluating the user's acceptance of a Cloud Computing based context-aware Personal Healthcare Records (PHR). The system features include basic phys-iological measurement, life style management, etc. It exploits the so called “polling scheme for Bluetooth” and multi-device automatically reading physiological measurements to achieve the efficacy of context-aware. Moreover, the entire personal health records can be transmitted synchronously into a Cloud system in real time. To evaluate the usability, we conduct an experimental test on the prototype system. We recruit 100 par-ticipants for the evaluation. The study results show that the participants have high rating of positive response to the system usability. Keywords: health care, personal health records, context-aware, cloud-computing, usability .

• Periodical: Applied Mechanics and Materials (Volumes 764-765)
• Pages: 801-805
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.764-765.801
• Online since: May 2015
• Authors: Shu Lin Wang*, Mu Hsing Kuo, Hung Ming Chen, Andre Kushniruk, Elizabeth Borycki
• Keywords: Cloud-Computing, Context-Aware, Health Care, Personal Health Records, Usability

References

[1] L. Lee, J. Ha, K. Chung, & Y. Chang: Ubiquitous healthcare service using Zigbee and mobile phone for elderly patients. International journal of medical informatics Vol. 78 (2009), p.193–198.

DOI: 10.1016/j.ijmedinf.2008.07.005

[2] J.G. Song, S. Jung, B. H. Kang, D.J. Hwang, & S. Kim: Design of context aware middle- ware for mobile healthcare services. Journal of the Chinese Institute of Engineers Vol. 35(5) (2012), pp.535-545.

DOI: 10.1080/02533839.2012.679063

[3] S.C. Wangberg, E. Arsand, E. & N. Andersson: Diabetes education via mobile text messaging. J Telemed Telecare Vol. 12(l) (2006), p.55–56.

DOI: 10.1258/135763306777978515

[4] W. Brown, P.Y. Yenc, M. Rojas, & R. Schnall: Assessment of the Health IT Usability Evaluation Model (Health-ITUEM) for evaluating mobile health (mHealth) technology. Journal of Biomedical Informatics Vol. 46(6) (2013), pp.1080-1087.

DOI: 10.1016/j.jbi.2013.08.001

[5] P. Mell, & T. Grance: The NIST definition of cloud computing. Communication ACM Vol. 53(6) (2010) p.50.

[6] A.M. Kuo: Opportunities and Challenges of Cloud Computing to Improve Health Care Services. J Med Internet Res. Vol. 13(3) (2011), p. e67.

DOI: 10.2196/jmir.1867

[7] E. AbuKhousa, & H.A. Najati: UAE-IHC: Steps towards Integrated E-Health Environment in UAE. In Proceedings of the 4th e-Health and Environment Conference in the Middle East, Dubai, UAE, February (2012).

[8] E. Ferro & P. Francesco: Bluetooth and Wi-Fi wireless protocols: a survey and a comparison, Wireless Communications. IEEE Vol. 12(1) (2005), pp.12-26.

DOI: 10.1109/mwc.2005.1404569

[9] R.L. Oliver: A cognitive model for the antecedents and consequences of satisfaction. Journal of Marketing Research Vol. 17(4) (1980), p.460–469.

[10] J.Y.L. Thong, S.J. Hong, & K.Y. Tam: The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance. International Journal of Hu- man-Computer Studies Vol. 64(9) (2006), P. 799–810.

DOI: 10.1016/j.ijhcs.2006.05.001

[11] R.E. Anderson, & S.S. Srinivasan: E-satisfaction and e-loyalty: a contingency frame- work. Psychology and Marketing Vol. 20(2) (2013), p.123–138.

[12] P. Martínez, & I. Rodríguez del Bosque: CSR and customer loyalty: The roles of trust, customer identification with the company and satisfaction. International Journal of Hospitality Management Vol. 35(2013), p.89–99.

DOI: 10.1016/j.ijhm.2013.05.009