THE-MUSS: Mobile U-Health Service System

In this paper, we introduce a mobile u-health service system called THE-MUSS. THE-MUSS supports the development and running of u-health services with functions, modules, and facilities that are commonly required for various mobile u-health services. Aiming to achieve reusability and evolvability design goals, basic modules to support bio-signal capturing, processing, analysis, diagnosis, and feedback are developed and stacked in the layered architecture of THE-MUSS. A U-health service platform, design tool, portal, and matrix-based disease group identification method are the major components constituting the THE-MUSS architecture. We confirmed that THE-MUSS is practically useful for mobile u-health services by developing mobile stress and weight management services on THE-MUSS. The more u-health services are developed in THE-MUSS, the better services it can provide in the future.

[1]  R. Istepanian,et al.  M-Health: Emerging Mobile Health Systems , 2006 .

[2]  Ramasamy Uthurusamy,et al.  Data mining and knowledge discovery in databases , 1996, CACM.

[3]  Karl E. Wiegers,et al.  Software Requirements , 1999 .

[4]  Emil Jovanov,et al.  Guest Editorial Introduction to the Special Section on M-Health: Beyond Seamless Mobility and Global Wireless Health-Care Connectivity , 2004, IEEE Transactions on Information Technology in Biomedicine.

[5]  K. Koh,et al.  Development of the Stress Response Inventory and Its Application in Clinical Practice , 2001, Psychosomatic medicine.

[6]  Frank Leymann,et al.  Web services and business process management , 2002, IBM Syst. J..

[7]  J.M. Quero,et al.  Health Care Applications Based on Mobile Phone Centric Smart Sensor Network , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[8]  Dongsoo Han,et al.  WebVine Suite: A Web Services Based BPMS , 2006, APWeb.

[9]  Christer Carlsson,et al.  Past, present, and future of decision support technology , 2002, Decis. Support Syst..

[10]  Michael Uschold,et al.  Ontologies: principles, methods and applications , 1996, The Knowledge Engineering Review.

[11]  Dong-Soo Han,et al.  PreSPI: a domain combination based prediction system for protein-protein interaction. , 2004, Nucleic acids research.

[12]  IstepanianR. S.H.,et al.  Guest Editorial Introduction to the Special Section on M-Health , 2004 .

[13]  In-Young Ko,et al.  An Evolving Mobile E-Health Service Platform , 2007, 2007 Digest of Technical Papers International Conference on Consumer Electronics.

[14]  Sankar K. Pal,et al.  Data mining in soft computing framework: a survey , 2002, IEEE Trans. Neural Networks.

[15]  Dongsoo Han,et al.  A BPM-Based Mobile U-Health Service Framework , 2008, HEALTHINF.

[16]  Howard Smith,et al.  Business Process Management: The Third Wave , 2003 .

[17]  David G. Stork,et al.  Pattern Classification , 1973 .

[18]  Finn Verner Jensen,et al.  Introduction to Bayesian Networks , 2008, Innovations in Bayesian Networks.

[19]  Mohd Fadlee A. Rasid,et al.  Bluetooth telemedicine Processor for multichannel biomedical signal transmission via mobile cellular networks , 2005, IEEE Transactions on Information Technology in Biomedicine.

[20]  Minkyu Lee,et al.  A Probability-Based Prediction Framework for Stress Identification , 2007, 2007 9th International Conference on e-Health Networking, Application and Services.

[21]  Florian Alexander Ruths Principles and Practice of Stress Management (3rd edn) , 2009, British Journal of Psychiatry.