Monitoring and analysis of vital signs of a patient through a multi-agent application system
Abstract In the medical environment, the clinical study of the most basic vital signs of a patient represents the simplest and most effective way to detect and monitor health problems. There are many diseases that can be diagnosed and controlled through regular monitoring of these medical data. The purpose of this study is to develop a monitoring and tracking system for the various vital signs of a patient. In particular, this work focuses on the design of a multi-agent architecture composed of virtual organizations with capabilities to integrate different medical sensors on an open, low-cost hardware platform. This system integrates hardware and software elements needed for the routine measurement of vital signs, performed by the patient or caregiver without having to go to a medical center.
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Busse, R., Blümel, M., Scheller-Kreinsen, D., & Zentner, a. (2010). Tackling chronic disease in Europe: Strategies, interventions and challenges. Observatory Studies, 20, 111. http://doi.org/10.1558/poth.v0i4.65
Chris Rorden’s Neuropsychology Lab?» Open source multi-channel EEG/ECG/EMG. (n.d.). Retrieved January 20, 2016, from http://www.mccauslandcenter.sc.edu/CRNL/tools/ads1298
Cooking Hacks - Electronic Kits, tutorials and guides for Makers and Education. (n.d.). Retrieved February 8, 2016, from https://www.cooking-hacks.com/
Corchado, J. M., Bajo, J., & Abraham, A. (2008). GerAmi: Improving Healthcare Delivery in Geriatric Residences. IEEE Intelligent Systems, 23(2), 19–25. http://doi.org/10.1109/MIS.2008.27
Fezari, M., Rasras, R., & Emary, I. M. M. El. (2015). Ambulatory Health Monitoring System Using Wireless Sensors Node. Procedia Computer Science, 65, 86–94. http://doi.org/10.1016/j.procs.2015.09.082
Fraile, J. A., De Paz, Y., Bajo, J., De Paz, J. F., & Pérez-Lancho, B. (2013). Context-aware multiagent system: Planning home care tasks. Knowledge and Information Systems. http://doi.org/10.1007/s10115-013-0635-9
Howe, A., & Anderson, J. (2003). Involving patients in medical education. BMJ (Clinical Research Ed.), 327(7410), 326–8. http://doi.org/10.1136/bmj.327.7410.326
Huang, F.-H. (2015). Explore Home Care Needs and Satisfaction for Elderly People with Chronic Disease and their Family Members. Procedia Manufacturing, 3, 173–179. http://doi.org/10.1016/j.promfg.2015.07.123
Knai, C., Brusamento, S., Legido-Quigley, H., Saliba, V., Panteli, D., Turk, E., … Busse, R. (2012). Systematic review of the methodological quality of clinical guideline development for the management of chronic disease in Europe. Health Policy (Amsterdam, Netherlands), 107(2-3), 157–67. http://doi.org/10.1016/j.healthpol.2012.06.004
Koutkias, V. G., Chouvarda, I., & Maglaveras, N. (2003). Multi-agent System Architecture for Heart Failure Management in a Home Care Environment. Computers in Cardiology, 2003, 383–386. http://doi.org/10.1109/CIC.2003.1291172
Preuveneers, D., Berbers, Y., & Joosen, W. (2013). The Future of Mobile E-health Application Development: Exploring HTML5 for Context-aware Diabetes Monitoring. Procedia Computer Science, 21, 351–359. http://doi.org/10.1016/j.procs.2013.09.046
Raspberry Pi - Teach, Learn, and Make with Raspberry Pi. (n.d.). Retrieved January 20, 2016, from https://www.raspberrypi.org/
van den Berg, N., Schumann, M., Kraft, K., & Hoffmann, W. (2012). Telemedicine and telecare for older patients--a systematic review. Maturitas, 73(2), 94–114. http://doi.org/10.1016/j.maturitas.2012.06.010
Varma, D., Shete, V. V, & Somani, S. B. (2015). Development of Home Health Care Self Monitoring System, 4(6), 252–255. http://doi.org/10.17148/IJARCCE.2015.4654
Varshney, U. (2014). Mobile health: Four emerging themes of research. Decision Support Systems, 66, 20–35. http://doi.org/10.1016/j.dss.2014.06.001
Virone, G., Wood, A., Selavo, L., Cao, Q., Fang, L., Doan, T., … Stankovic, J. a. (2006). An Advanced Wireless Sensor Network for Health Monitoring. Transdisciplinary Conference on Distributed Diagnosis and Home Healthcare (D2H2), 2–5. http://doi.org/10.1.1.64.7346
Wimmer, N. J., Scirica, B. M., & Stone, P. H. (2013). The clinical significance of continuous ECG (ambulatory ECG or Holter) monitoring of the ST-segment to evaluate ischemia: a review. Progress in Cardiovascular Diseases, 56(2), 195–202. http://doi.org/10.1016/j.pcad.2013.07.001
Wood, A., Stankovic, J., Virone, G., Selavo, L., He, Z., Cao, Q., … Stoleru, R. (2008). Context-aware wireless sensor networks for assisted living and residential monitoring. IEEE Network, 22(4), 26–33. http://doi.org/10.1109/MNET.2008.4579768
Zato, C., Villarrubia, G., Sánchez, A., Bajo, J., & Manuel Corchado, J. (2013). PANGEA: A new platform for developing virtual organizations of agents. International Journal of Artificial Intelligence, 11(13 A), 93–102. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-84879747021&partnerID=tZOtx3y1
Hernández De La Iglesia, D., Villarrubia González, G., López Barriuso, A., Lozano Murciego, Álvaro, & Revuelta Herrero, J. (2016). Monitoring and analysis of vital signs of a patient through a multi-agent application system. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 4(3), 19–30. https://doi.org/10.14201/ADCAIJ2015431930
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