Smart Embedded Medical Diagnosis using Beaglebone Black and Arduino
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2014 by IJETT Journal|
|Year of Publication : 2014|
|Authors : Ch Srikanth , D S Pradeep M ,Sreeram Charan K
Ch Srikanth , D S Pradeep M ,Sreeram Charan K."Smart Embedded Medical Diagnosis using Beaglebone Black and Arduino", International Journal of Engineering Trends and Technology(IJETT), 8(1),43-48 February 2014. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
Now a day’s healthcare industry is to provide better healthcare to people anytime and anywhere in the world in a more economic and patient friendly manner. The Medical Diagnosis Shield allows Arduino and Beaglebone Black users to perform biometric and medical applications where body monitoring is needed by using 9 different sensors. This information can be used to monitor in real time the state of a patient or to get sensitive data in order to be subsequently analysed for medical diagnosis. Biometric information gathered can be wirelessly sent using any of the 6 connectivity options available: Bluetooth, 802.15.4, ZigBee, WI-Fi, 3G and GPRS depending on the application.
 G.Z.Yang,Body Sensor Networks, 1st ed. London: Springer-Verlag, 2006, pp. 1–275.
 P.S.Pandian,K.Mohanavelu,K.P.Safeer,T.M.Kotresh,D.T.Shakunthala, P. Gopal, and V. C. Padaki, “Smart vest: Wearable multiparameter remote physiological monitoring system,” Med. Eng. Phys., vol. 30, no. 4, pp. 466–477, May 2008.
 T. Yilmaz, R. Foster, and Y. Hao, “Detecting vital signs with wearable wireless sensors,” Sensors, vol. 10, no. 12, pp. 10837–10862, Dec. 2010.
 B. Massot, N. Baltenneck, C. Gehin, A. Dittmar, and E. McAdams, “EmoSense: An ambulatory device for the assessment of ANS activityapplication in the objective evaluation of stress with the blind,” IEEE Sensors J., vol. 12, no. 3, pp. 543–551, Mar. 2012.
 Y. T. Chen, I. C. Hung, M. W. Huang, C. J. Hou, and K. S. Cheng, “Physiological signal analysis for patients with depression,” in Proc. 4th Int. Conf. Biomed. Eng. Informat., Shanghai, China, 2011, pp. 805–808.
 T. Taleb, D. Bottazzi, and N. Nasser, “A novel middleware solution to improve ubiquitous healthcare systems aided by affective information,” IEEE Trans. Inf. Technol. Biomed., vol. 14, no. 2, pp. 335–349, Mar. 2010.
 J.G.Ko,C.Y.Lu,M.B.Srivastava,J.A.Stankovic,A.Terzis,andM.Welsh, “Wireless sensor networks for healthcare,” Proc. IEEE, vol. 98, no. 11, pp. 1947–1960, Nov. 2010.
 W. Y. Chung, C. Yau, K. S. Shin, and R. Myllylä, “A cell phone based health monitoring system with self-analysis processor using wireless sensor network technology,” in Proc. 29th Annu. Int. Conf. Eng. Med.Biol. Soc., Lyon, France, 2007, pp. 3705–3708.
 G. Lawton, “Machine-to-machine technology gears up for growth,”Computer, vol. 37, no. 9, pp. 12–15, Sep. 2004.
 C. Kim, A. Soong, M. Tseng, and X. Zhixian, “Global wireless machineto-machine standardization,” IEEE Internet Comput., vol. 15, no. 2, pp. 64–69, Mar.–Apr. 2011.
 S. Whitehead, “Adopting wireless machine-to-machine technology,” Comput. Control Eng., vol. 15, no. 5, pp. 40–46, Oct. 2004.
 C. Inhyok, Y. Shah, A. U. Schmidt, A. Leicher, and M. V. Meyerstein, “Trust in M2M communication,” IEEE Veh. Technol. Mag., vol. 4, no. 3, pp. 69–75, Sep. 2009.
 Z. Shelby and C. Bormann, 6LoWPAN: The Wireless Embedded Internet. New York: Wiley, 2009, pp. 1–244.
 W. Shen, Y. Xu, D. Xie, T. Zhang, and A. Johansson, “Smart border routers for e-healthcare wireless sensor networks,” in Proc. 7th Int. Conf. Wireless Commun., Netw. Mobile Comput., Wuhan, China, 2011, pp. 1–4.
 A. J. Jara, M. A. Zamora, and A. F. G. Skarmeta, “An architecture based on internet of things to support mobility and security in medical environments,” in Proc. 7th IEEE Consumer Commun. Netw. Conf., Las Vegas, NV, 2010, pp. 1–5.
 S. H. Toh, S. C. Lee, and W. Y. Chung, “WSN based personal mobile physiological monitoring and management system for chronic disease,” in Proc. 3rd Int. Conf. Convergence Hybrid Inf. Technol., Busan, Korea, 2008, pp. 467–472.
 N. D. Lane, E. Miluzzo, H. Lu, D. Peebles, T. Choudhury, and A. T. Campbell, “A survey of mobile phone sensing,” IEEE Commun. Mag., vol. 48, no. 9, pp. 140–150, Sep. 2010.
 W. Y. Chung, Y. D. Lee, and S. J. Jung, “A wireless sensor network compatible wearable u-healthcare monitoring system using integrated ECG, accelerometer and SpO2,” in Proc. 30th Annu. Int. Conf. Eng. Med. Biol. Soc., Vancouver, BC, Canada, 2008, pp. 1529–1532.
 S. J. Jung and W. Y. Chung, “Flexible and scalable patient’s health monitoring system in 6LoWPAN,” Sensor Lett., vol. 9, no. 2, pp. 778–785, Apr. 2011.
 Internet Engineering Task Force (IETF). (2009) [Online]. Available: http://www.ietf.org/
 Samsung Galaxy S. (2010) [Online]. Available:http://www.samsung.com/global/microsite/galaxys/index_2. Ml
 M. Malik, “Heart rate variability: Standards of measurement, physiological interpretation, and clinical use,” Circulation, vol. 93, no. 5.
Pulse, SPO2, airflow (breathing), Body temperature,ECG,glucometer, galvanic skin response, blood pressure, patient position, muscle/electromyography sensor (EMG).