References
[1]. G. Z. Yang (2006). Body Sensor Networks, 1st ed.
London: Springer-Verlag, pp. 1–275.
[2] P. S. Pandian, K. Mohanavelu, K. P. Safeer, T. M. Kotresh,
D. T. Shakunthala, P. Gopal, and V. C. Padaki (2008).
“Smart vest: Wearable multiparameter remote
physiological monitoring system,” Med. Eng. Phys., Vol.
30, No. 4, pp. 466–477.
[3]. T. Yilmaz, R. Foster, and Y. Hao (2010). “Detecting vital
signs with wearable wireless sensors,” Sensors, Vol. 10, No.
12, pp. 10837–10862.
[4]. B. Massot, N. Baltenneck, C. Gehin, A. Dittmar, and E.
McAdams (2012). “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.
[5]. Y. T. Chen, I. C. Hung, M. W. Huang, C. J. Hou, and K. S.
Cheng (2011). “Physiological signal analysis for patients
with depression,” in Proc. 4th Int. Conf. Biomed. Eng.
Informat., Shanghai, China, pp. 805–808.
[6]. T. Taleb, D. Bottazzi, and N. Nasser (2010). “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.
[7]. J. G. Ko, C. Y. Lu, M. B. Srivastava, J. A. Stankovic, A.
Terzis, and M.Welsh (2010). “Wireless sensor networks for
healthcare,” Proc. IEEE, Vol. 98, No. 11, pp. 1947–1960.
[8]. W. Y. Chung, C. Yau, K. S. Shin, and R. Myllylä (2007). “A
cell phone based health monitoring system with
selfanalysis processor using wireless sensor network
technology,” in Proc. 29th Annu. Int. Conf. Eng. Med. Biol.
Soc., Lyon, pp. 3705–3708.
[9]. G. Lawton (2004).“Machine-to-machine technology
gears up for growth,” Computer, Vol. 37, No. 9, pp. 12–15.
[10]. C. Kim, A. Soong, M. Tseng, and X. Zhixian (2011).
“Global wireless machineto-machine standardization,”
IEEE Internet Comput., Vol. 15, No. 2, pp. 64–69.
[11]. S. Whitehead (2004). “Adopting wireless machine
tomachine technology,” Comput. Control Eng., Vol. 15,No. 5, pp. 40–46.
[12]. C. Inhyok, Y. Shah, A. U. Schmidt, A. Leicher, and M.
V. Meyerstein (2009). “Trust in M2M communication,” IEEE
Veh. Technol. Mag., Vol. 4, No. 3, pp. 69–75,
[13]. Z. Shelby and C. Bormann (2009). 6LoWPAN: The
Wireless Embedded Internet. New York: Wiley, pp. 1–244.
[14]. W. Shen, Y. Xu, D. Xie, T. Zhang, and A. Johansson
(2011). “Smart border routers for e-healthcare wireless
sensor networks,” in Proc. 7th Int.Conf. Wireless Commun.,
Netw. Mobile Comput., Wuhan, China, pp. 1–4.
[15]. A. J. Jara, M. A. Zamora, and A. F. G. Skarmeta
(2010). “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, pp. 1–5.
[16]. S. H. Toh, S. C. Lee, and W. Y. Chung (2008). “WSN
based personal mobile physiological monitoring and
management system for chronic disease,” in Proc. 3rd Int.
Conf. Convergence Hybrid Inf. Technol., Busan, Korea,
pp. 467–472.
[17]. 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.
[18]. W. Y. Chung, Y. D. Lee, and S. J. Jung (2008). “A
wireless sensor network compatible wearable
uhealthcare monitoring system using integrated ECG,
accelerometer and SpO2,” in Proc. 30th Annu. Int. Conf.
Eng. Med. Biol. Soc., Vancouver, BC, Canada, pp.
1529–1532.
[19]. S. J. Jung and W. Y. Chung (2011). “Flexible and
scalable patient's health monitoring system in 6LoWPAN,”
Sensor Lett., Vol. 9, No. 2,pp. 778–785,
[20]. Internet Engineering Task Force (IETF). (2009)
Retrieved from : http://www.ietf.org/
[21]. Samsung Galaxy S. (2010) Retrieved from : http
://www.samsung.com/global/microsite/galaxys/index_2.
html.
[22]. M. Malik (1996). “Heart rate variability: Standards of
measurement, physiological interpretation, and clinical
use,” Circulation, Vol. 93, No. 5,pp. 1043–1065,
[23]. J. Valencia, M. Vallverdu, R. Schroeder, A. Voss, R.
Vazquez, A. Bayes de Luna, and P. Caminal (2009).
“Complexity of the short-term heart-rate variability,” IEEE
Eng. Med. Biol. Mag., Vol. 28, No. 6, pp. 72–78.
[24]. C. W. Lin, J. S. Wang, and P. C. Chung (2010). “Mining
physiological conditions from heart rate variability
analysis,” IEEE Comput. Intell. Mag., Vol. 5, No. 1, pp.
50–58.
[25]. U. Dulleck, A. Ristl, M. Schaffner, and B. Torgler (2011). “Heart rate variability, the autonomic nervous system, and neuroeconomic experiments,” J. Neurosci. Psychol. Econ., Vol. 4, No. 2, pp. 117–124.
[26]. M. A. Garcia-Gonzalez, M. Fernandez-Chimeno, and J. Ramos-Castro (2007). “Estimation of the uncertainty in time domain Indices of RR time series,” IEEE Trans. Biomed. Eng., Vol. 54, No. 3, pp. 556–563,
[27]. R. Bailón, L. Sörnmo, and P. Laguna (2006). “A robust method for ECGbased estimation of the respiratory frequency during stress testing,” IEEE Trans. Biomed. Eng.,Vol. 53, No. 7, pp. 1273–1285,
[28]. E. Tobaldini, N. Montano, S. G. Wei, Z. H. Zhang, J. Francis, R. Weiss, K. Casali, R. Felder, and A. Porta (2009). “Autonomic cardiovascular modulation,” IEEE Eng. Med. Biol. Mag., Vol. 28, No. 6, pp. 79–85,