Abstract
This chapter presents analysis of emerging mHealth applications as well as the exploration of novel trends supporting healthcare intelligent environments assisted by mobile devices. The case of study is mHealth and remote vital sign monitoring. Particularly, we present a methodology for recollecting, processing and real-time monitoring heart activity with the main purpose to interpret electrocardiogram ECG signals, detect and manage situations of risk and provide the interaction between medical practitioner and patient into smart healthcare environment. The proposed architecture and approach provide continuous detection and interpretation of the patient’s QRS complex. The challenge is to adapt some approaches for data gathering, processing, compression, storage, analysis, and visualization to capabilities of mobile devices. The designed system for monitoring vital signals has been tested using standard MIT-BIH Arrhythmia Database achieving satisfactory ECG interpretation accuracy with relative error in range from 4 % to 10 % for signal sampling frequency of 360 and 128 samples per second respectively. It is important to note that the proposed prototype does not substitute diagnosis by physician. Our intention is to propose methodologies that serve as guide for development of complex health assistance tool expanding coverage of medical services.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Alarcon-Aquino, V., Starostenko, O.: Detection of micro calcifications in digital mammograms using the dual-tree complex wavelet transform. J. of Eng. Intel. Sys. 17(1), 49–63 (2009)
Aghajan, H., Augusto, J.C.: Home-based health and wellness measurement and moni-toring. J. Amb. Intel. and Smart Env. 4, 397 (2012)
AliveCor, AliveCor - mHealth for iHumans (2013), http://alivecor.com/ (accessed May 3, 2013)
Belgacem, N., Boumerdassi, S.: Mobile personal electrocardiogram monitoring system with patient location. In: Proceedings of the ACM Workshop on Medical-Grade Wireless Networks, Louisiana, pp. 69–72 (2009)
Biotronik, BIOTRONIK - excellence for life (2013), http://www.biotronik.com/es/lam/2246 (accessed December 10, 2013)
BSIG, Bluetooth Special Interest Group, Specification of BT v3.0+HS (2013), http://www.bluetooth.com/Pages/Bluetooth-Home.aspx (accessed January 6, 2014)
CardioNet, Mobile cardiac outpatient telemetry (MCOT) – cardiac telemetry cardionet event monitors (2013), http://www.cardionet.com/ (accessed May 10, 2013)
Curtis, D.V., Bailey, J., et al.: Using ambient intelligence for physiological monitoring. J. Amb. Intel and Smart Env. 1(2), 129–142 (2009)
Gay, V.: A mobile rehabilitation application for the remote monitoring of cardiac patients after a heart attack or coronary bypass surgery. In: Proceedings of the Conference on Pervsive Technologies, Greece, pp. 235–238 (2009)
Goldberger, A.L., et al.: PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation 101(23), e215–e220 (2013), http://www.physionet.org/physiobank/ (accessed April 6, 2013)
Hamilton, P.: Open source ECG analysis. J. Comput. in Cardiology, 101–104 (2002)
Handy, S.: The doctor in the pocket (2013), http://handysana.com/ (accessed April 8, 2013)
IEEE 802.15.4a, IEEE p802.15.4a/d7, Part 15.4: Wireless Medium Access Control and Physical Layer Specifications for low-rate wireless personal area networks, Technical report. IEEE, New York (2007)
IEEE 802.15.6, IEEE 802.15 WPANTM Task Group 6 (TG6) Body Area Networks (2013), http://www.ieee802.org/15/pub/TG6.html (accessed January 10, 2014)
IMEC, Monitoring your health with your mobile phone (2013), http://www2.imec.be/be_en/press/imec-news/wirelesshealthnecklaceinterface.html (accessed April 8, 2013)
Kyriacou, E.: System for monitoring of children with arrhythmias. In: Proceedings of the Conference on Pervsive Technologies, Greece, p. 668 (2009)
Kulkarni, S.: Smartphone driven healthcare system for rural communities in developing countries. In: Proceedings of the Workshop on Systems and Networking Support for Health Care Environments, Colorado, pp. 1–3 (2008)
Muñoz-Ramos, O., Starostenko, O., Alarcon-Aquino, V., Cruz-Perez, C.: Real-time system for monitoring and analyzing personal electrocardiogram on cell phone. In: Khaled, E., Tarek, S. (eds.) Innovations and Advances in Computer, Information, Systems Sciences and Engineering. LNEE, vol. 152(28), pp. 327–338. Springer, Heidelberg (2013)
Nieto, J.I., Vazquez, M., Cervantes, H., Martinez, M.E., Sergiyenko, O.: m-Health: software development and wireless technologies applications. In: Aquino Santos, R., Rangel Licea, V., Edwards Block, A. (eds.) Emerging Technologies in Wireless Ad Hoc Networks: Applications and Future Development, vol. 5, pp. 92–114. IGI Global, USA (2011)
Pan, J., Tompkins, W.J.: A real-time QRS detection algorithm. IEEE Trans. on Biomed. Eng., 230–236 (1985)
Pawar, P., Jones, V., Beijnum, B.-J., Hermens, H.: A framework for the comparison of mobile patient monitoring systems. J. of Biom. Informatics 45(3), 544–556 (2012)
Tzu-Hao, Y.: A portable real-time ECG recognition system based on smartphone. In: 35th Annual International Conference of IEEE Engineering in Medicine and Biology Society, Osaka, pp. 7262–7265 (2013), http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6611234 (accessed January 10, 2014)
Wagner, G.S.: Marriot Electrocardiografía Práctica, 11th edn. Lippincott Williams & Wilkins, Barcelona, Españ (2009)
Want, R.: When cell phones become computers. IEEE Pervasive Comp. J. 8(2), 2–5 (2009)
Yun-Hong, N.: Implementation of real-time abnormal ECG detection algorithm for wearable healthcare. In: 6th Conference on Computer Sciences and Convergence Information Technology, Seogwipo (2011), http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6316585 (accessed January 10, 2014)
Zhang, Y., Tian, Y., Wang, Z.: An ECG intelligent monitoring system with MSP430 mi-crocontroller. In: 8th Workshop on Systems, Signal Processing and their Applications, Algiers (2013), http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6602364 (accessed January 15, 2014)
Zheng, Q., Chen, C., Li, Z.: A novel multi-resolution SVM (MR-SVM) algorithm to de-tect ECG signal anomaly in WE-CARE project. In: Conference on Biosignals and Biorobotics, Rio de Janerio (2013), http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6487453 (accessed January 15, 2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Starostenko, O., Alarcon-Aquino, V., Rodriguez-Asomoza, J., Sergiyenko, O., Tyrsa, V. (2015). Remote Health/Vital Sign Monitoring. In: Adibi, S. (eds) Mobile Health. Springer Series in Bio-/Neuroinformatics, vol 5. Springer, Cham. https://doi.org/10.1007/978-3-319-12817-7_10
Download citation
DOI: https://doi.org/10.1007/978-3-319-12817-7_10
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-12816-0
Online ISBN: 978-3-319-12817-7
eBook Packages: EngineeringEngineering (R0)