IMPLEMENTATION OF AN AUTOMATED ECG-BASED DIAGNOSIS ALGORITHM FOR A WIRELESS BODY SENSOR PLATAFORM

Francisco J. Rincón, Laura Gutiérrez, Mónica Jiménez, Víctor Díaz, Nadia Khaled, David Atienza, Marcos Sánchez-Élez, Joaquín Recas, Giovanni De Micheli

Abstract

Wireless Body Sensor Networks (WBSN) are poised to become a key enabling technology of personal systems for pervasive healthcare. Recent results have however shown that the conventional approach to their design, which consists in continuous wireless streaming of the sensed data to a central data collector, is unsustainable in terms of network lifetime and autonomy. Furthermore, it was established that wireless data communication is responsible for most of the energy consumption. To address the energy inefficiency of conventional WBSNs, we advocate an advanced WBSN concept where sensor nodes exploit their available, yet limited processing and storage resources to deploy advanced embedded intelligence and processing, to reduce the amount of wireless data communication and consequently energy consumption. More specifically, this paper addresses the design and optimization of an automated real-time electrocardiogram (ECG) signal analysis and cardiovascular arrhythmia diagnosis application for a prototype sensor node called Wireless 25 EEG/ECG system. The satifactory accuracy of this on-line automated ECG-based analysis and diagnosis system is assessed and compared to the salient off-line automated ECG analysis algorithms. More importantly, our results show an energy consumption reduction of 80% to 100% with respect to conventional WBSNs, when our analysis and diagnosis algorithm is used to process the sensed ECG data to extract its relevant features, which are then wirelessly reported to the WBSN central data collector, after the node can automatically determine the potential cardiovascular pathology without human monitoring.

References

  1. Culler, D. (2006). Tinyos: Operating system design for wireless sensor networks. Sensors, pages 41-49.
  2. Culler, D., Estin, D., and Srivastava, M. (2004). Overview of sensor networks. Computer, pages 41-49.
  3. Daskalov, I. K. and Christov, I. I. (1999). Automatic detection of the electrocardiogram T-wave end. Med Biol Eng Comput, 37(3):348-353.
  4. Gay, D., Levis, P., von Behren, R., Welsh, M., Brewer, E., and Culler, D. (2003). The nesC language: A holistic approach to networked embedded systems. In PLDI'03:Programming Language Design and Implementation.
  5. Jovanov, E. and et al. (2005). A WBAN system for ambulatory monitoring of physical activity and health status: applications and challenges. In International Conference of the IEEE Engineering in Medicine and Biology Society.
  6. Kemere, C. and et al. (2004). Model-based decoding for reaching movement for prosthetic systems. In InKhadtare, M. S. and Sahambi, J. (2004). ECG arrhythmia analysis by multicategory support vector machine. In AACC, pages 100-107.
  7. Laguna, P., Mark, R. G., Goldberger, A. L., and Moody, G. B. (1997). A database for evaluation of algorithms for measurement of QT and other waveform intervals in the ECG. Computers in Cardiology, pages 673- 676.
  8. Lazzer, S., Feng, J., Koushanfar, F., and Potkonjak, M. (2002). System-architectures for sensor networks issues. In IEEE International Conference on Computer Design (ICCD).
  9. Li, C., Zheng, C., and Tai, C. F. (1995). Detection of ECG characteristic points using wavelet transforms. IEEE Transactions on Biomedical Engineering, 42:21-29.
  10. Lo, B. and Yang, G. (2005). Key technical challenges and current implementations of body sensor networks. In Second International Workshop on Wearable and Implantable Body Sensor Networks.
  11. L öfgren, N. and et al. (2007). EEG entropy estimation using a Markov model of the EEG for sleep stage separation in human neonates. In International Conference of the IEEE Engineering in Medicine and Biology Society.
  12. Lutz Bierl, T. I. (2000). MSP430 family mixed-signal microcontroller application reports. Technical Report TI06-2000.
  13. Penders, J., Gyselinckx, B., de Vicq, N., and Torfs, T. (2007). Body area networks for multi-modal biomedical monitoring. In pHealth.
  14. Pérez-Gómez, F. (1985). Cardiac Pacing. Editorial Grouz.
  15. Rincón, F., Paselli, M., Recas, J., Zhao, Q., Sánchez- Ólez, M., Atienza, D., Penders, J., and Micheli, G. D. (2008). OS-Based Sensor Node Platform and Energy Estimation Model for Health-Care Wireless Sensor Networks. In Design, Automation and Test in Europe (DATE 7808), number ISSN: 1530-1591/05.
  16. Schamroth, L. (1971). The disorders od cardiac rhythm. Blackwell Scientific Publications.
  17. Semiconductor, N. (2000). nRF2401 transceiver data sheets. http://www.nordicsemi.com/.
  18. S örnmo, L. and Laguna, P. (2005). Bioelectrical Signal Processing in Cardiac and Neurological Applications. Elsevier Academic Press.
  19. Sun, Y., Chan, K. L., and Krishnan, S. M. (2002). Ecg signal conditioning by morphological filtering. Computers in Biology and Medicine, 32(6):465-479.
  20. Sun, Y., Chan, K. L., and Krishnan, S. M. (2005). Characteristic wave detection in ecg signal using morphological transform. BMC Cardiovascular Disorders.
Download


Paper Citation


in Harvard Style

Rincón F., Gutiérrez L., Jiménez M., Díaz V., Khaled N., Atienza D., Sánchez-Élez M., Recas J. and De Micheli G. (2009). IMPLEMENTATION OF AN AUTOMATED ECG-BASED DIAGNOSIS ALGORITHM FOR A WIRELESS BODY SENSOR PLATAFORM . In Proceedings of the International Conference on Biomedical Electronics and Devices - Volume 1: BIODEVICES, (BIOSTEC 2009) ISBN 978-989-8111- 64-7, pages 88-96. DOI: 10.5220/0001549000880096


in Bibtex Style

@conference{biodevices09,
author={Francisco J. Rincón and Laura Gutiérrez and Mónica Jiménez and Víctor Díaz and Nadia Khaled and David Atienza and Marcos Sánchez-Élez and Joaquín Recas and Giovanni De Micheli},
title={IMPLEMENTATION OF AN AUTOMATED ECG-BASED DIAGNOSIS ALGORITHM FOR A WIRELESS BODY SENSOR PLATAFORM},
booktitle={Proceedings of the International Conference on Biomedical Electronics and Devices - Volume 1: BIODEVICES, (BIOSTEC 2009)},
year={2009},
pages={88-96},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001549000880096},
isbn={978-989-8111- 64-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Biomedical Electronics and Devices - Volume 1: BIODEVICES, (BIOSTEC 2009)
TI - IMPLEMENTATION OF AN AUTOMATED ECG-BASED DIAGNOSIS ALGORITHM FOR A WIRELESS BODY SENSOR PLATAFORM
SN - 978-989-8111- 64-7
AU - Rincón F.
AU - Gutiérrez L.
AU - Jiménez M.
AU - Díaz V.
AU - Khaled N.
AU - Atienza D.
AU - Sánchez-Élez M.
AU - Recas J.
AU - De Micheli G.
PY - 2009
SP - 88
EP - 96
DO - 10.5220/0001549000880096