Journal of Sensor Science and Technology (센서학회지)

The Korean Sensors Society (한국센서학회)
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A Research for Removing ECG Noise and Transmitting 1-channel of 3-axis Accelerometer Signal in Wearable Sensor Node Based on WSN

무선센서네트워크 기반의 웨어러블 센서노드에서 3축 가속도 신호의 단채널 전송과 심전도 노이즈 제거에 대한 연구

  • Lee, Seung-Chul (Department of Electronic Engineering, Graduate School, Pukyong National University) ;
  • Chung, Wan-Young (Department of Electronic Engineering, Pukyong National University)
  • 이승철 (부경대학교 대학원 전자공학과) ;
  • 정완영 (부경대학교 전자공학과)
  • Received : 2011.01.08
  • Accepted : 2011.03.21
  • Published : 2011.03.31
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Abstract

Wireless sensor network(WSN) has the potential to greatly effect many aspects of u-healthcare. By outfitting the potential with WSN, wearable sensor node can collects real-time data on physiological status and transmits through base station to server PC. However, there is a significant gap between WSN and healthcare. WSN has the limited resource about computing capability and data transmission according to bio-sensor sampling rates and channels to apply healthcare system. If a wearable node transmits ECG and accelerometer data of 4 channel sampled at 100 Hz, these data may occur high loss packets for transmitting human activity and ECG to server PC. Therefore current wearable sensor nodes have to solve above mentioned problems to be suited for u-healthcare system. Most WSN based activity and ECG monitoring system have been implemented some algorithms which are applied for signal vector magnitude(SVM) algorithm and ECG noise algorithm in server PC. In this paper, A wearable sensor node using integrated ECG and 3-axial accelerometer based on wireless sensor network is designed and developed. It can form multi-hop network with relay nodes to extend network range in WSN. Our wearable nodes can transmit 1-channel activity data processed activity classification data vector using SVM algorithm to 3-channel accelerometer data. ECG signals are contaminated with high frequency noise such as power line interference and muscle artifact. Our wearable sensor nodes can remove high frequency noise to clear original ECG signal for healthcare monitoring.

Keywords

References

  1. M. Rigby,“ Applying emergent ubiquitous technologies inhealth: The need to respond to new challenges of opportunity, expectation, and responsibility”, International Journal of Medical Informatics, vol. 76,supplement 3, pp. S349-S352, 2007. https://doi.org/10.1016/j.ijmedinf.2007.03.002
  2. S.-H. Toh, S.-C. Lee, H.-J. Lee, K.-U. Do, and W.-Y.Chung “Mobile u-healthcare system in IEEE 802.15.4WSN and CDMA network environments”, J. Kor. SensorsSoc., vol. 18, no. 5, pp. 337-342, 2009. https://doi.org/10.5369/JSST.2009.18.5.337
  3. Luprano and O. Chetelat, “Sensors and parameterextraction by wearable systems: Present situation andfuture”, Preceding of International Workshop onWearable Micro and Nanosystems for PersonalisedHealth, 2008.
  4. F. Hu, M. Jiang, L. Celentano, and Y. Xiao, “Robustmedical ad hoc sensor networks (MASN) with waveletbasedECG data mining”, Ad Hoc Networks, vol. 6, issue7, pp. 986-1012, 2008. https://doi.org/10.1016/j.adhoc.2007.09.002
  5. J.-H. Lee, K.-W. Seong, M.-N. Kim, and J.-H. Cho,“Development for body temperature sensor andmonitoring telemetry system”, J. Kor. Sensors Soc., vol.19, no. 6, pp. 435-442, 2010. https://doi.org/10.5369/JSST.2010.19.6.435
  6. H. Alemdar, and C. Ersoy,“ Wireless sensor networks forhealthcare: A survey”, Computer Networks, vol. 54, issue15, pp. 2688-2710, 2010. https://doi.org/10.1016/j.comnet.2010.05.003
  7. S.-C Lee, Y.-S. Seo, T.-H. Kwon, and W.-Y. Chung,“Design and evaluation of wireless sensor networkrouting protocolfor home healthcare “, J. Kor. SensorsSoc., vol. 19, no. 4, pp. 297-305, 2010. https://doi.org/10.5369/JSST.2010.19.4.297
  8. P.S. Pandian, K. Mohanavelu, K.P. Safeer, T.M. Kotresh,D.T. Shakunthala, Parvati Gopal, and V.C. Padaki,“Smart vest: Wearable multi-parameter remotephysiological monitoring system”, Medical Engineering &Physics, vol. 30, issue 4, pp. 466-477, 2008. https://doi.org/10.1016/j.medengphy.2007.05.014
  9. J.-W. Lee and G.-K. Lee,“ Design of an adaptive filterwith a dynamic structure for ECG signal processing”,International Journal of Control, Automation, andSystems, vol. 3, no. 1, pp. 137-142, 2005.
  10. D.M. Karantonis, M.R. Narayanan, M. Mathie, N.H.Lovell, and B.G. Celler,“ Implementation of a real-timehuman movement classifier using a triaxialaccelerometer for ambulatory monitoring”, InformationTechnology in Biomedicine, vol. 10, issue 1, pp. 156-167,2006. https://doi.org/10.1109/TITB.2005.856864
  11. J.-A. Lee, S.-H. Cho, Y.-J. Lee, H.-K. Yang, and J.-W.Lee, “Portable activity monitoring system for temporalparameters of gait cycles”, Journal of Medical Systems,vol. 34, no. 5, pp. 956-966, 2010.
  12. http://www.atmel.com/ Accessed may 9, 2005.

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