- Volume 65 Issue 7
DOI QR Code
Acquisition of Multi-channel Biomedical Signals Based on Internet of Things
사물인터넷 기반의 다중채널 생체신호 측정
Kim, Jeong-Hwan;Jeung, Gyeo-Wun;Lee, Jun-Woo;Kim, Kyeong-Seop
- Received : 2016.06.01
- Accepted : 2016.06.10
- Published : 2016.07.01
Internet of Things(IoT)-devices are now expanding inter-connecting networking technologies to invent healthcare monitoring system especially for assessing physiological conditions of the chronically-ill patients those with cardiovascular diseases. Hence, IoT system is expected to be utilized for home healthcare by dedicating the original usage of IoT devices to collect the biomedical data such as electrocardiogram(ECG) and photoplethysmography(PPG) signal. The aim of this work is to implement health monitoring system by integrating IoT devices with Raspberry-pi components to measure and analyze ECG and the multi-channel PPG signals. The acquired data and fiducial features from our system can be transmitted to mobile devices via wireless networking technology to support the concept of tele-monitoring services based on IoT devices.
Internet of things;IoT;Single-board computer;Raspberry-pi;ECG;PPG;PTT;Multi-channel system
- A. M. Ortiz, D. Hussein, S. C. Par, S. N. Han, "The Cluster Between Internet of Things and Social Networks Review and Research Challenges," IEEE Internet of Things Journal, vol. 1, No. 3, pp. 206-215, 2014. https://doi.org/10.1109/JIOT.2014.2318835
- L. M. R. Tarouco, L. M. Bertholdo, L. Z. Granville, "Internet of Things in Healthcare: Interoperatibility and Security Issues," IEEE International Conference on Communications, pp. 6121-6125, 2012.
- S. P. Heo, D. H. Noh, C. B. Moon, D. S. Kim, "Trend of IoT-based Healthcare Service," Journal of Institute of Embedded Engineering of Korea, vol. 10, No. 4, 2015.
- W. D. Cho, Smart Mobile Healthcare Service Trend, Jinhan M&B, 2012.
- C. T. Kasundra, A. S. Shirsat, "Raspberry-Pi Based Health Monitoring System," International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, vol. 4, No. 8, pp. 7147-7154, 2015.
- F. Abrahi, B. Aslamy, I. Boujabir, F. Seoane, K. Lindecrantz, "An Affordable ECG and Respiration Monitoring System Based on Raspberry PI and ADAS1000: First Step towards Homecare Applications," Nordic-Baltic Conference on Biomedical Engineering, vol 28, pp. 5-8, 2015.
- U. R. Acharya, J. S. Suri, J. A. E. Spaan, S. M. Krishnan, Advances in Cardiac Signal Processing, Springer, 2007.
- J. Allen, Photoplethysmography and its Application in Clinical Physiological Measurement," Physio. Meas, vol 28, No. 3, pp. R1-R39, 2007. https://doi.org/10.1088/0967-3334/28/3/R01
- R. A. Payne, C. N. Symeonides, D. J. Webb, S. R. J. Maxwell, "Pulse Transit Time Measured from the ECG: an Unreliable Marker of Beat-to-beat Blood Pressure," Journal of Applied Physiology, vol. 100, pp. 136-141, 2006. https://doi.org/10.1152/japplphysiol.00657.2005
- S. E, Park, J. H. Kim, G. W. Jeung, K. S. Kim, "Estimation of Fiducial Points of PPG Signal by Utilizing ECG R-Peaks," Information and Control Symposium, pp. 182-183, 2014.
- M. C. Hemon, J. P. Phillips, "Comparison of Foot Finding Methods for Deriving Instantaneous Pulse Rates from Photoplethysmographic Signals," Journal of Clinic Monitoring and Computing, vol. 30 No. 2, pp. 157-168, 2016. https://doi.org/10.1007/s10877-015-9695-6
Supported by : 한국연구재단