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Volumn 6, Issue 9, 2009, Pages 560-565

Intelligent sensor node based a low power ECG monitoring system

Author keywords

Body sensor networks; ECG analysis; Low power

Indexed keywords

ABNORMALITY DETECTION; BODY SENSOR NETWORKS; ECG ANALYSIS; ECG SIGNALS; EUCLIDEAN DISTANCE; EUCLIDEAN DISTANCE MODEL; INTELLIGENT SENSORS; LIGHT WEIGHT; LOW POWER; LOW POWER IMPLEMENTATION; MONITORING SYSTEM; NODE-BASED; POWER CONSUMPTION; TRANSMISSION POWER;

EID: 67249161135     PISSN: None     EISSN: 13492543     Source Type: Journal    
DOI: 10.1587/elex.6.560     Document Type: Article
Times cited : (5)

References (6)
  • 3
    • 67249144197 scopus 로고    scopus 로고
    • Cardionet. [Online]
    • Cardionet. [Online] http://www.cardionet.com/
  • 4
    • 36049008097 scopus 로고    scopus 로고
    • Potential and challenges of body area networks for cardiac monitoring
    • April
    • B. Gyselinckx, J. Penders, and R. Vullers, "Potential and challenges of body area networks for cardiac monitoring," J. Electrocardiology, vol. 40, no. 4, pp. 789-802, April 2006.
    • (2006) J. Electrocardiology , vol.40 , Issue.4 , pp. 789-802
    • Gyselinckx, B.1    Penders, J.2    Vullers, R.3
  • 6
    • 3042565159 scopus 로고    scopus 로고
    • Cardiac arrhythmia classification using autoregressive modeling
    • Nov
    • D. F. Ge, N. Srinivasan, and S. M. Krishnan, "Cardiac arrhythmia classification using autoregressive modeling," Biomedical Engineering Online, vol. 1, no. 5, pp. 1-12, Nov. 2002.
    • (2002) Biomedical Engineering Online , vol.1 , Issue.5 , pp. 1-12
    • Ge, D.F.1    Srinivasan, N.2    Krishnan, S.M.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.