• DocumentCode
    1569048
  • Title

    Heart Rate Analysis and Telemedicine: New concepts & Maths

  • Author

    Khoór, Sandor ; Kecskés, Istvan ; Kovács, Ilona ; Verner, D. ; Remete, A. ; Jankovich, P. ; Bartus, R. ; Stanko, Nandor ; Schramm, Norbert ; Domijan, Michael ; Domijan, E.

  • Author_Institution
    Szent Istvan Hosp., Budapest
  • fYear
    2007
  • Firstpage
    39
  • Lastpage
    43
  • Abstract
    Our paper deals with some new aspects of ambulatory (Holter) ECG monitoring extending its indications and using for risk management purpose. Remote sensing consists of the transmittal of patient information, such as ECG, X-rays, or patient records, from a remote site to a collaborator in a distant site. Our earlier developed internet based ECG system was unique for on/off-line analysis of long-term ECG registrations. After the 5-year experience in a smaller region of Budapest, Hungary involving a municipal hospital and the surrounding outpatient cardiology departments and general practitioners, we decided to integrate into our new ECG equipment, the CardioClient the results. In the first clinical study of the four was a wavelet, non-linear heart rate analysis in sudden cardiac death patients using the Internet and the GPRS mobile communication. After the wavelet transformation by the Haar wavelet and the Daubechies 10-tap wavelet, the phase-space of the wavelet-coefficient standard deviation and the scale parameters showed an excellent separation in the scale-range of 3-6 between the two groups: in that region, the average scaling exponents was 0.14plusmn0.04 for Group-A, and 1.22plusmn0.27 for Group-B (p<0.001). In the next study, we used the Internet database of long-term ambulatory, mobile, GPRS electrocardiograms for the for risk stratification of patients through the cardiovascular continuum. From our ambulatory mobile GPRS ECG database the following a priori groups were defined after a 24 months follow-up: G1: N=227 patients (without manifest cardiovascular disease, clusterized "boxes" based on the age, sex, cholesterol level, diabetes, hypertension ); G2: N=89 patients (postinfarction group); G3: N=66 (patients with chronic heart failure) with (+) or without (-): all-cause death (acD), myocardial infarction (MI), malignant ventricular arrhythmia (MVA), sudden cardiac death (SCD). The actual vs. predicted values were analyzed with chi-square test. The best- significance levels (p<0.001) were found with method in G1/MI+, G2/SCD+, G3/acD+, G3/SCD+ groups. In the third study a wavelet analysis of late potentials based on long-term, high-resolution, mobile, GPRS ECG data was performed. These pathological changes were also detected by the Haar and Daubechies_4 wavelets, but in a narrower space (110-128 ms and 180-240) and with lesser significance (p<0.01). Late potentials were found in Group-A (N=21) in 18 cases with Morlet, 16 with Haar, 19 with Daub-4 analysis, and in 15 cases using all the 3 waves; for Group-B the data were 5, 9, 8, 5, respectively. In the fourth clinical study the prognostic value of the nonlinear dynamicity measurement of atrial fibrillation waves detected by GPRS Internet long-term ECG monitoring were analyzed. The multivariate discriminant model selects the best parameters stepwise, the entry or removal based on the minimalization of the Wilks\´ lambda. Three variables remained finally: x1 = CI mean-value at log r=-1.0 (m9-14), x2 = CI mean-value at log r=-0.5 (m12-17), and x3 = CD_cg. The Wilks\´ lambda was 0.011, chi-square 299.68, significancy: p<0.001.
  • Keywords
    Haar transforms; Internet; biomedical communication; diseases; electrocardiography; medical computing; medical signal processing; mobile computing; packet radio networks; patient monitoring; wavelet transforms; CardioClient; Daubechies 10-tap wavelet; Daubechies_4 wavelets; ECG data; GPRS electrocardiogram; GPRS mobile communication; Haar wavelet; Holter ECG monitoring; Internet database; X-ray data; ambulatory ECG monitoring; atrial fibrillation waves; cardiovascular disease; chi-square test; cholesterol level; chronic heart failure; diabetes; hypertension; malignant ventricular arrhythmia; municipal hospital; myocardial infarction; nonlinear dynamicity measurement; outpatient cardiology department; patient information transmittal; patient record; patient risk stratification; sudden cardiac death patients; telemedicine; wavelet nonlinear heart rate analysis; wavelet transformation; wavelet-coefficient standard deviation; Cardiology; Databases; Electrocardiography; Ground penetrating radar; Heart rate; Internet; Patient monitoring; Remote monitoring; Telemedicine; Wavelet analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems and Informatics, 2007. SISY 2007. 5th International Symposium on
  • Conference_Location
    Subotica
  • Print_ISBN
    978-1-4244-1442-0
  • Electronic_ISBN
    978-1-4244-1443-7
  • Type

    conf

  • DOI
    10.1109/SISY.2007.4342620
  • Filename
    4342620