Part ii: old mathematics for the novel applied problems of cardiometry

Автор: Adamoviс Evgenie D., Aleksandrov Pavel L., Gradov Oleg V., Mamalyga Leonid M., Mamalyga Maksim L.

Журнал: Cardiometry @cardiometry

Рубрика: Original research

Статья в выпуске: 8, 2016 года.

Бесплатный доступ

Aims This paper describes a novel approach to the analysis of electrocardiographic data based on the consideration of the repetitive P, Q, R, S, T sequences as cyclic codes. In Part I we introduce a principle similar to the syndrome decoding using the control numbers, which allows correcting the noise combinations. Materials and methods We propose to apply the burst-error-correcting algorithms for automatic detection of the ECG artifacts and the functional abnormalities, including those compared to the reference model. Our approach is compared to the symbolic dynamics methods in cardiology practice. During the automated search of the code components (i.e. point values and spectral ranges one-to-one corresponding to P, Q, R, S, T) considered in Part II, the authors apply the Lomb-Scargle periodogram method with the phase control which allows to determine the code components not only from the main harmonics, but also using the sidebands, avoiding the phase errors. Results The results of the method testing on rats with the heart failure using a simplified telemetric recording from the implantable chips are given in Part III...

Еще

Ecg, cyclic code, syndrome decodin, control numbers, lombscargle periodogram methods, fingerprinting

Короткий адрес: https://sciup.org/148308814

IDR: 148308814   |   DOI: 10.12710/cardiometry.2016.8.3946

Список литературы Part ii: old mathematics for the novel applied problems of cardiometry

  • Mamalyga ML. Application of the Novel Technologies for the Study of the Cardiovascular System Regulation by the Cerebral Mechanisms. Moscow: Prometheus, 2015. 80 p.
  • Mamalyga ML. Application of the Novel Technologies for the Complex Hemodynamics Estimation during the Study of the Interrelated Physiological Processes in the Heart and Brain. Moscow: Prometheus, 2015. 124 p.
  • Mamalyga ML. The Mutual Dependence of the Cerebral and Cardiovascular Disorders under the Seizure Activity of the Brain. Moscow: MPSU, 2015. 224 p.
  • Mamalyga ML. Cardiocerebral Disorders and Intracellular Changes in CNS under Seizure Activity and After its Correction. Moscow: Prometheus, 2015. 377 p.
  • Mamalyga ML. Physiological Basis of the Interdependent Processes in the Heart and Brain. Moscow: MPSU, 2014. 124 p.
  • Lomb NR. Least-squares frequency analysis of unequally spaced data. Astrophys. Sp. Sci. 1976;39:447-62.
  • Scargle JD. Studies in astronomical time series analysis: I. Modeling random processes in the time domain. Astrophysical Journal Suppl. Ser. 1981;45:1-71.
  • Scargle JD. Studies in astronomical time series analysis: IV. Modeling chaotic and random processes with linear filters. Astrophysical Journal. 1990;359:469-82.
  • Scargle JD. Studies in astronomical time series analysis. Statistical aspects of spectral analysis of unevenly spaced data. Astrophysical Journal. 1982;263:835-53.
  • Scargle JD. Studies in astronomical time series analysis: III. Fourier transforms, autocorrelation functions, and cross-correlation functions of unevenly spaced data. Astrophysical Journal. 1989;343:874-87.
  • Boulakia M, Fernández MA, Gerbeau JF, Zemzemi N. Numerical simulation of electrocardiograms. Modeling, Simulation and Applications. 2012;5:77-106.
  • Guillén A, Rojas I, Ros E, Herrera LJ. Using fuzzy clustering technique for function approximation to approximate ECG signals. Lecture Notes in Computer Science. 2005;3562:538-47.
  • Locsi L. Discrete Approximation of ECG Signals. In: Proceedings of the 8th International Conference on Applied Informatics, Eger, Hungary, January 27-30 2010;2:45-52.
  • Vityazev VV. The Time Interferometer: a new tool of spectral analysis of time series. Astron. and Astrophys. Trans. 1994;5:177-210.
  • Vityazev VV. Time series analysis of unequally spaced data: The statistical properties of the Schuster periodogram. Astron. and Astrophys. Trans. 1997;11:159-73.
  • Vityazev VV. Analysis of non-uniform time series. Saint-Petersburgh: SPSU Publishing, 2001. 68 p.
  • Peschel M. Modellbildung für signale und systeme. Berlin: VEB Verlag Techniqk, 1978. 184 p.
  • Gunawan H. A generalization of Bessel’s inequality and Parseval’s identity. Periodica Mathematica Hungarica. 2002;44(2):177-81.
  • Borodin LF. Introduction to the Theory of Jam-Proof Coding Electronics. Charlottesville: Army Foreign Science & Technology Center, 1970. 456 p.
  • Borodin LF. Einführung in die Theorie der störsicheren Kodierung. Leiptzig: Akademische Verlagsgesellschaft Geest und Portig, 1972. 380 p.
  • Peterson WW. Prüfbare und korrigierbare Codes. München, Oldenbourg. 1967. 380 p.
  • Peterson WW. Error-correcting codes. Cambridge: MIT Press, 1972. 558 p.
  • Slepian D. A note on two binary signaling alphabets. IRE Transactions on Information Theory. 1956;2(2):84-6.
  • Slepian D. Some further theory of group codes. 1960;39(5):1219-52.
  • Borodin LF. Equidistant and other optimal and near-optimal codes. Radio Eng. & Electron. 1961; 5(6):1-16.
  • Berlekamp ER. Hamming codes, single Error -correcting and cyclic. International Centre for Mechanical Sciences, Courses and Lectures. 1970;28:14-8.
  • Nechiporuk PA, Zhuravskaya OV, Poberaylo AA. Improvement of interference immunity of telemetry transmission systems based on the use of the Hamming code. Radioelectronics and Communications Systems. 2008;51(2):92-6.
  • Harikumar R, Shivappriya SN. A novel approach for different morphological characterization of ECG signal. Lecture Notes in Electrical Engineering. 2013;221:13-23.
  • Jankowski S, Tijink J, Vumbaca G, Balsi M, Karpinski G. Morphological analysis of ECG Holter recordings by support vector machines. Lecture Notes in Computer Science. 2002;2526:134-43
  • Krishnan SM, Keong KC, Sun Yan, Luk CK. ECG Signal Conditioning by Morphological Filters. In: Advances in Cardiac Signal Processing. Berlin -Heidelberg -New York:,Springer; 2007. pp. 311-326.
  • Sun Y, Chan KL, Krishnan SM. Characteristic wave detection in ECG signal using morphological transform. BMC Cardiovascular Disorders. 2005;5: 1-7. Art. No. 28.
  • Hocquenghem A. Codes correcteurs d'erreurs. Chiffres. 1959;2:147-56.
  • Bose RC, Ray-Chaudhuri DK. On a class of error correcting binary group codes. Information and Control. 1960;3(1):68-79.
  • Richters J. Application of Pareto error statistics to Hagelbarger codes. IEEE Transactions on Information Theory. 1965;11(4):571-6.
  • Elias P. Universal codeword sets and representations of the integers. IEEE Transactions on Information Theory. 1975;21(2):194-203.
  • Brodman K, Erdmann AJ, Lorge I, Wolff HG. The Cornell medical index-health questionnaire: II. As a diagnostic instrument. Journ. Amer. Med. Assoc. 1951;145(3):152-7.
  • Brodman K. Diagnostic decisions by machine. IRE Transactions on Medical Electronics. 1960;ME-7.
  • Brodman K, Van Woerkum AJ. Computer-aided diagnostic screening for 100 common diseases. Journ. Amer. Med. Assoc. 1966;197(11):901-5.
  • Brodman K, Goldstein LS, Baer RA. Automated diagnostic screening for comprehensive medicine. Journ. Occup. Med. 1967;9(10):494-7.
  • Brodman K, Goldstein LS. The medical data screen: an adjunct for the diagnosis of 100 common diseases. Archives of Environmental Health. 1967;14(6):821-6.
  • Kullback S, Leibler RA. On information and sufficiency. The Annals of Mathematical Statistics. 1951;22(1):79-86.
  • Wilson AG. Entropy in urban and regional modeling. London: Pion Limited, 1970.
  • Adamovich ED, Gradov OV. Joint Fourier and non-Fourier spectral/pseudo-spectral approach to the lung bioacoustics and biomedical signal fingerprinting as a way to increase the quality of the lung diagnostics using supercomplex hybridization of different DSP methods. Journal of Biomedical Technologies. 2015;1:34-7.
  • Gradov OV. Novel bioacoustic methods for marine faun research. Biomedical Engineering and Electronics. 2016;1.
  • Orehov TC, Gradov OV. Hybridization of COBAC, QSPR/QSAR and SBGN technologies: The unity of theory and practice for biomedical technique design and biochemical diagnostic information analysis. Journ. Med. Bioeng. 2015;5(2):128-32.
  • Alexandrov P, Notchenko A, Gradova M, Gradov O. Simultaneous in situ detection of the optical fluorescence, fluorescence recovery kinetics after photobleaching & membrane ion flux on the electrophysiological lab-on-a-chip. American Journal of Optics and Photonics. 2015;3(5):118-22.
  • Grädow O. Novel phenospectral auxanometry using complexation of optical spectroscopy and chromatographic auxanometry or GC-MS-auxanometry in forest plant species vegetation phenological monitoring based on gas & flavor chemistry principles. Journ. Green Herb. Chem. 2014;3(2):555-79.
  • Adamovich ED, Gradov OV, Orekhov FK. Tunable diode laser based spectral chronaximetry, adequatometry and discretometry -three novel methods for complex neuro-ophtalmological and photophysiological measurements (biomedical engineering notes). Medicus. 2015;4(4):54-6.
  • Notchenko AV, Gradov OV. Elementary Morphometric Labs-on-a-Chip Based on Hemocytometric Chambers with Radiofrequency Culture Identification and Relay of Spectrozonal Histochemical Monitoring. Visualization, Image Processing and Computation in Biomedicine. 2013;2
  • Gradov OV. Automatical phenological monitoring of birds species populations and bioacoustical maping of landscapes for taxonomical fingerprinting. But. S. 2013;4:75-84.
  • Gradov OV. Bioacoustical fingerprinting as a multifactor method for automatic identification of avifauna. But. S. 2013;4:65-74.
  • Jablokov AG, Gradov OV. Multiparametric qualimetric microsurgical scanning chip-lancet model: theoretical metrological and biomedical considerations. MicroMedicine. 2015;3(2):31-5.
  • Smith S, et al. Intraoperational physicochemical and physiochemical qualimetry as a general principle of multifactor monitoring of surgical manipulations (international bibliographic review). Part II: Intraoperational spectroscopy, spectrozonal and multi-spectral monitoring. International Reviews: Clinical Practice and Health Issue. 2014;8(2):5-20. .
  • Smith S, et al. Intraoperational physicochemical and physiochemical qualimetry as a general principle of multifactor monitoring of surgical manipulations (international bibliographic review). Part I: General principles of monitoring and control. International Reviews: Clinical Practice and Health.Vol. 2014;1(7):17-30. .
  • Gradov OV. Multifactor patchclamp spectroscopy as a method for analysis of the cell signalling and function regulation via the ion channels. Tsitologiya. 2015;57(9):625-6. .
  • Gradov OV. Patch-clamp-spectroscopy as a potential diagnostic instrument for molecular oncology and analysis of ion channels as a possible molecular targets. Usp. Mol. Oncol. 2015;2(4):66. .
Еще
Статья научная