Comparative Analysis of Different Fractal Methods in Studying Post-ictal ECG signals of Epilepsy Patient

被引:0
|
作者
Chakraborty, Monisha [1 ]
Das, Tithi [2 ]
Ghosh, Dipak [3 ]
机构
[1] Jadavpur Univ, Sch Biosci & Engn, Kolkata, India
[2] Jadavpur Univ, Dept Phys, Kolkata, India
[3] Jadavpur Univ, Sir CV Raman Ctr Phys & Mus, Kolkata, India
来源
2016 IEEE FIRST INTERNATIONAL CONFERENCE ON CONTROL, MEASUREMENT AND INSTRUMENTATION (CMI) | 2016年
关键词
Epilepsy; Monofractal analysis; Multifractal analysis; Postictal ECG Signal; HEART-RATE DYNAMICS;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Measuring EEG signals as a diagnostic tool for Epileptic patient is a well traveled way. Different non-linear statistical approaches have been applied over the past years on this signal to reveal the nature of connection between epilepsy and EEG. In this work we study the post-ictal ECG signals of epileptic patient collected from MIT-BIH database using mono-fractal methods as well as multifractal approach. We compare the results of the same statistical methods with healthy normal group. Result from monofractal analysis such as Rescaled range analysis indicates that the ECG signals of epileptic patients are anti-persistent in nature whereas for healthy normal people it is persistent. Detrended fluctuation analysis also confirms the same fact and declares that ECG signals of healthy normal people are more persistent and more correlated than epileptic patients. Finally we use the multifractal approach on the ECG signals. Result from the Multifractal detrended fluctuation analysis confirms that healthy normal people have higher degree of multifractality compared to epileptic patients.
引用
收藏
页码:219 / 223
页数:5
相关论文
共 12 条
  • [1] Post-ictal psychosis in a patient with a history of nocturnal epilepsy
    Datta, Aarti
    Oladinni, Olakunle
    PROGRESS IN NEUROLOGY AND PSYCHIATRY, 2014, 18 (02) : 28 - 31
  • [2] Post-ictal forceful yawning in a patient with nondominant hemisphere epilepsy
    Yankovsky, AE
    Andermann, F
    Dubeau, F
    EPILEPTIC DISORDERS, 2006, 8 (01) : 65 - 69
  • [3] POST-ICTAL LOCOMOTOR-ACTIVITY IN 3 DIFFERENT RAT MODELS OF EPILEPSY
    EHLERS, CL
    KOOB, GF
    BLOOM, FE
    BRAIN RESEARCH, 1982, 250 (01) : 178 - 182
  • [4] Entropy Complexity Analysis of Electroencephalographic Signals During Pre-Ictal, Seizure and Post-Ictal Brain Events
    Zaylaa, A. J.
    Harb, A.
    Khatib, F. I.
    Nahas, Z.
    Karameh, F. N.
    2015 INTERNATIONAL CONFERENCE ON ADVANCES IN BIOMEDICAL ENGINEERING (ICABME), 2015, : 134 - 137
  • [6] Application of a vagal nerve stimulator in an epilepsy patient with cardiac pacemaker after post-ictal cardiac arrest
    Caceres, R.
    Richter, J.
    Safstrom, K.
    Landtblom, A. -M.
    ACTA NEUROLOGICA SCANDINAVICA, 2009, 120 (02): : 139 - 142
  • [7] Diagnosis of post-ictal heart oscillations in partial epilepsy using Power Spectral Density analysis
    Amarnath, M.
    Naik, B. Raghu
    Singh, Aditya Kumar
    Joshi, Ch. Dinesh
    2010 2ND INTERNATIONAL CONFERENCE ON COMPUTER AND AUTOMATION ENGINEERING (ICCAE 2010), VOL 3, 2010, : 333 - 336
  • [8] Post-ictal forceful yawning: An autonomic symptom in a patient with nondominant hemisphere epilepsy. Video-EEG presentation
    Yankovsky, AE
    Andermann, F
    Dubeau, F
    EPILEPSIA, 2005, 46 : 34 - 34
  • [9] Alterations of network synchrony after epileptic seizures: An analysis of post-ictal intracranial recordings in pediatric epilepsy patients
    Tomlinson, Samuel B.
    Khambhati, Ankit N.
    Bermudez, Camilo
    Kamens, Rebecca M.
    Heuer, Gregory G.
    Porter, Brenda E.
    Marsh, Eric D.
    EPILEPSY RESEARCH, 2018, 143 : 41 - 49
  • [10] A comparative analysis of signal processing and classification methods for different applications based on EEG signals
    Khosla, Ashima
    Khandnor, Padmavati
    Chand, Trilok
    BIOCYBERNETICS AND BIOMEDICAL ENGINEERING, 2020, 40 (02) : 649 - 690