Analysis of quantitative electroencephalogram background activity in Autism disease patients with Lempel-Ziv complexity and short time fourier transform measure

Proceedings of the 4th IEEE-EMBS International Summer School and Symposium on Medical Devices and Biosensors, ISSS-MDBS 2007

Volumn , Issue , 2007, Pages 111-114

  Sheikhani, Ali ^a   Behnam, Hamid ^b   Mohammadi, Mohammad Reza ^c   Noroozian, Maryam ^c   Golabi, Pari ^d  

^a ISLAMIC AZAD UNIVERSITY   (Iran)

^b IRAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Iran)

^c TEHRAN UNIVERSITY OF MEDICAL SCIENCES   (Iran)

^d Omid Iranian Children Association   (Iran)

Author keywords

Autism disorders; EEG; LZ complexity; STFT

Indexed keywords

BIOSENSORS; CHLORINE COMPOUNDS; FOURIER TRANSFORMS; IMAGING TECHNIQUES; INTERFERENCE SUPPRESSION; MEDICAL COMPUTING; MEDICAL IMAGING;

AGE CONTROL; AUTISM DISORDERS; EEG; ELECTROENCEPHALOGRAPHY (EEG); FREQUENCY ANALYSIS; LEMPEL-ZIV COMPLEXITY; LZ COMPLEXITY; MAHALANOBIS DISTANCE; MEDICAL DEVICES; SHORT-TIME FOURIER TRANSFORM; STFT; SUMMER SCHOOLS; TELEHEALTH TECHNOLOGIES; TERAHERTZ IMAGING; VARIANCE ANALYSIS;

ELECTROENCEPHALOGRAPHY;

EID: 48049123454     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISSMDBS.2007.4338305     Document Type: Conference Paper

References (29)

1. L. Kanner, Autistic disturbances of affective contact. Nervous Child (1943); 10:217-50.
2. SS. Gubbay, M. Lobascher, P. Kingerlee. A neurologic appraisal of autistic children: results of western Australian survey. Dev Med Child Neurol (1970); 12:433-9.
3. RF. Tuchman, I. Rapin, S. Shinnar, Autistic and dysphasic children:II. Epilepsy. Pediatrics (1991); 88:1219-25.
4. RF. Tuchman, I. Rapin, Epilepsy in autism. Lancet Neural (2002); 1:352-8..
5. I. Olsson, S. Steffenburg, C. Gillberg, Epilepsy in autism and autistic like conditions. Arch Neural (1988); 45; 666-8.
6. M.G. Chez, Frequency of epileptiform EEG abnor,malities in a sequential screening of autistic patients with no known clinical epilepsy from 1996 to 2005,ELSEVIER, Epilepsy&Behavior ,(2006)-267-271.
7. st international IEEE EMBS conference on Neural Engineering, Capri island ,italy, March 20-22,(2003).
8. th ed. Lippincott Willams & Wilkins, Philadelphia (1999).
9. Y. Shen, E. Olbrich, Dimensional complexity and spectral properties of the human sleep EEG, Clin. Neurophysiol. 114 (2) (2003); 199-209.
10. A.G. Hudetz, Effect of volatile anaesthetics on interhemispheric EEG cross-approximate entropy in the rat, Brain Res. 954 (1) (2002); 123-131.
11. M. Le Van Quyen, J, Martinerie, Characterizing neurodynami changes befor seizures, J. Clin. Neurophysiol. 18 (3), (2001); 191-208.
12. S.N. Sarbadhikari, K. Chakrabatry, Chaos in the brain: a short review alluding to epilepsy, depression, exercise and lateralization, Med. Eng. Phys. 23 (7), (2001); 447-457.
13. S. Tong, A. Bezerianos, J. Paul, Nonextensive entropy measure of EEG following brain injury from cardiac arrest, Physica A 305 (3,4) (2002); 619-628.
14. J. Jeong, J.H. Chae, S.Y. Kim, S.H. Han, Nonlinear dynamics analysis of EEG in patients with Alzheimers disease and vascular dementia, J. Clin. Neurophysiol. 18 (1) ,(2001) ;58-67.
15. M. Kemal Kiymik, Comparison of STFT and wavelet transform methods in determining epileptic seizure activity in EEG signals for real-tim application. Computers in Biology and Medicine 35, (2005); 603-616.
16. th ed. Washington DC; (1994).
17. A. Lempel, J., Ziv, On the complexity of finite sequences, IEEE Trans Inform Theory (1976); 22, 75-81.
18. D. Abasolo, Analysis of EEGbackground activity in Alzheimer's disease patients with Lempel-Ziv complexity and central tendency measure, Medical Engineering & Phsics 28 (2006); 315-322.
19. J. Jeong , SJ. Kim, Non-linear dynamical analysis of the EEG in Alzheimers disease with optimal embedding dimension. Electroenceph Clin Neurophysiol (1998); 106,220-8.
20. N. Radhakrishnan, BN. Gangadhar, Estimating regularity in epileptic seizure time-seriess data. A complexitymeasure approach. IEEE Eng Med Bol (1998); 17,89-94
21. XS. Zhang, YS. Zhu, Detecting ventricular tachycardia and fibrillation by complexity measure. IEEE Trans Biomed Eng (1999); 46: 548-55.
22. XS. Zhang, RJ. Roy, Derived fuzzy knowledge model for estimating the depth of anesthesia. IEEE Trans Biomed Eng (2001); 48: 312-23.
23. H.O. Gulcur, T. Demiralp. Analysis of EEG-EP variabilities: a parametric approach, Proceedings of the 1992 International Biomedical Engineering Days 1 (1992); 86-91.
24. O. Rioul, M. Vetterli, Wavelets and signal proessing, IEEE SP MAG. October (1991); 14-38.
25. P.S. Sebel, S.M. Bowles. EEG bispectrum predicts movement during thiopental/isoflurane anaesthesia. J, Clin. Monit .(1995); 11, 83-91.
26. J. Vernon, E. Lang, P. Sebel, Prediction of movement using BIS electroencephalographic analysis during propofol/alfentanil or isoflurane/alfentanil anaesthesia. Anesth. Analog.(1995); 80, 780-785.
27. MH. Zweig, G. Campbell. Receiver-operatingcharacteristic (ROC) plots: a fundamental evaluation tool in clinical medicine, Clin Chem (1993), 39:561-77.
28. st. IEEE EMBS conf. on Neural Engineering.
29. A. Schlogl, F. Lee, H. Bischof and G. Pfurtscheller, Characterization of four-class motor imagery EEG data for the BCI- Competitation , (2005) J.Neural Eng. 2 L14-22.