Iranian Journal of Biomedical Engineering (IJBME)
نشریه علمی مهندسی پزشکی زیستی

Evaluation of Baseline Craving in Patients with Methamphetamine Addiction Using EEG Signals in Neurofeedback Process

Document Type : Full Research Paper

Authors

Mahdi Zolfagharzadeh Kermani 1
Mohammad Ali Khalilzadeh 2
Majid Ghoshuni 3
Peyman Hashemian 4

1 Master,Department of Biomedical engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran

2 Associate Professor, Department of Biomedical engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran

3 Assistant Professor, Department of Biomedical engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran

4 Assistant Professor, MashhadUniversity of Medical Sciences, Department of Psychiatry, Mashhad, Iran

https://doi.org/10.22041/ijbme.2016.22212
Abstract
Evaluation and measurement of parameters associated with methamphetamine craving can be a valuable tool in the management and intervention programs related to methamphetamine use and dependence. We believe that quantitative electroencephalography (EEG) have brought about a revolution in identification the neurologic infrastructure of craving processing. This study has been conducted aimed to design and develop a new method to measure baseline craving in methamphetamine-dependent patients using EEG signals in neurofeedback therapy for separation of the three modes of low, medium, and high craving. For this purpose, 10 methamphetamine abusers were selected by available method in terms of age, sex and IQ. All patients received 10 sessions of neurofeedback therapy with alpha-theta protocol. During the period of treatment with neurofeedback, before and 60 minutes after each training session, at rest state, on Pz, for 2 minutes and 10 seconds EEG was recorded. To labeling EEG signals we have used Desire for Drug Questionnaire (DDQ). After collecting the required data from signals, time, frequency and nonlinear features were extracted. Then by calculating the linear correlation coefficient of the two variables and variance analysis on three levels optimized and effective features were selected. Finally, using fuzzy classifier, those features were separated into three classes of low, medium and high craving. According to the results, separation accuracy of EEG signals in three classes by K-fold Cross-Validation (KCV)method was 96.67% and test data was 75.15%. This study showed in addition to estimating baseline craving in methamphetamine abusers by quantifying EEG we can optimize the number of training sessions for participants.

Keywords

Methamphetamine
Craving
Electroencephalogram
Evaluation
Neurofeedback

Subjects

[1[اختیاری، حامد،“آشناییبامواداصلیاعتیادآوردرایران،راهنمایخانواده‌ها”، تهران، انتشارات مهروماهنو. (1388).
[2] H. Narenjiha, H. Rafiey, A. H. Baghestani, “Rapid situation assessment of drug abuse and drug dependence in Iran”, Circulated report [in Persian], DARIUS Institute, 2005.
[3] Kaufman, M. J. “Brain imaging in substance abuse: research, clinical, and forensic applications”,American Journal of Neuroradiology, 2001, 22, 1230-1231.
]4[رستمی، رضا؛ گودرزی، شاهرخ؛ بولهری، جعفر،“سم زدایی سریع: مروری بر مزایا و معایب. مجله اندیشه و رفتار”، (1382)، 8(4)، 31-16.
]5[اختیاری، حامد؛ علم مهجردی، زهرا؛ حسنی ابهریان، پیمان؛، نوری، مهری؛، فرنام، رابرت؛ مکری، آذرخش،“بررسی و ارزیابی واژه‌های القاء کنندة ولع مصرف، در سوء مصرف کنندگان مت آمفتامین فارسی زبان. فصلنامه تازه‌های علوم شناختی”، (1389)، 12(2)، 82-69.
[6] M. Maarefvand, P. Hasani-Abharian, H. Ekhtiari, “Measurement of drug craving in Persian speaking subjects; a review on current experiences and future perspectives”,Zahedan Journal of research in medical sciences, 2012, 14(9), 1-7.
[7] C. Praputpittaya, J. Krisanasap, P. Sribanditmongkol, “Correlation between locomotor activity and stereotyped behavior, but not ALPHA-1 EEG power spectrum, in methamphetamine-treated rats”,ThaiJournal of physiological sciences, 2005, 18(3), 41-53.
[8] J. Yamamoto,“Cortical and hippocampal EEG power spectra in animal models of schizophrenia produced with methamphetamine, cocaine, and phencyclidine”, Psychopharmacology, 1997,131(4), 379-387.
[9] T.Egner, E. Strawson, J. H. Gruzelier, “EEG signature andphenomenology of alpha/theta neurofeedback training versusmock feedback”,Applied Psychophysiology and Biofeedback, 2002, 27, 261–270.
[10] D. Vaitl, N. Birbaumer, J. Gruzelier, G. Jamieson, B.Kotchoubey, A. Kubler, D., Lehmann, WHR. Miltner, U. Ott, P. Putz, G.Sammer, I. Strauch, U.Strehl, J. Wackermann, T.Weiss, “Psychobiologyaltered states of consciousness”,Psychol Bull, 2005,131,98–127.
[11] IH. A. Franken, V. M. Hendriks, W. V. Brink, “Initial validation of two opiate craving questionnaires. The obsessive compulsive drug use scale and the desires for drug questionnaire”,Addict Behav, 2002,27(5), 675-685.
 [12] R. F. Anton, D. H. Moak, P.Latham,“The obsessive compulsive drinking scale: A self-rated instrument for the quantification of thoughts about alcohol and drinking behavior”,Alcoholism: Clinical Experimental Research, 1995, 19(1), 92-99.
]13[اختیاری، حامد؛ عدالتی، هانیه؛ بهزادی، آرین؛ نوری، مهری؛ صفایی، هومن؛ مکری، آذرخش،“تهیه و بررسی پنج آزمون تصویری ارزیابی ولع مصرف در گروه‌های مختلف معتادین اوپیوئدی”،ویژه نامه اعتیاد مجلة روانپزشکی و روانشناسی بالینی ایران، (1387)،14(3)، 349-337.
[14] United Nations Office on Drugs & Crime, (2010). World drug report 2010. United Nations Publications.
[15] R. R. Yager, D. P. Filev, (1994). Generation of fuzzy rules by mountain clustering. Journal of Intelligent & Fuzzy Systems, 2(3), 209-219, 1994.
Iranian Journal of Biomedical Engineering (IJBME)
Volume 9, Issue 3
Autumn 2015
Pages 243-251

  • Receive Date 07 August 2015
  • Revise Date 26 June 2016
  • Accept Date 17 October 2016

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