6.1. Evaluation of the state of the brain
HFD for detection of depression. The sensitivity of the developed original linear Spectral Asymmetry Index (SASI) and nonlinear Higuchi’s fractal dimension (HFD) methods of electroencephalogram (EEG) analysis were shown being comparable in detection of depression in analysis of single-channel EEG signal. The rate of correct indication was 85% for SASI and had the same value also for HFD.
DFA of depression EEG. The results of Detrended Fluctuation Analysis (DFA) indicate that resting EEG of healthy subjects exhibits persistent long-range correlation in time. In depression the EEG long-range correlation was less persistent; even long-range anticorrelation was revealed for about half of the depressed subjects. SASI has superior discrimination ability with classification accuracy of 76.5 %, while the classification accuracy of DFA was 70.6 %.
LZC for detection of depression. The Lempel Ziv Complexity (LZC) calculated for eyes closed resting EEG demonstrated increased complexity in depression compared to controls; the difference between depressive and normal EEG is statistically significant even in a single-channel signal.
The experimental results for evaluation of sensitivity of SASI for detection of depression showed that the developed original SASI method provides, compared to well-known nonlinear methods as HFD, DFA and LZC, not less sensitivity for evaluation of depression but required much less computing power.
Cooperation: North Estonia Medical Center, West-Tallinn Central Hospital, University of Skopje
- M. Bachmann, J. Lass, A. Suhhova, H. Hinrikus. Spectral Asymmetry and Higuchi’s Fractal Dimension Measures of Depression Electroencephalogram. Computational and Mathematical Methods in Medicine, vol. 2013, Article ID 251638, 8 pages, 2013. doi:10.1155/2013/251638.
- M. Bachmann, K. Kalev, A. Suhhova, J. Lass, H. Hinrikus. Lempel Ziv Complexity of EEG in depression. IFMBE Proceedings: 6th European Conference of the International Federation for Medical and Biological Engineering, Dubrovnik, 7-11.09.2014, vol. 45, pp. 58 - 61. Springer, 2015.
6. 2. The mechanism of microwave radiation effect on the brain bioelectric activity
Physical mechanism of microwave effect. Our experimental results confirm that low-level microwave radiation enhances diffusion at constant temperature. As a consequence, a mechanism of low-level microwave effect was proposed: microwave radiation, rotating dipolar water molecules, causes high-frequency alterations of hydrogen bonds between water molecules, thereby makes faster diffusion and disturbs the neurophysiologic processes at constant temperature. The modulated microwave radiation causes excitation of EEG rhythms at the parametric resonance frequencies. The proposed mechanism is a step behind the state of the art in world-wide discussion on the of low-level microwave effects.
SASI and HFD reveal microwave effect. Spectral asymmetry index (SASI) and Higuchi’s fractal dimension (HFD) methods detected modulated low-level microwave effect on human electroencephalographic (EEG) signal at the applied microwave power density 10 dB lower compared to existing heath protection limits. The experimental results confirm the proposed novel mechanism of low-level microwave radiation effect and stimulation of brain bioelectric oscillations by microwave radiation.
Microwave stimulation as relatively simple for application, noninvasive and contact-free method, has some advantages compared to existing transcranial magnetic and direct electrical current stimulation methods.
Cooperation: Nalecz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences, University of Eastern Finland
- Hiie Hinrikus, Jaanus Lass, Denis Karai, Kristjan Pilt, and Maie Bachmann. Microwave effect on diffusion: a possible mechanism for non-thermal effect. Electromagnetic Biology and Medicine, Early Online: 1–7, May 23, 2014. doi:10.3109/15368378.2014.921195
- M. Bachmann, J. Lass, A. Suhhova, H. Hinrikus. Spectral asymmetry index and Higuchi’s fractal dimension for detecting microwave radiation effect on electroencephalographic signal. Proc. of the Estonian Academy of Sciences, 2014, 63, 3, 234–239.