Bispectrum for the detection of the effect of photic and microwave stimulation on human EEG

Med. Biol. Eng. Comput.

Kalda

Lass

et al. 2005

Self Cite

The study compared traditional spectral analysis and a new scale-invariant method, the analysis of the length distribution of low-variability periods (LDLVPs), to distinguish between electro-encephalogram (EEG) signals with and without a weak stressor, a low-level modulated microwave field. During the experiment, 23 healthy volunteers were exposed to a microwave (450 MHz) of 7 Hz frequency on-off modulation. The field power density at the scalp was 0.16 mW cm(-2). The experimental protocol consisted of ten cycles of repetitive microwave exposure. Signals from frontal EEG channels FP1 and FP2 were analysed. Smooth power spectrum and length distribution curves of low-variability periods, as well as probability distribution close to normal, confirmed that stationarity of the EEG signal during recordings was achieved. The quantitative measure of LDLVPs provided a significant detection of the effect of the stressor for the six subjects exposed to the microwave field but for none of the sham recordings. The spectral analysis revealed a significant result for one subject only. A significant effect of the exposure to the EEG signal was detected in 25% of subjects, with microwave exposure increasing EEG variability. The effect was not detectable by power spectral measures.

Section: Distinction Of Stressor Effectmentioning

confidence: 97%

“…We used modulated microwave radiation at a non-thermal level of field power density, identical to our previous studies (LASS et al, 2002;PARTS et al, 2003). Microwave exposure conditions were the same for all subjects.…”

Section: Microwave Exposurementioning

confidence: 99%

Non-linear analysis of the electroencephalogram for detecting effects of low-level electromagnetic fields

Med. Biol. Eng. Comput.

Kalda

Lass

et al. 2005

Self Cite

“…The 1 W output power was guided by a coaxial cable to the 13 cm quarter wave antenna, located 10 cm from the left side of the head. The field power density at the skin, estimated by the measured calibration curves, was 0.16 mW/cm 2 , SAR was about 0.35 W/kg [5]. …”

Section: Microwave Exposurementioning

confidence: 99%

“…It is difficult to detect small variations in the EEG signals on the background of their high natural variability. Manuscript Our previous studies on detection of the effect of microwave radiation on human EEG showed that some traditional methods for EEG analysis such as weighted spectral intensity, bispectrum or fractal dimension, usually successfully applied, did not provide distinction of small changes caused by microwave in EEG [5,6]. In the case of detection of small changes in stochastic signals the method of modulation with further integration of differences between the segments of signal with and without expected change would be useful.…”

Section: Introductionmentioning

confidence: 99%

Integration of differences in EEG Analysis Reveals Changes in Human EEG Caused by Microwave

2006 International Conference of the IEEE Engineering in Medicine and Biology Society

Lass²,

Kalda³

et al. 2006

Three different methods in combination with integration of differences in signals were applied for EEG analysis to distinguish changes in EEG caused by microwave: S-parameter, power spectral density and length distribution of low variability periods. The experiments on the effect of modulated low-level microwaves on human EEG were carried out on four different groups of healthy volunteers exposed to 450 MHz microwave radiation modulated with 7 Hz, 14 Hz, 21 Hz, 40 Hz, 70 Hz, 217 or 1000 Hz frequencies. The field power density at the scalp was 0.16 mW/cm2. The EEG analysis performed for individuals with three different methods showed that statistically significant changes occur in the EEG rhythms energy and dynamics between 12% and 30% of subjects.

“…Our previous attempts on detection of the effect of microwave radiation on human EEG showed that some traditional methods of EEG analysis such as weighted spectral power of the EEG frequency bands, bispectrum or fractal dimension, usually successfully applied, did not provide reliable distinction of small changes in the EEG caused by the microwave radiation [ 9 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

Methods of electroencephalographic signal analysis for detection of small hidden changes

Hinrikus

Kalda

et al. 2007

Nonlinear Biomed Phys

The aim of this study was to select and evaluate methods sensitive to reveal small hidden changes in the electroencephalographic (EEG) signal. Two original methods were considered.Multifractal method of scaling analysis of the EEG signal based on the length distribution of low variability periods (LDLVP) was developed and adopted for EEG analysis. The LDLVP method provides a simple route to detecting the multifractal characteristics of a time-series and yields somewhat better temporal resolution than the traditional multifractal analysis.The method of modulation with further integration of energy of the recorded signal was applied for EEG analysis. This method uses integration of differences in energy of the EEG segments with and without stressor.Microwave exposure was used as an external stressor to cause hidden changes in the EEG. Both methods were evaluated on the same EEG database. Database consists of resting EEG recordings of 15 subjects without and with low-level microwave exposure (450 MHz modulated at 40 Hz, power density 0.16 mW/cm 2 ). The significant differences between recordings with and without exposure were detected by the LDLVP method for 4 subjects (26.7%) and energy integration method for 2 subjects (13.3%).The results show that small changes in time variability or energy of the EEG signals hidden in visual inspection can be detected by the LDLVP and integration of differences methods.