Electroencephalogram (EEG) is the recording of the electrical activity of the brain. The EEG signal is a representative signal containing information about the condition of the brain.  The shape of the wave may contain useful information about the state of the brain.   However, the human observer can not directly monitor these subtle details.  EEG signal parameters, extracted and analyzed using computers, are highly useful in diagnostics. Some of the major fields of application of these relatively cheap and non-invasive diagnostic techniques are shown below.

a) SEIZURE - Epilepsy affects almost 1% of the world’s population. Automatic seizure detection is very important in clinical practice and has to be achieved by analyzing the EEG.  Comprehensive chaotic analysis of the normal, background and epileptic EEG signals are carried out.

Phase Space EEG of Normal State

Phase Space EEG during seizure

Phase Space EEG background (pre-seizure)

b) SLEEP - Sleep data is analyzed using nonlinear parameters. The analysis is carried out using nonlinear parameters: Correlation Dimension, Fractal Dimension, Largest Lyapunov Entropy, Approximate Entropy, Hurst Exponent, Phase space plot and Recurrence plots.

Recurrence Plot of Sleep stage 0

Recurrence Plot of Sleep stage 5

c) MEDITATION - Meditation is the breathing exercise developed by the ancient yogis for purification. The EEG signal amplitude and frequency varies at different stages meditation.

Variation of correlation dimension during the three stages of meditation

d) REFLEXOLOGY - Reflexology is a 4000-year-old art of healing practiced in ancient India, China and Egypt.  In the beginning of the 20th century it spread to the western world.  In spite of the widespread popularity, no serious research work has been done in this area. This research is an attempt to quantitatively assess the effect of reflexological stimulation from a systems point of view.

Reflex points on hand

Variation of Entropy with and without reflexology