Subjective mood estimation using power energy of EEG frequency band

Various frequency bands can be distinguished by filters. Analog filters are restricted by component tolerances and ageing which result in incorrect measurement. Digital filters exhibit high accuracy and drift-less features. The sampling frequency for EEG (Electro-encephalogram) is not high. According to Nyquist-Shannon theorem, the sampling frequency is at least two times larger than the signal bandwidth. But in medical field applications, 8 to 12 times sampling rate is required. Therefore, digital filter is a good choice. So we choose an ADC (analog-to-digital converter) with a sampling rate of 500Hz, The EEG signal is sent to a PC via USB interface and passed through the digital filters procedure (Visual Basic 6) with 200 taps, and thus the spectrum of individual signals can be analyzed. For example, the Alpha Wave (α1, 8-10Hz, α2, 10-12Hz), beta (β1, 13-15Hz, β2, 16-24Hz), Theta (θ1, 4-5Hz, θ2, 6-7 Hz), Delta (δ, 1-3 Hz) can be employed to analyze the mood states and mood estimation.