Subjective mood estimation using power energy of EEG frequency band

Chin Shun Hsieh, Cheng Chi Tai

Research output: Contribution to conferencePaperpeer-review

2 Citations (Scopus)

Abstract

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, 1315Hz, 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.

Original languageEnglish
Pages517-520
Number of pages4
DOIs
Publication statusPublished - 2013 May 27
Event2013 IEEE International Symposium on Next-Generation Electronics, ISNE 2013 - Kaohsiung, Taiwan
Duration: 2013 Feb 252013 Feb 26

Other

Other2013 IEEE International Symposium on Next-Generation Electronics, ISNE 2013
CountryTaiwan
CityKaohsiung
Period13-02-2513-02-26

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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