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EEG periodogram. Analysis of biomedical data.

Description

We could call this signal from a biological or medical source - just simple a biosignal. The biosignal could be at the molecular level, cell level, or a systemic or organ level.

Examples include the electrocardiogram (ECG), or electrical activity from the heart; speech signals; the electroencephalogram (EEG), or electrical activity from the brain; evoked potentials (EPs, i.e., auditory, visual, somatosensory, etc.), or electrical responses of the brain to specific peripheral stimulation; the electroneurogram, or field potentials from local regions in the brain; action potential signals from individual neurons or heart cells; the electromyogram (EMG), or electrical activity from the muscle; the electroretinogram from the eye; and so on.

We are going to use real EEG data from one subject.

Motivation

Analysis of biosignals is one of the most important thing now. Doctors doesn't have skills in programming languages, but they know a lot about medical things. Programmers can solve this problem, creating tools for doctors and helping them with detecting or estimating quickly.

Clinically, biomedical signals are primarily acquired for monitoring (detecting or estimating) specific pathological/physiological states for purposes of diagnosis and evaluating therapy. In some cases of basic research, they are also used for decoding and eventual modeling of specific biological systems.

Results

Here's EEG time series and EEG spectrum from different 5 sec records. Number of record: 7, 21 and 50.

Look at the spectrum. It has fluctuations of 13-40 Hz, so you can see betta waves. It's just simple example. If we talk about statistic data or how it helps in diagnostic we cannot use this data. First of all we need to average 84 records. See this repository

Learn more

Installation

You can use Python with data package: Anaconda or Miniconda. There's another way - use Portable Python. Also you can use whatever IDE for Python.

License

Free