General Data Format for Biomedical Signals

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The General Data Format for Biomedical Signals is a scientific and medical data file format. The aim of GDF is to combine and integrate the best features of all biosignal file formats into a single file format. [1]

A file format is a standard way that information is encoded for storage in a computer file. It specifies how bits are used to encode information in a digital storage medium. File formats may be either proprietary or free and may be either unpublished or open.

A biosignal is any signal in living beings that can be continually measured and monitored. The term biosignal is often used to refer to bioelectrical signals, but it may refer to both electrical and non-electrical signals. The usual understanding is to refer only to time-varying signals, although spatial parameter variations are sometimes subsumed as well.

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The original GDF specification was introduced in 2005 as a new data format to overcome some of the limitations of the European Data Format for Biosignals (EDF). GDF was also designed to unify a number of file formats which had been designed for very specific applications (for example, in ECG research and EEG analysis). [2] The original specification included a binary header, and used an event table. [3] An updated specification (GDF v2) was released in 2011 and added fields for additional subject-specific information (gender, age, etc.) and utilized several standard codes for storing physical units and other properties. [2] In 2015, the Austrian Standardization Institute made GDF an official Austrian Standard https://shop.austrian-standards.at/action/en/public/details/553360/OENORM_K_2204_2015_11_15, and the revision number has been updated to v3.

Electrocardiography method to record the electrical activity of then heart through passive electrodes placed over the skin

Electrocardiography is the process of producing an electrocardiogram, a recording - a graph of voltage versus time - of the electrical activity of the heart using electrodes placed on the skin. These electrodes detect the small electrical changes that are a consequence of cardiac muscle depolarization followed by repolarization during each cardiac cycle (heartbeat). Changes in the normal ECG pattern occur in numerous cardiac abnormalities, including cardiac rhythm disturbances, inadequate coronary artery blood flow, and electrolyte disturbances.

Electroencephalography electrophysiological monitoring method

Electroencephalography (EEG) is an electrophysiological monitoring method to record electrical activity of the brain. It is typically noninvasive, with the electrodes placed along the scalp, although invasive electrodes are sometimes used, as in electrocorticography. EEG measures voltage fluctuations resulting from ionic current within the neurons of the brain. Clinically, EEG refers to the recording of the brain's spontaneous electrical activity over a period of time, as recorded from multiple electrodes placed on the scalp. Diagnostic applications generally focus either on event-related potentials or on the spectral content of EEG. The former investigates potential fluctuations time locked to an event, such as 'stimulus onset' or 'button press'. The latter analyses the type of neural oscillations that can be observed in EEG signals in the frequency domain.

The GDF format is often used in brain–computer interface research. [4] [5] [6] However, since GDF provides a superset of features from many different file formats, it could be also used for many other domains.


A brain–computer interface (BCI), sometimes called a neural-control interface (NCI), mind-machine interface (MMI), direct neural interface (DNI), or brain–machine interface (BMI), is a direct communication pathway between an enhanced or wired brain and an external device. BCI differs from neuromodulation in that it allows for bidirectional information flow. BCIs are often directed at researching, mapping, assisting, augmenting, or repairing human cognitive or sensory-motor functions.

The free and open source software BioSig library provides implementations for reading and writing of GDF in GNU Octave/MATLAB and C/C++. [7] A lightweight C++ library called libGDF is also available and implements version 2 of the GDF format. [8]

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References

  1. ↑ "Scientific data formats - Filters for Octave and Matlab" . Retrieved 3 August 2015.
  2. 1 2 Schlögl, Alois (2006). "GDF - A general dataformat for biosignals". arXiv: cs/0608052v10  Lock-green.svg.
  3. ↑ "GDF - A General Dataformat for Biosignals" (PDF). Retrieved 3 August 2015.
  4. ↑ "Standards in Brain-Computer Interfaces" . Retrieved 3 August 2015.[ permanent dead link ]
  5. ↑ Allison, Brendan Z.; et al., eds. (2012). Towards practical brain-computer interfaces bridging the gap from research to real-world applications. Berlin: Springer. p. 323. ISBN   9783642297465.
  6. ↑ Mellinger, Gerwin Schalk, Jürgen (2010). A practical guide to brain-computer interfacing with BCI2000 general-purpose software for brain-computer interface research, data acquisition, stimulus presentation, and brain monitoring (Online-Ausg. ed.). London: Springer. p. 91. ISBN   9781849960922.
  7. ↑ "BioSig". sourceforge.net. Retrieved 3 August 2015.
  8. ↑ "libGDF download - SourceForge.net". sourceforge.net. Retrieved 3 August 2015.
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