Signal quality index
Signal quality index (SQI)
The Signal quality index (SQI) is a measure of the quality of the EEG. It provides a numeric score indicating the cleanliness of the EEG. The score is normalised between 0-1 with a high score indicating a high level of artifact contamination of the signal and 0 indicating perfectly clean EEG.
SQI uses a series of preset thresholds to identify artifacts in the EEG. The more artifacts found the higher the score.
Further details of the operation of the SQI method can be found in the paper. Which may be obtained here.
The code can be downloaded from here.
Requirements
SQI runs in Matlab and requires the Matlab biosig toolbox to run (this can be found here (external website)). It does not rely on any other external toolboxes for its operation.
References
Please cite the following paper when using SQI, or a modified version of SQI, in your research.
Daly, I., Pichiorri, F., Faller, J., Kaiser, V., Kreilinger, A., Scherer, R., & Mueller-Putz, G. (2012). What does clean EEG look like? In Conf Proc IEEE Eng Med Biol Soc.
I recommend you also acknowledge the authors of the biosig toolbox when using SQI in your research.
Schölgl, A., Vidaurre, C., & Sander, T. H. (2011). BioSig: The free and open source software library for biomedical signal processing. Computational Intelligence and Neuroscience, 2011. https://doi.org/10.1155/2011/935364