This program detects sleep spindles simultaneously across all channels of a multichannel human sleep EEG using a multichannel transient separation algorithm. Please see the publication below for further details.
To run a quick demo, run the file demo.m To utilize parallel detection on an excerpt of EEG (30 minutes) use runSpindleDetection.m For the MASS database, use the file Mass_parallelSpindleDetection.m For a demo of paramter tuning method used in the publication, run parameterTuning.m
Permanent Contact: ankit.parekh@nyu.edu ankit.parekh@mssm.edu
For questions regarding the code, please email at the addresses above.
Please cite as: Multichannel Sleep Spindle Detection using Sparse Low-Rank Optimization A. Parekh, I. W. Selesnick, R. S. Osorio, A. W. Varga, D. M. Rapoport and I. Ayappa Journal of Neuroscience Methods, Vol. 288, pp. 1-16, Aug. 2017. (https://doi.org/10.1016/j.jneumeth.2017.06.004)