Tools

CNELab: A fast and user-friendly Matlab toolbox to review and process neurophysiological signal: CNELab 2.5.6, User Manual and Sample Dataset

CNELBehv: A WinAPI behavioral system (written in C++) to collect sensor data, video and forward to localhost through UDP: CNELBehv, CNEL_BEHV_Manual. Make sure to install VS2015 runtime library , UDP and RT pacer before hand.

Tutorial Video:

Teensy Demo Code

The above work (CNELab, CNELBehv) have been published in the 39th EMBS conference. Cite us if you find them useful !

Jiang, T., Siddiqui, H., Ray, S., Asman, P., Ozturk, M., & Ince, Firat, N. (2017). A Portable Platform to Collect and Review Behavioral Data Simultaneously with Neurophysiological Signals. In Proceedings of 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. Jeju Island. [download]

Unsupervised Clustering of High Frequency Oscillations [1a]

Sparse Common Spatial (Spectral) Pattern :

  • Greedy search : forward search and backward eliminating [1b]
  • Recursive weight elimination [2b][3b]
  • Oscillating search [4b]

Other commonly used tools and drivers:

[1a] Liu S, Sha Z , ASencer A, Aydoseli A, Bebek N, Abosch A, Henry T, Gurses C, Ince NF, “Exploring the time-frequency content of high frequency oscillations for automated prediction of seizure onset zone in epilepsy,” Journal of Neural Engineering, 2016 Apr;13(2):026026. [paper][ code]
[1b] Goksu F, Ince NF, and Tewfik H, “Greedy solutions for the construction of sparse spatial and spatio-spectral filters in brain computer interface applications,” Neurocomputing, vol. 108, pp. 69– 78, may 2013 . [download][code]
[2b] Onaran I and Ince NF, “Extraction of spatially sparse common spatio-spectral filters with recursive weight elimination,” in 2013 6th International IEEE/EMBS Conference on Neural Engineering (NER), pp. 1291–1294, IEEE, nov 2013. [download][code]
[3b] Goksu F, Ince NF, and Onaran I, “Sparse common spatial patterns with recursive weight elimination,” in 2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), pp. 117–121, IEEE, nov 2011. [download][code]
[4b] Onaran I, Ince NF, Abosch A, and Cetin AE, “Extraction of sparse spatial filters using Oscillating Search,” in 2012 IEEE International Workshop on Machine Learning for Signal Processing, pp. 1–7, IEEE, sep 2012. [download][code]