@article{RealKotchoubeyKuebler2014,
  author    = {Real, Ruben G. L. and Kotchoubey, Boris and K{\"u}bler, Andrea},
  title     = {Studentized continuous wavelet transform (t-CWT) in the analysis of individual ERPs: real and simulated EEG data},
  doi       = {10.3389/fnins.2014.00279},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-113581},
  year      = {2014},
  abstract  = {This study aimed at evaluating the performance of the Studentized Continuous Wavelet Transform (t-CWT) as a method for the extraction and assessment of event-related brain potentials (ERP) in data from a single subject. Sensitivity, specificity, positive (PPV) and negative predictive values (NPV) of the t-CWT were assessed and compared to a variety of competing procedures using simulated EEG data at six low signal-to-noise ratios. Results show that the t-CWT combines high sensitivity and specificity with favorable PPV and NPV. Applying the t-CWT to authentic EEG data obtained from 14 healthy participants confirmed its high sensitivity. The t-CWT may thus be well suited for the assessment of weak ERPs in single-subject settings.},
  language  = {en}
}