Decoding imagined speech with delay differential analysis

HIGHLIGHTS

• What: The authors aim to test a non-linear speech decoding method based on delay differential analysis (DDA), a signal Frontiers in Human Neuroscience processing tool that is increasingly being used in the analysis of iEEG (intracranial EEG) (Lainscsek et_al, 2017). The authors evaluate the performance of DDA classification on two public imagined speech decoding datasets and compare different DDA approaches, such as training and validation between or across participants, in addition to varying window sizes. The authors aim to address this gap by providing a systematic review of the method relative to other past decoding work . . .
  

   

  

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