On fusion of heart and brain signals for hybrid BCI

Shahjahan Shahid, G Prasad, R. K. Sinha

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

13 Citations (Scopus)


This paper investigates the fusion of ECG with EEG in devising a hybrid brain-computer interface (hBCI). Effortful motor imagery (MI) based BCI experiments were arranged with a twelve seconds of cue-based MI paradigm on six healthy individuals over two sessions of 160 trials, while ECG and EEG signals were simultaneously recorded. The proposed hBCI uses bispectrum based features from EEG and ECG along with an LDA classifier. The off-line analysis shows an improvement in MI task detection accuracy if both ECG and EEG features are considered together. In addition, the time domain analysis of ECG signal shows that the average heart rate increases during MI state, which clearly shows that the cardiac system responds to MI related tasks.
Original languageEnglish
Title of host publicationUnknown Host Publication
Place of PublicationCancun, Mexico
Number of pages5
Publication statusPublished (in print/issue) - 1 May 2011
Event5th Int. IEEE EMBS Conference on Neural Engineering - Cancun, Mexico
Duration: 1 May 2011 → …


Conference5th Int. IEEE EMBS Conference on Neural Engineering
Period1/05/11 → …


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