Real-Time Classification of Actual vs Imagery Finger Tapping Using fNIRS

Maria Peifer; Li Zhu; Laleh Najafizadeh

doi:10.1364/BIOMED.2014.BM3A.34

Biomedical Optics 2014
OSA Technical Digest (online) (Optica Publishing Group, 2014),
paper BM3A.34
•https://doi.org/10.1364/BIOMED.2014.BM3A.34

Real-Time Classification of Actual vs Imagery Finger Tapping Using fNIRS

Maria Peifer, Li Zhu, and Laleh Najafizadeh

Biomedical Optics 2014

Miami, Florida United States
26–30 April 2014
ISBN: 978-1-55752-997-8

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Poster Session II (BM3A)

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M. Peifer, L. Zhu, and L. Najafizadeh, "Real-Time Classification of Actual vs Imagery Finger Tapping Using fNIRS," in Biomedical Optics 2014, OSA Technical Digest (online) (Optica Publishing Group, 2014), paper BM3A.34.

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Abstract

Using a real-time method and LS-SVM, fNIRS signals from actual and imagery finger tapping experiments are successfully classified. This method can achieve an average accuracy of 76% using a time window of only 0.4 seconds.

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