Human fNIRS: right-hand, left-hand and foot tapping, a person left out at a time
Bak et al. fNIRS finger- and foot-tapping dataset: fNIRS results
The open-access fNIRS dataset for classification of unilateral finger- and foot-tapping (figshare 9783755) holds functional near-infrared spectroscopy from 30 volunteers performing right-hand finger tapping, left-hand finger tapping and foot tapping, 25 trials of each, recorded with a three-wavelength multichannel system (LIGHTNIRS, Shimadzu) with eight sources and eight detectors placed around C3 and C4. Released by Sujin Bak, Jinwoo Park, Jaeyoung Shin and Jichai Jeong (Korea University and Wonkwang University) under CC BY 4.0 and described in Electronics (2019). The supplied oxy- and deoxyhemoglobin series of all 30 participants are used here.
Also known asOpen Access fNIRS Dataset for Classification of Unilateral Finger- and Foot-Tapping · figshare 9783755 · fNIRS dataset for ternary classification · Bak et al. (2019)
A person left out of training · executed tapping, not motor imagery
Balanced accuracy
66.8%60.6%–72.9%Each person’s balanced accuracy, averaged with equal weight. Class recall over all held-out trials: right hand 69.2%, left hand 63.6%, foot 67.7%. The interval resamples the fixed participant scores (2,000 draws): not a refit bootstrap and not a clinical confidence interval.
30
Training priorreference or comparator, not a decoding model
A person left out of training · executed tapping, not motor imagery
Balanced accuracy
33.3%Predicts the same class every time: no interval, because every person gets the same score.
30
Offline, from the supplied oxy- and deoxyhemoglobin series over a window after each task onset. Task-correlated systemic or motion effects are not excluded, so this shows neither a brain-only signal nor cortical localisation. This site’s own protocol: it does not reproduce the authors’ within-person scores, and it is not compared with any scalp EEG result.
Source and licence
Bak et al. fNIRS finger- and foot-tapping dataset
CreditSujin Bak, Jinwoo Park, Jaeyoung Shin and Jichai Jeong · Open Access fNIRS Dataset for Classification of Unilateral Finger- and Foot-Tapping, figshare, doi:10.6084/m9.figshare.9783755.v2, CC BY 4.0. Paper: Sujin Bak, Jinwoo Park, Jaeyoung Shin and Jichai Jeong, Open-Access fNIRS Dataset for Classification of Unilateral Finger- and Foot-Tapping, Electronics 8(12), 1486 (2019), doi:10.3390/electronics8121486. Derived analysis by BCI Report; not endorsed by the authors.
BCI Report does not redistribute any recording. These are aggregate measurements computed by BCI Report under the licence above; the data remain their creators’.
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