The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Classification of prefrontal activity due to mental arithmetic and music imagery using hidden Markov models and frequency domain near-infrared spectroscopy
Abstract
Near-infrared spectroscopy (NIRS) has recently been investigated as a non-invasive brain-computer interface (BCI). In particular, previous research has shown that NIRS signals recorded from the motor cortex during left- and right-hand imagery can be distinguished, providing a basis for a two-choice NIRS-BCI. In this study, we investigated the feasibility of an alternative two-choice NIRS-BCI paradigm based on the classification of prefrontal activity due to two cognitive tasks, specifically mental arithmetic and music imagery. Deploying a dual-wavelength frequency domain near-infrared spectrometer, we interrogated nine sites around the frontopolar locations (International 10-20 System) while ten able-bodied adults performed mental arithmetic and music imagery within a synchronous shape-matching paradigm. With the 18 filtered AC signals, we created task- and subject-specific maximum likelihood classifiers using hidden Markov models. Mental arithmetic and music imagery were classified with an average accuracy of 77.2% +/- 7.0 across participants, with all participants significantly exceeding chance accuracies. The results suggest the potential of a two-choice NIRS-BCI based on cognitive rather than motor tasks.
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Cites
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Cited by
fNIRS-based brain-computer interfaces: a review
Naseer, N., & Hong, K.-S. (2015) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2015.00003 · Cited by 988
Cui, X., Bryant, D. M., & Reiss, A. L. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.09.003 · Cited by 807
“…et al., 1996; Malonek et al., 1997; Schroeter et al., 2006; Toronov et al., 2003), non-invasive brain-computer interfaces (Coyle et al., 2004; 2007; Power et al., 2010; Sitaram et al., 2007; Utsugi et al., 2008), and brain activity in both active tasks and resting states (Boecker et al., 2007;…”
Social neuroscience and hyperscanning techniques: past, present and future.
Babiloni, F., & Astolfi, L. (2014) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2012.07.006 · Cited by 573
Open Access Dataset for EEG+NIRS Single-Trial Classification
Shin, J., von Luhmann, A., Blankertz, B., Kim, D.-W., Jeong, J., Hwang, H.-J., & Muller, K.-R. (2017) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2016.2628057 · Cited by 287
Mental stress assessment using simultaneous measurement of EEG and fNIRS
Al-Shargie, F., Kiguchi, M., Badruddin, N., Dass, S. C., Hani, A. F. M., & Tang, T. B. (2016) · Biomedical Optics Express · doi:10.1364/boe.7.003882 · Cited by 284
Metadata
- Authors
- Power, S. D., Falk, T. H., & Chau, T.
- Venue
- Journal of Neural Engineering
- Publisher
- IOP Publishing
- Published
- 2010-02-18
- Volume
- 7
- Issue
- 2
- Pages
- 026002
- ISSN
- 1741-2552 (ISSN-L)
- 1741-2560
- OpenAlex
- W2112686332
- Cited by
- 158
- References
- 5
- FWCI
- 9.05
- Type
- journal article
- Language
- en
- Open access
- closed
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- Power, S. D., Falk, T. H., & Chau, T. (2010). Classification of prefrontal activity due to mental arithmetic and music imagery using hidden Markov models and frequency domain near-infrared spectroscopy. Journal of Neural Engineering. https://doi.org/10.1088/1741-2560/7/2/026002
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