Status: Bibliographieeintrag
Standort: ---
Exemplare:
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| Online-Ressource |
Verfasst von: | Herff, Christian [VerfasserIn]  |
| Putze, Felix [VerfasserIn]  |
| Heger, Dominic [VerfasserIn]  |
| Schultz, Tanja [VerfasserIn]  |
Titel: | Speaking mode recognition from functional Near Infrared Spectroscopy |
Verf.angabe: | Christian Herff, Felix Putze, Dominic Heger, Cuntai Guan and Tanja Schultz |
E-Jahr: | 2012 |
Jahr: | 12 November 2012 |
Umfang: | 4 S. |
Fussnoten: | Gesehen am 30.08.2018 |
Titel Quelle: | Enthalten in: Annual international conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2012 |
Ort Quelle: | Piscataway, NJ : IEEE, 2012 |
Jahr Quelle: | 2012 |
Band/Heft Quelle: | (2012), Seite 1715-1718 |
ISBN Quelle: | 978-1-4577-1787-1 |
| 1-4244-4119-6 |
| 978-1-4244-4119-8 |
Abstract: | Speech is our most natural form of communication and even though functional Near Infrared Spectroscopy (fNIRS) is an increasingly popular modality for Brain Computer Interfaces (BCIs), there are, to the best of our knowledge, no previous studies on speech related tasks in fNIRS-based BCI. We conducted experiments on 5 subjects producing audible, silently uttered and imagined speech or do not produce any speech. For each of these speaking modes, we recorded fNIRS signals from the subjects performing these tasks and distinguish segments containing speech from those not containing speech, solely based on the fNIRS signals. Accuracies between 69% and 88% were achieved using support vector machines and a Mutual Information based Best Individual Feature approach. We are also able to discriminate the three speaking modes with 61% classification accuracy. We thereby demonstrate that speech is a very promising paradigm for fNIRS based BCI, as classification accuracies compare very favorably to those achieved in motor imagery BCIs with fNIRS. |
DOI: | doi:10.1109/EMBC.2012.6346279 |
URL: | Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.
DOI: https://doi.org/10.1109/EMBC.2012.6346279 |
Datenträger: | Online-Ressource |
Sprache: | eng |
Sach-SW: | Accuracy |
| Adult |
| audible speech |
| best individual feature approach |
| Brain |
| brain computer interface |
| brain-computer interfaces |
| Corpus Callosum |
| Electrodes |
| Feature extraction |
| functional near infrared spectroscopy |
| Hemodynamics |
| Humans |
| imagined speech |
| infrared spectra |
| Male |
| Motor Cortex |
| mutual information |
| Mutual information |
| silently uttered speech |
| speaking mode recognition |
| Spectroscopy |
| Spectroscopy, Near-Infrared |
| Speech |
| speech recognition |
| support vector machine |
| support vector machines |
K10plus-PPN: | 1580559239 |
Verknüpfungen: | → Sammelwerk |
Speaking mode recognition from functional Near Infrared Spectroscopy / Herff, Christian [VerfasserIn]; 12 November 2012 (Online-Ressource)
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