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dc.contributor.authorPérez Vidal, Alan
dc.contributor.authorGarcía Beltrán, Carlos Daniel
dc.contributor.authorMartínez Sibaja, Albino
dc.contributor.authorPosada Gómez, Rubén
dc.date.accessioned2022-06-30T15:39:28Z
dc.date.available2022-06-30T15:39:28Z
dc.date.issued2018-05-09
dc.identifier.citationPérez-Vidal, A. F., Garcia-Beltran, C. D., Martínez-Sibaja, A., & Posada-Gómez, R. (2018). Use of the stockwell transform in the detection of P300 evoked potentials with low-cost brain sensors. Sensors, 18(5), 1483.es
dc.identifier.issn1424-8220
dc.identifier.urihttp://repositorios.orizaba.tecnm.mx:8080/xmlui/handle/123456789/614
dc.description.abstractThe evoked potential is a neuronal activity that originates when a stimulus is presented. To achieve its detection, various techniques of brain signal processing can be used. One of the most studied evoked potentials is the P300 brain wave, which usually appears between 300 and 500 ms after the stimulus. Currently, the detection of P300 evoked potentials is of great importance due to its unique properties that allow the development of applications such as spellers, lie detectors, and diagnosis of psychiatric disorders. The present study was developed to demonstrate the usefulness of the Stockwell transform in the process of identifying P300 evoked potentials using a low-cost electroencephalography (EEG) device with only two brain sensors. The acquisition of signals was carried out using the Emotiv EPOC device—a wireless EEG headset. In the feature extraction, the Stockwell transform was used to obtain time-frequency information. The algorithms of linear discriminant analysis and a support vector machine were used in the classification process. The experiments were carried out with 10 participants; men with an average age of 25.3 years in good health. In general, a good performance (75–92%) was obtained in identifying P300 evoked potentials .es
dc.language.isoenes
dc.publisherMDPIes
dc.subjectP300 evoked potentialses
dc.subjectStockwell transformes
dc.subjectelectroencephalograpes
dc.subjectbrain-computer interfacees
dc.subjectnon-invasive brain sensorses
dc.subjectsignals processinges
dc.subjectwireless devicees
dc.titleUse of the Stockwell Transform in the Detection of P300 Evoked Potentials with Low-Cost Brain Sensorses
dc.typeArticlees


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