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    Wyświetlanie 1-3 z 3
    Tytuł:
    Improvement of performance of Japanese P300 speller by using second display
    Autorzy:
    Yamamoto, Y.
    Yoshikawa, T.
    Furuhashi, T.
    Powiązania:
    https://bibliotekanauki.pl/articles/91812.pdf
    Data publikacji:
    2015
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    brain computer interface
    BCI
    P300 speller
    interface
    communication
    P300
    ortografia
    podręcznik
    interfejs
    komunikacja
    Opis:
    Brain computer interface (BCI) is a system allows a user to control external devices or to communicate with other people using only his or her thoughts. The P300 speller is one such BCI in which users input letters. For inputting letters via the P300 speller, higher accuracy and shorter input times are needed, especially given densely populated display screens. We propose a new interface with a second display in the P300 speller that the user can switch to and from by selecting the “next” or “back” commands, therby reducing the density of displayed letters and improving the performance of the P300 speller. We show the comparison results in terms of accuracy and input times between the conventional interface and proposed interface.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2015, 5, 3; 221-226
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Convolutional neural networks for P300 signal detection applied to brain computer interface
    Autorzy:
    Riyad, Mouad
    Khalil, Mohammed
    Adib, Abdellah
    Powiązania:
    https://bibliotekanauki.pl/articles/2141900.pdf
    Data publikacji:
    2020
    Wydawca:
    Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
    Tematy:
    deep learning
    convolutional neural network
    brain computer interface
    P300
    classification
    Opis:
    A Brain‐Computer Interface (BCI) is an instrument capa‐ ble of commanding machine with brain signal. The mul‐ tiple types of signals allow designing many applications like the Oddball Paradigms with P300 signal. We propose an EEG classification system applied to BCI using the con‐ volutional neural network (ConvNet) for P300 problem. The system consists of three stages. The first stage is a Spatiotemporal convolutional layer which is a succession of temporal and spatial convolutions. The second stage contains 5 standard convolutional layers. Finally, a lo‐ gistic regression is applied to classify the input EEG sig‐ nal. The model includes Batch Normalization, Dropout, and Pooling. Also, It uses Exponential Linear Unit (ELU) function and L1‐L2 regularization to improve the lear‐ ning. For experiments, we use the database Dataset II of the BCI Competition III. As a result, we get an F1‐score of 53.26% which is higher than the BN3 model.
    Źródło:
    Journal of Automation Mobile Robotics and Intelligent Systems; 2020, 14, 4; 58-63
    1897-8649
    2080-2145
    Pojawia się w:
    Journal of Automation Mobile Robotics and Intelligent Systems
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Event-related potentials as an index of lost cognitive control and lost self in a TBI patient with duration increasing post-traumatic Delusional Misidentification Syndrome concluded with Cotard Syndrome
    Autorzy:
    Pąchalska, Maria
    Powiązania:
    https://bibliotekanauki.pl/articles/2106070.pdf
    Data publikacji:
    2019
    Wydawca:
    Fundacja Edukacji Medycznej, Promocji Zdrowia, Sztuki i Kultury Ars Medica
    Tematy:
    memory
    working autobiographic memory
    executive dysfunction
    delusional misidentification syndromes
    Cotard syndrome
    Capgras syndrome
    Fregoli syndrome
    P300
    N170
    Opis:
    The goal of the study was twofold: 1) to evaluate the QEEG/ ERPs indexes of functional brain impairment in a TBI patient diagnosed with chronic lost cognitive control and lost self caused by post traumatic, and here increasing over time, delusional misidentification syndrome concluded with Cotard syndrome in the blooming stage, with nihilistic delusions concerning the body and existence, and the delusion of being dead, and 2) to explore the mind of a patient whose identity has been disengaged, and who experiences the loss of his self and relations with his immediate surroundings with all the tragic consequences that entails. I herein present a 52-year-old patient, who – after a serious head injury due to a car accident 20 years ago, which re- sulted in focal injuries in the frontal and temporal areas of the right hemisphere – developed Cotard syndrome. After arousal from a 63-day coma and 98 days of post-traumatic amnesia, he manifested: (1) the loss of autobiographical memory, (2) a lost self, (3) forgotten family ties (including his lover). The study revealed that the patient’s cognitive control system is completely destroyed: no cognitive components have been found. Recall from memory has been completely disturbed (a low amplitude of N170). The two hemispheres work inco- herently with the right hemisphere revealing a serious delay in memory recall.
    Źródło:
    Acta Neuropsychologica; 2019, 17(4); 487-508
    1730-7503
    2084-4298
    Pojawia się w:
    Acta Neuropsychologica
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

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