Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Nattapong Thammasan"'
Autor:
Ivo V. Stuldreher, Alexandre Merasli, Nattapong Thammasan, Jan B. F. van Erp, Anne-Marie Brouwer
Publikováno v:
Frontiers in Neuroergonomics, Vol 2 (2022)
Research on brain signals as indicators of a certain attentional state is moving from laboratory environments to everyday settings. Uncovering the attentional focus of individuals in such settings is challenging because there is usually limited infor
Externí odkaz:
https://doaj.org/article/0292892a85dd417e8f80714a1ba0d397
Publikováno v:
Frontiers in Computer Science, Vol 3 (2022)
To enable virtual reality exposure therapy (VRET) that treats anxiety disorders by gradually exposing the patient to fear using virtual reality (VR), it is important to monitor the patient's fear levels during the exposure. Despite the evidence of a
Externí odkaz:
https://doaj.org/article/aa27df068bb34f15bd8b5bd2559956a0
Publikováno v:
Frontiers in Computer Science, Vol 3 (2021)
At vital moments in professional soccer matches, penalties were often missed. Psychological factors, such as anxiety and pressure, are among the critical causes of the mistakes, commonly known as choking under pressure. Nevertheless, the factors have
Externí odkaz:
https://doaj.org/article/c23140bb155a4b24b08dbaeca7ebbc1f
Publikováno v:
Frontiers in Neuroscience, Vol 14 (2020)
Interpersonal physiological synchrony (PS), or the similarity of physiological signals between individuals over time, may be used to detect attentionally engaging moments in time. We here investigated whether PS in the electroencephalogram (EEG), ele
Externí odkaz:
https://doaj.org/article/306aa6cd3407483f870fce581dea50fa
A Comparative Study of Window Size and Channel Arrangement on EEG-Emotion Recognition Using Deep CNN
Publikováno v:
Sensors, Vol 21, Iss 5, p 1678 (2021)
Emotion recognition based on electroencephalograms has become an active research area. Yet, identifying emotions using only brainwaves is still very challenging, especially the subject-independent task. Numerous studies have tried to propose methods
Externí odkaz:
https://doaj.org/article/16f2f1de4f66485280126c1b1c9b99ae
Autor:
Nattapong Thammasan, Makoto Miyakoshi
Publikováno v:
Sensors, Vol 20, Iss 24, p 7040 (2020)
Magneto-/Electro-encephalography (M/EEG) commonly uses (fast) Fourier transformation to compute power spectral density (PSD). However, the resulting PSD plot lacks temporal information, making interpretation sometimes equivocal. For example, consider
Externí odkaz:
https://doaj.org/article/f99ecebeb6634d6cb3ff834c41388f74
Autor:
Nattapong Thammasan, Ivo V. Stuldreher, Elisabeth Schreuders, Matteo Giletta, Anne-Marie Brouwer
Publikováno v:
Sensors, Vol 20, Iss 18, p 5380 (2020)
Measuring psychophysiological signals of adolescents using unobtrusive wearable sensors may contribute to understanding the development of emotional disorders. This study investigated the feasibility of measuring high quality physiological data and e
Externí odkaz:
https://doaj.org/article/71de8529f2a14904bb37957b3cfc7161
Autor:
Mannes Poel, Anne-Marie Brouwer, Ivo V. Stuldreher, Nattapong Thammasan, Dagmar Wismeijer, Jan B. F. van Erp
Publikováno v:
2019 8th International Conference on Affective Computing and Intelligent Interaction, ACII 2019, 371-377
STARTPAGE=371;ENDPAGE=377;TITLE=2019 8th International Conference on Affective Computing and Intelligent Interaction, ACII 2019
2019 8th International Conference on Affective Computing and Intelligent Interaction (ACII), 371-377
ACII
STARTPAGE=371;ENDPAGE=377;TITLE=2019 8th International Conference on Affective Computing and Intelligent Interaction, ACII 2019
2019 8th International Conference on Affective Computing and Intelligent Interaction (ACII), 371-377
ACII
Skin conductance or electrodermal activity (EDA) has been shown to be a reliable indicator of emotional arousal. With the current development to record EDA with wearable sensors attached to individuals who freely move around, detecting EDA artefacts
A Comparative Study of Window Size and Channel Arrangement on EEG-Emotion Recognition Using Deep CNN
Publikováno v:
Sensors, Vol 21, Iss 1678, p 1678 (2021)
Sensors (Basel, Switzerland)
Sensors
Volume 21
Issue 5
Sensors (Switzerland), 21(5):1678, 1-19. MDPI
Sensors (Basel, Switzerland)
Sensors
Volume 21
Issue 5
Sensors (Switzerland), 21(5):1678, 1-19. MDPI
Emotion recognition based on electroencephalograms has become an active research area. Yet, identifying emotions using only brainwaves is still very challenging, especially the subject-independent task. Numerous studies have tried to propose methods
Publikováno v:
Frontiers in Neuroscience, 14:575521. Frontiers Research Foundation
Frontiers in Neuroscience
Frontiers in Neuroscience, Vol 14 (2020)
Frontiers in Neuroscience
Frontiers in Neuroscience, Vol 14 (2020)
Interpersonal physiological synchrony (PS), or the similarity of physiological signals between individuals over time, may be used to detect attentionally engaging moments in time. We here investigated whether PS in the electroencephalogram (EEG), ele
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0c06c3036c29088e209d7ba4079940ca
https://research.utwente.nl/en/publications/0a10a4d9-5ae5-47f1-a59c-4298e3452da6
https://research.utwente.nl/en/publications/0a10a4d9-5ae5-47f1-a59c-4298e3452da6