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Journal articles on the topic 'Audio-EEG analysis'

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1

Reddy Katthi, Jaswanth, and Sriram Ganapathy. "Deep Correlation Analysis for Audio-EEG Decoding." IEEE Transactions on Neural Systems and Rehabilitation Engineering 29 (2021): 2742–53. http://dx.doi.org/10.1109/tnsre.2021.3129790.

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Geng, Bingrui, Ke Liu, and Yiping Duan. "Human Perception Intelligent Analysis Based on EEG Signals." Electronics 11, no. 22 (2022): 3774. http://dx.doi.org/10.3390/electronics11223774.

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The research on brain cognition provides theoretical support for intelligence and cognition in computational intelligence, and it is further applied in various fields of scientific and technological innovation, production and life. Use of the 5G network and intelligent terminals has also brought diversified experiences to users. This paper studies human perception and cognition in the quality of experience (QoE) through audio noise. It proposes a novel method to study the relationship between human perception and audio noise intensity using electroencephalogram (EEG) signals. This kind of phys
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Dasenbrock, Steffen, Sarah Blum, Stefan Debener, Volker Hohmann, and Hendrik Kayser. "A Step towards Neuro-Steered Hearing Aids: Integrated Portable Setup for Time- Synchronized Acoustic Stimuli Presentation and EEG Recording." Current Directions in Biomedical Engineering 7, no. 2 (2021): 855–58. http://dx.doi.org/10.1515/cdbme-2021-2218.

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Abstract Aiming to provide a portable research platform to develop algorithms for neuro-steered hearing aids, a joint hearing aid - EEG measurement setup was implemented in this work. The setup combines the miniaturized electroencephalography sensor technology cEEGrid with a portable hearing aid research platform - the Portable Hearing Laboratory. The different components of the system are connected wirelessly, using the lab streaming layer framework for synchronization of audio and EEG data streams. Our setup was shown to be suitable for simultaneous recording of audio and EEG signals used in
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Lee, Yi Yeh, Aaron Raymond See, Shih Chung Chen, and Chih Kuo Liang. "Effect of Music Listening on Frontal EEG Asymmetry." Applied Mechanics and Materials 311 (February 2013): 502–6. http://dx.doi.org/10.4028/www.scientific.net/amm.311.502.

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Frontal EEG asymmetry has been recognized as a useful method in determining emotional states and psychophysiological conditions. For the current research, resting prefrontal EEG was measured before, during and after listening to sad music video. Data were recorded and analyzed using a wireless EEG module with digital results sent via Bluetooth to a remote computer for further analysis. The relative alpha power was utilized to determine EEG asymmetry indexes. The results indicated that even if a person had a stronger right hemisphere in the initial phase a significant shift first occurred durin
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Hadjidimitriou, Stelios K., Asteris I. Zacharakis, Panagiotis C. Doulgeris, Konstantinos J. Panoulas, Leontios J. Hadjileontiadis, and Stavros M. Panas. "Revealing Action Representation Processes in Audio Perception Using Fractal EEG Analysis." IEEE Transactions on Biomedical Engineering 58, no. 4 (2011): 1120–29. http://dx.doi.org/10.1109/tbme.2010.2047016.

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Reshetnykov, Denys S. "EEG Analysis of Person Familiarity with Audio-Video Data Assessing Task." Upravlâûŝie sistemy i mašiny, no. 4 (276) (August 2018): 70–83. http://dx.doi.org/10.15407/usim.2018.04.070.

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7

Kumar, Himanshu, Subha D. Puthankattil, and Ramakrishnan Swaminathan. "ANALYSIS OF EEG RESPONSE FOR AUDIO-VISUAL STIMULI IN FRONTAL ELECTRODES AT THETA FREQUENCY BAND USING THE TOPOLOGICAL FEATURES." Biomedical Sciences Instrumentation 57, no. 2 (2021): 333–39. http://dx.doi.org/10.34107/yhpn9422.04333.

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Emotions are the fundamental intellectual capacity of humans characterized by perception, attention, and behavior. Emotions are characterized by psychophysiological expressions. Studies have been performed by analyzing Electroencephalogram (EEG) responses from various lobes of the brain under all frequency bands. In this work, the EEG response of the theta band in the frontal lobe is analyzed extracting topological features during audio-visual stimulation. This study is carried out using the EEG signals from the public domain database. In this method, the signals are projected in higher dimens
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Ribeiro, Estela, and Carlos Eduardo Thomaz. "A Whole Brain EEG Analysis of Musicianship." Music Perception 37, no. 1 (2019): 42–56. http://dx.doi.org/10.1525/mp.2019.37.1.42.

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The neural activation patterns provoked in response to music listening can reveal whether a subject did or did not receive music training. In the current exploratory study, we have approached this two-group (musicians and nonmusicians) classification problem through a computational framework composed of the following steps: Acoustic features extraction; Acoustic features selection; Trigger selection; EEG signal processing; and Multivariate statistical analysis. We are particularly interested in analyzing the brain data on a global level, considering its activity registered in electroencephalog
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9

Gao, Chenguang, Hirotaka Uchitomi, and Yoshihiro Miyake. "Influence of Multimodal Emotional Stimulations on Brain Activity: An Electroencephalographic Study." Sensors 23, no. 10 (2023): 4801. http://dx.doi.org/10.3390/s23104801.

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This study aimed to reveal the influence of emotional valence and sensory modality on neural activity in response to multimodal emotional stimuli using scalp EEG. In this study, 20 healthy participants completed the emotional multimodal stimulation experiment for three stimulus modalities (audio, visual, and audio-visual), all of which are from the same video source with two emotional components (pleasure or unpleasure), and EEG data were collected using six experimental conditions and one resting state. We analyzed power spectral density (PSD) and event-related potential (ERP) components in r
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Lee, Tae-Ju, Seung-Min Park, and Kwee-Bo Sim. "Electroencephalography Signal Grouping and Feature Classification Using Harmony Search for BCI." Journal of Applied Mathematics 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/754539.

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This paper presents a heuristic method for electroencephalography (EEG) grouping and feature classification using harmony search (HS) for improving the accuracy of the brain-computer interface (BCI) system. EEG, a noninvasive BCI method, uses many electrodes on the scalp, and a large number of electrodes make the resulting analysis difficult. In addition, traditional EEG analysis cannot handle multiple stimuli. On the other hand, the classification method using the EEG signal has a low accuracy. To solve these problems, we use a heuristic approach to reduce the complexities in multichannel pro
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11

Zhou, Tie Hua, Wenlong Liang, Hangyu Liu, Ling Wang, Keun Ho Ryu, and Kwang Woo Nam. "EEG Emotion Recognition Applied to the Effect Analysis of Music on Emotion Changes in Psychological Healthcare." International Journal of Environmental Research and Public Health 20, no. 1 (2022): 378. http://dx.doi.org/10.3390/ijerph20010378.

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Music therapy is increasingly being used to promote physical health. Emotion semantic recognition is more objective and provides direct awareness of the real emotional state based on electroencephalogram (EEG) signals. Therefore, we proposed a music therapy method to carry out emotion semantic matching between the EEG signal and music audio signal, which can improve the reliability of emotional judgments, and, furthermore, deeply mine the potential influence correlations between music and emotions. Our proposed EER model (EEG-based Emotion Recognition Model) could identify 20 types of emotions
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12

Andrusiak, V., and V. Kravchenko. "Comparative EEG analysis of learning effectiveness using paper books, e-books, and audio books." Bulletin of Taras Shevchenko National University of Kyiv. Series: Biology 74, no. 2 (2017): 39–46. http://dx.doi.org/10.17721/1728_2748.2017.74.39-46.

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In this work the peculiarities of reading comprehension from electronic, audio devices and hard copies were studied through comparative analysis of the learning accuracy and electrical activity of the brain when reading or listening to the text. Eighty students took part in the research. They were offered 2 passages of text from fiction and popular-scientific literature for reading, presented in a form of an e-book, MP3-format and in a printed copy. The level of comprehension and assimilation of the read material was checked by testing based on the content of the text immediately after reading
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13

Chen, Wei, and Guobin Wu. "A Multimodal Convolutional Neural Network Model for the Analysis of Music Genre on Children’s Emotions Influence Intelligence." Computational Intelligence and Neuroscience 2022 (August 29, 2022): 1–11. http://dx.doi.org/10.1155/2022/5611456.

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This paper designs a multimodal convolutional neural network model for the intelligent analysis of the influence of music genres on children’s emotions by constructing a multimodal convolutional neural network model and profoundly analyzing the impact of music genres on children’s feelings. Considering the diversity of music genre features in the audio power spectrogram, the Mel filtering method is used in the feature extraction stage to ensure the effective retention of the genre feature attributes of the audio signal by dimensional reduction of the Mel filtered signal, deepening the differen
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14

Bischoff, M., H. Gebhardt, CR Blecker, K. Zentgraf, D. Vaitl, and G. Sammer. "EEG-guided fMRI-analysis reveals involvement of the superior temporal sulcus in audio-visual binding." NeuroImage 47 (July 2009): S130. http://dx.doi.org/10.1016/s1053-8119(09)71270-4.

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15

Masood, Naveen, and Humera Farooq. "Investigating EEG Patterns for Dual-Stimuli Induced Human Fear Emotional State." Sensors 19, no. 3 (2019): 522. http://dx.doi.org/10.3390/s19030522.

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Most electroencephalography (EEG) based emotion recognition systems make use of videos and images as stimuli. Few used sounds, and even fewer studies were found involving self-induced emotions. Furthermore, most of the studies rely on single stimuli to evoke emotions. The question of “whether different stimuli for same emotion elicitation generate any subject-independent correlations” remains unanswered. This paper introduces a dual modality based emotion elicitation paradigm to investigate if emotions can be classified induced with different stimuli. A method has been proposed based on common
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16

Sokhadze, E. M., B. Hillard, M. Eng, A. S. El-Baz, A. Tasman, and L. Sears. "ELECTROENCEPHALOGRAPHIC BIOFEEDBACK IMPROVES FOCUSED ATTENTION IN ATTENTION DEFICIT/HYPERACTIVITY DISORDER." Bulletin of Siberian Medicine 12, no. 2 (2013): 182–94. http://dx.doi.org/10.20538/1682-0363-2013-2-182-194.

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EEG biofeedback (so called neurofeedback) is considered as an efficacious treatment for ADHD. We propose that operant conditioning of EEG in neurofeedback training mode, aimed to mitigate inattention and low arousal in ADHD, will be accompanied by changes in EEG bands' relative power. Patients were 18 children diagnosed with ADHD. The neurofeedback protocol (“Focus/Alertness” by Peak Achievement Trainer, Neurotek, KY) used to train patients has focused attention training procedure, which according to specifications, represents wide band EEG amplitude suppression training. Quantitative EEG anal
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17

Browarska, Natalia, Aleksandra Kawala-Sterniuk, Jaroslaw Zygarlicki, et al. "Comparison of Smoothing Filters’ Influence on Quality of Data Recorded with the Emotiv EPOC Flex Brain–Computer Interface Headset during Audio Stimulation." Brain Sciences 11, no. 1 (2021): 98. http://dx.doi.org/10.3390/brainsci11010098.

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Off-the-shelf, consumer-grade EEG equipment is nowadays becoming the first-choice equipment for many scientists when it comes to recording brain waves for research purposes. On one hand, this is perfectly understandable due to its availability and relatively low cost (especially in comparison to some clinical-level EEG devices), but, on the other hand, quality of the recorded signals is gradually increasing and reaching levels that were offered just a few years ago by much more expensive devices used in medicine for diagnostic purposes. In many cases, a well-designed filter and/or a well-thoug
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18

Cui, Gao Chao, and Jian Ting Cao. "P300 Oddball Task and Classification Based on Support Vector Machine for BCI System." Applied Mechanics and Materials 397-400 (September 2013): 2187–90. http://dx.doi.org/10.4028/www.scientific.net/amm.397-400.2187.

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The P300 oddball task is the most popular paradigm in the existing BCI systems. Recently using auditory stimuli in P300 oddball task arises since it gives much freedom to the BCI user. In this paper, we present a novel BCI paradigm using P300 and P100 responses. Since P300 and P100 responses occur in the frontal lobe and the temporal lobe respectively, so that we can use these responses stimulated by an audio in a single task. The main advantage of our designed paradigm is that we can obtain two different kinds of responses in a single trial EEG task. In the EEG data analysis, we first employ
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19

Giroldini, William, Luciano Pederzoli, Marco Bilucaglia, et al. "EEG correlates of social interaction at distance." F1000Research 4 (August 3, 2015): 457. http://dx.doi.org/10.12688/f1000research.6755.1.

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This study investigated EEG correlates of social interaction at distance between twenty-five pairs of participants who were not connected by any traditional channels of communication.Each session involved the application of 128 stimulations separated by intervals of random duration ranging from 4 to 6 seconds. One of the pair received a one-second stimulation from a light signal produced by an arrangement of red LEDs, and a simultaneous 500 Hz sinusoidal audio signal of the same length. The other member of the pair sat in an isolated sound-proof room, such that any sensory interaction between
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Giroldini, William, Luciano Pederzoli, Marco Bilucaglia, et al. "EEG correlates of social interaction at distance." F1000Research 4 (November 9, 2015): 457. http://dx.doi.org/10.12688/f1000research.6755.2.

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This study investigated EEG correlates of social interaction at distance between twenty-five pairs of participants who were not connected by any traditional channels of communication.Each session involved the application of 128 stimulations separated by intervals of random duration ranging from 4 to 6 seconds. One of the pair received a one-second stimulation from a light signal produced by an arrangement of red LEDs, and a simultaneous 500 Hz sinusoidal audio signal of the same length. The other member of the pair sat in an isolated sound-proof room, such that any sensory interaction between
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21

Giroldini, William, Luciano Pederzoli, Marco Bilucaglia, et al. "EEG correlates of social interaction at distance." F1000Research 4 (January 14, 2016): 457. http://dx.doi.org/10.12688/f1000research.6755.3.

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This study investigated EEG correlates of social interaction at distance between twenty-five pairs of participants who were not connected by any traditional channels of communication.Each session involved the application of 128 stimulations separated by intervals of random duration ranging from 4 to 6 seconds. One of the pair received a one-second stimulation from a light signal produced by an arrangement of red LEDs, and a simultaneous 500 Hz sinusoidal audio signal of the same length. The other member of the pair sat in an isolated sound-proof room, such that any sensory interaction between
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22

Giroldini, William, Luciano Pederzoli, Marco Bilucaglia, et al. "EEG correlates of social interaction at distance." F1000Research 4 (February 2, 2016): 457. http://dx.doi.org/10.12688/f1000research.6755.4.

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This study investigated EEG correlates of social interaction at distance between twenty-five pairs of participants who were not connected by any traditional channels of communication.Each session involved the application of 128 stimulations separated by intervals of random duration ranging from 4 to 6 seconds. One of the pair received a one-second stimulation from a light signal produced by an arrangement of red LEDs, and a simultaneous 500 Hz sinusoidal audio signal of the same length. The other member of the pair sat in an isolated sound-proof room, such that any sensory interaction between
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23

Giroldini, William, Luciano Pederzoli, Marco Bilucaglia, et al. "EEG correlates of social interaction at distance." F1000Research 4 (February 10, 2016): 457. http://dx.doi.org/10.12688/f1000research.6755.5.

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This study investigated EEG correlates of social interaction at distance between twenty-five pairs of participants who were not connected by any traditional channels of communication.Each session involved the application of 128 stimulations separated by intervals of random duration ranging from 4 to 6 seconds. One of the pair received a one-second stimulation from a light signal produced by an arrangement of red LEDs, and a simultaneous 500 Hz sinusoidal audio signal of the same length. The other member of the pair sat in an isolated sound-proof room, such that any sensory interaction between
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24

Rajashekhar, U., and Neelappa Neelappa. "Development of Automated BCI System to Assist the Physically Challenged Person Through Audio Announcement With Help of EEG Signal." WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL 16 (May 26, 2021): 302–14. http://dx.doi.org/10.37394/23203.2021.16.26.

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Individuals face numerous challenges with many disorders, particularly when multiple disfunctions are diagnosed and especially for visually effected wheelchair users. This scenario, in reality creates in a degree of incapacity on the part of the wheelchair user in terms of performing simple activities. Based on their specific medical needs confined patients are treated in a modified method. Independent navigation is secured for individuals with vision and motor disabilities. There is a necessity for communication which justifies the use of virtual reality (VR) in this navigation situation. For
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Puchkova, A. N., O. N. Tkachenko, I. P. Trapeznikov, et al. "Assessment of potential capabilities of Dreem: An ambulatory device for EEG phase-locked acoustic stimulation during sleep." SOCIALNO-ECOLOGICHESKIE TECHNOLOGII 9, no. 1 (2019): 96–112. http://dx.doi.org/10.31862/2500-2961-2019-9-1-96-112.

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Sleep disorders are one of the significant problems in the modern society. Current research is on the lookout for the nonpharmacological ways to improve sleep quality and slow wave brain activity that plays a crucial role in homeostasis and cognitive functions. One of the promising approaches is acoustic stimulation that is phase-locked to deep sleep EEG rhythms. It was already shown that such stimulation improves slow wave brain activity. This article describes Dreem: a wireless consumer device that performs acoustic sleep stimulation in home conditions. The device has dry EEG electrodes, pho
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Davis, Jeffrey Jonathan (Joshua), Chin-Teng Lin, Grant Gillett, and Robert Kozma. "An Integrative Approach to Analyze Eeg Signals and Human Brain Dynamics in Different Cognitive States." Journal of Artificial Intelligence and Soft Computing Research 7, no. 4 (2017): 287–99. http://dx.doi.org/10.1515/jaiscr-2017-0020.

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Abstract Electroencephalograph (EEG) data provide insight into the interconnections and relationships between various cognitive states and their corresponding brain dynamics, by demonstrating dynamic connections between brain regions at different frequency bands. While sensory input tends to stimulate neural activity in different frequency bands, peaceful states of being and self-induced meditation tend to produce activity in the mid-range (Alpha). These studies were conducted with the aim of: (a) testing different equipment in order to assess two (2) different EEG technologies together with t
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Kimmatkar, Nisha Vishnupant, and B. Vijaya Babu. "Novel Approach for Emotion Detection and Stabilizing Mental State by Using Machine Learning Techniques." Computers 10, no. 3 (2021): 37. http://dx.doi.org/10.3390/computers10030037.

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The aim of this research study is to detect emotional state by processing electroencephalography (EEG) signals and test effect of meditation music therapy to stabilize mental state. This study is useful to identify 12 subtle emotions angry (annoying, angry, nervous), calm (calm, peaceful, relaxed), happy (excited, happy, pleased), sad (sleepy, bored, sad). A total 120 emotion signals were collected by using Emotive 14 channel EEG headset. Emotions are elicited by using three types of stimulus thoughts, audio and video. The system is trained by using captured database of emotion signals which i
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Chen, Qicheng, and Boon Giin Lee. "Deep Learning Models for Stress Analysis in University Students: A Sudoku-Based Study." Sensors 23, no. 13 (2023): 6099. http://dx.doi.org/10.3390/s23136099.

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Due to the phenomenon of “involution” in China, the current generation of college and university students are experiencing escalating levels of stress, both academically and within their families. Extensive research has shown a strong correlation between heightened stress levels and overall well-being decline. Therefore, monitoring students’ stress levels is crucial for improving their well-being in educational institutions and at home. Previous studies have primarily focused on recognizing emotions and detecting stress using physiological signals like ECG and EEG. However, these studies often
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Masood, Naveen, and Humera Farooq. "Comparing Neural Correlates of Human Emotions across Multiple Stimulus Presentation Paradigms." Brain Sciences 11, no. 6 (2021): 696. http://dx.doi.org/10.3390/brainsci11060696.

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Most electroencephalography (EEG)-based emotion recognition systems rely on a single stimulus to evoke emotions. These systems make use of videos, sounds, and images as stimuli. Few studies have been found for self-induced emotions. The question “if different stimulus presentation paradigms for same emotion, produce any subject and stimulus independent neural correlates” remains unanswered. Furthermore, we found that there are publicly available datasets that are used in a large number of studies targeting EEG-based human emotional state recognition. Since one of the major concerns and contrib
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Sahni, Pooja, and Jyoti Kumar. "Effect of Nature Experience on Fronto-Parietal Correlates of Neurocognitive Processes Involved in Directed Attention: An ERP Study." Annals of Neurosciences 27, no. 3-4 (2020): 136–47. http://dx.doi.org/10.1177/0972753121990143.

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Background: Several studies have demonstrated that brief interactions with natural environments can improve cognitive functioning. However, the neurocognitive processes that are affected by natural surroundings are not yet fully understood. It is argued that the “elements” in natural environment evoke “effortless” involuntary attention and may affect the neural mechanisms underlying inhibition control central to directed attention. Methods: The present study used electroencephalography (EEG) to investigate the effects of nature experience on neurocognitive processes involved in directed attent
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Shah, Syed Yaseen, Hadi Larijani, Ryan M. Gibson, and Dimitrios Liarokapis. "Random Neural Network Based Epileptic Seizure Episode Detection Exploiting Electroencephalogram Signals." Sensors 22, no. 7 (2022): 2466. http://dx.doi.org/10.3390/s22072466.

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Epileptic seizures are caused by abnormal electrical activity in the brain that manifests itself in a variety of ways, including confusion and loss of awareness. Correct identification of epileptic seizures is critical in the treatment and management of patients with epileptic disorders. One in four patients present resistance against seizures episodes and are in dire need of detecting these critical events through continuous treatment in order to manage the specific disease. Epileptic seizures can be identified by reliably and accurately monitoring the patients’ neuro and muscle activities, c
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Wei, Wei, Qingxuan Jia, Yongli Feng, and Gang Chen. "Emotion Recognition Based on Weighted Fusion Strategy of Multichannel Physiological Signals." Computational Intelligence and Neuroscience 2018 (July 5, 2018): 1–9. http://dx.doi.org/10.1155/2018/5296523.

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Emotion recognition is an important pattern recognition problem that has inspired researchers for several areas. Various data from humans for emotion recognition have been developed, including visual, audio, and physiological signals data. This paper proposes a decision-level weight fusion strategy for emotion recognition in multichannel physiological signals. Firstly, we selected four kinds of physiological signals, including Electroencephalography (EEG), Electrocardiogram (ECG), Respiration Amplitude (RA), and Galvanic Skin Response (GSR). And various analysis domains have been used in physi
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Abdul Halim, S. F., S. A. Awang, and S. Mohamaddan. "An Investigation of Brain Signal Characteristics between Hafiz/Hafizah Subjects and Non-Hafiz/Hafizah Subjects." Journal of Physics: Conference Series 2071, no. 1 (2021): 012037. http://dx.doi.org/10.1088/1742-6596/2071/1/012037.

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Abstract Tahfiz education has gain its popularity among Malaysians thus expand the circle of hafiz and hafizah all over the country. This study has been done to investigate effect of memorizing Al-Quran by determining the difference between hafiz/hafizah subjects and non-hafiz/hafizah subjects in terms of their focus using brain signal characteristics. 10 subjects (5 hafiz/hafizah and 5 non-hafiz/hafizah) have been participated in this study. Database of EEG was recorded by using EegoSport (ANT Neuro, ES-230, The Netherlands) while listening no music, rock music, instrumental music and Al-Qura
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Basu, Medha, SHANKHA SANYAL, Archi Banerjee, Kumardeb Banerjee, and Dipak Ghosh. "Does musical training affect neuro-cognition of emotions? An EEG study with instrumental Indian classical music." Journal of the Acoustical Society of America 151, no. 4 (2022): A60. http://dx.doi.org/10.1121/10.0010655.

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Music across all genres evokes a variety of emotions, irrespective of its timbre and tempo. Indian classical music (ICM) is no exception. Although being biased towards vocal musical styles, instrumental music forms one broad section of ICM. In this study, we have tried to compare the neural responses of music practitioners and non-musicians towards different emotions using audio clips from two popular plucked string instruments used in ICM, Sitar and Sarod. From pre-recorded performances of two eminent maestros, 20 clips of approximately 30 s duration were selected from the Alaap sections (ini
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Mercier, Manuel R., John J. Foxe, Ian C. Fiebelkorn, John S. Butler, Theodore H. Schwartz, and Sophie Molholm. "Auditory modulation of oscillatory activity in extra-striate visual cortex and its contribution to audio–visual multisensory integration: A human intracranial EEG study." Seeing and Perceiving 25 (2012): 198. http://dx.doi.org/10.1163/187847612x648279.

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Investigations have traditionally focused on activity in the sensory cortices as a function of their respective sensory inputs. However, converging evidence from multisensory research has shown that neural activity in a given sensory region can be modulated by stimulation of other so-called ancillary sensory systems. Both electrophysiology and functional imaging support the occurrence of multisensory processing in human sensory cortex based on the latency of multisensory effects and their precise anatomical localization. Still, due to inherent methodological limitations, direct evidence of the
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Tardón, Lorenzo J., Ignacio Rodríguez-Rodríguez, Niels T. Haumann, Elvira Brattico, and Isabel Barbancho. "Music with Concurrent Saliences of Musical Features Elicits Stronger Brain Responses." Applied Sciences 11, no. 19 (2021): 9158. http://dx.doi.org/10.3390/app11199158.

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Brain responses are often studied under strictly experimental conditions in which electroencephalograms (EEGs) are recorded to reflect reactions to short and repetitive stimuli. However, in real life, aural stimuli are continuously mixed and cannot be found isolated, such as when listening to music. In this audio context, the acoustic features in music related to brightness, loudness, noise, and spectral flux, among others, change continuously; thus, significant values of these features can occur nearly simultaneously. Such situations are expected to give rise to increased brain reaction with
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Ajenaghughrure, Ighoyota Ben, Sonia Da Costa Sousa, and David Lamas. "Measuring Trust with Psychophysiological Signals: A Systematic Mapping Study of Approaches Used." Multimodal Technologies and Interaction 4, no. 3 (2020): 63. http://dx.doi.org/10.3390/mti4030063.

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Trust plays an essential role in all human relationships. However, measuring trust remains a challenge for researchers exploring psychophysiological signals. Therefore, this article aims to systematically map the approaches used in studies assessing trust with psychophysiological signals. In particular, we examine the numbers and frequency of combined psychophysiological signals, the primary outcomes of previous studies, and the types and most commonly used data analysis techniques for analyzing psychophysiological data to infer a trust state. For this purpose, we employ a systematic mapping r
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Jeon, Jin Yong, Haram Lee, and Yunjin Lee. "Psychophysiological effect according to restoration factors of audio-visual environment." Journal of the Acoustical Society of America 152, no. 4 (2022): A128. http://dx.doi.org/10.1121/10.0015776.

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This study investigated the effects of psychophysiological restoration due to environmental factors while experiencing the city, waterfront, and green space using various psychological scales and physiological measurement tools. The environment was experienced using virtual reality technology, and the subjects' responses were collected through surveys and EEG (electroencephalography) and HRV (heart rate variability) measurement. HRV responses were carried out by parameters such as total power (TP), SDNN and TSI. In case of EEG, PSD (power spectrum density) analysis indicated a relatively high
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Samadiani, Huang, Cai, et al. "A Review on Automatic Facial Expression Recognition Systems Assisted by Multimodal Sensor Data." Sensors 19, no. 8 (2019): 1863. http://dx.doi.org/10.3390/s19081863.

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Facial Expression Recognition (FER) can be widely applied to various research areas, such as mental diseases diagnosis and human social/physiological interaction detection. With the emerging advanced technologies in hardware and sensors, FER systems have been developed to support real-world application scenes, instead of laboratory environments. Although the laboratory-controlled FER systems achieve very high accuracy, around 97%, the technical transferring from the laboratory to real-world applications faces a great barrier of very low accuracy, approximately 50%. In this survey, we comprehen
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Mortazavi, Mo, David Oakley, Jon Minor, Prem Kumar Thirunagari, Nassar Koucheki, and Nitin Prabhaker. "FUNCTIONAL NEUROCOGNITIVE DEFICITS AND CORTICAL EVOKED POTENTIALS IN PEDIATRIC PATIENTS WITH PROLONGED POST CONCUSSIVE SYMPTOMS." Orthopaedic Journal of Sports Medicine 8, no. 4_suppl3 (2020): 2325967120S0026. http://dx.doi.org/10.1177/2325967120s00261.

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Background: Prolonged neurophysiological impairments have been demonstrated after brain injury utilizing tools such as auditory evoked response potentials. The objectivity and sensitivity of such tools can provide clinicians a unique perspective on patients with prolonged post concussive symptoms (PPCS), and help determine optimal management strategies. Limited research currently exists on evoked potentials and pediatric PPCS. Purpose: Illustrate the clinical utility of abnormal evoked potentials in adolescents with PPCS. Methods and Study Design: The study is a retrospective cross-sectional a
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Reid, Malcolm S., Leslie S. Prichep, Debra Ciplet, et al. "Quantitative Electroencephalographic Studies of Cue-Induced Cocaine Craving." Clinical Electroencephalography 34, no. 3 (2003): 110–23. http://dx.doi.org/10.1177/155005940303400305.

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Quantitative electroencephalographic (qEEG) profiles were studied in cocaine dependent patients in response to cocaine cue exposure. Using neurometric analytical methods, the spectral power of each primary bandwidth was computed and topographically mapped. Additional measures of cue-reactivity included cocaine craving, anxiety and related subjective ratings, and physiological measures of skin conductance, skin temperature, heart rate, and plasma Cortisol and HVA levels. Twenty-four crack cocaine-dependent subjects were tested for their response to tactile, visual and audio cues related to crac
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Boyarkina, Iren. "Positive influence of certain sports on learning and second language acquisition processes." Zbornik radova Filozofskog fakulteta u Pristini 51, no. 1 (2021): 309–20. http://dx.doi.org/10.5937/zrffp51-30724.

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Various research convincingly demonstrated positive influence of certain sports and physical exercises on brain and brain functions in general, and on cognitive functions in particular. As it has been demonstrated, efficient and well-developed cognitive functions enhance all human activities and are of crucial importance for learning. In particular, this paper focuses on the positive correlation between certain sports and language learning and its relevance to the Second Language Acquisition studies (SLA). In SLA, students' ability to process input strongly depends on their cognitive abilities
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Zeng, Chengcheng, Wei Lin, Nian Li, et al. "Electroencephalography (EEG)-Based Neural Emotional Response to the Vegetation Density and Integrated Sound Environment in a Green Space." Forests 12, no. 10 (2021): 1380. http://dx.doi.org/10.3390/f12101380.

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Emotion plays an important role in physical and mental health. Green space is an environment conducive to physical and mental recovery and influences human emotions through visual and auditory stimulation. Both the visual environment and sound environment of a green space are important factors affecting its quality. Most of the previous relevant studies have focused solely on the visual or sound environment of green spaces and its impacts. This study focused on the combination of vegetation density (VD) and integrated sound environment (ISE) based on neural emotional evaluation criteria. VD wa
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Hölle, Daniel, Sarah Blum, Sven Kissner, Stefan Debener, and Martin G. Bleichner. "Real-Time Audio Processing of Real-Life Soundscapes for EEG Analysis: ERPs Based on Natural Sound Onsets." Frontiers in Neuroergonomics 3 (February 4, 2022). http://dx.doi.org/10.3389/fnrgo.2022.793061.

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With smartphone-based mobile electroencephalography (EEG), we can investigate sound perception beyond the lab. To understand sound perception in the real world, we need to relate naturally occurring sounds to EEG data. For this, EEG and audio information need to be synchronized precisely, only then it is possible to capture fast and transient evoked neural responses and relate them to individual sounds. We have developed Android applications (AFEx and Record-a) that allow for the concurrent acquisition of EEG data and audio features, i.e., sound onsets, average signal power (RMS), and power sp
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Cai, Hanshu, Zhenqin Yuan, Yiwen Gao, et al. "A multi-modal open dataset for mental-disorder analysis." Scientific Data 9, no. 1 (2022). http://dx.doi.org/10.1038/s41597-022-01211-x.

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AbstractAccording to the WHO, the number of mental disorder patients, especially depression patients, has overgrown and become a leading contributor to the global burden of disease. With the rising of tools such as artificial intelligence, using physiological data to explore new possible physiological indicators of mental disorder and creating new applications for mental disorder diagnosis has become a new research hot topic. We present a multi-modal open dataset for mental-disorder analysis. The dataset includes EEG and recordings of spoken language data from clinically depressed patients and
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Chen, Guijun, Xueying Zhang, Jing Zhang, Fenglian Li, and Shufei Duan. "A novel brain-computer interface based on audio-assisted visual evoked EEG and spatial-temporal attention CNN." Frontiers in Neurorobotics 16 (September 30, 2022). http://dx.doi.org/10.3389/fnbot.2022.995552.

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ObjectiveBrain-computer interface (BCI) can translate intentions directly into instructions and greatly improve the interaction experience for disabled people or some specific interactive applications. To improve the efficiency of BCI, the objective of this study is to explore the feasibility of an audio-assisted visual BCI speller and a deep learning-based single-trial event related potentials (ERP) decoding strategy.ApproachIn this study, a two-stage BCI speller combining the motion-onset visual evoked potential (mVEP) and semantically congruent audio evoked ERP was designed to output the ta
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Fauchon, Camille, David Meunier, Isabelle Faillenot, et al. "The Modular Organization of Pain Brain Networks: An fMRI Graph Analysis Informed by Intracranial EEG." Cerebral Cortex Communications 1, no. 1 (2020). http://dx.doi.org/10.1093/texcom/tgaa088.

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Abstract Intracranial EEG (iEEG) studies have suggested that the conscious perception of pain builds up from successive contributions of brain networks in less than 1 s. However, the functional organization of cortico-subcortical connections at the multisecond time scale, and its accordance with iEEG models, remains unknown. Here, we used graph theory with modular analysis of fMRI data from 60 healthy participants experiencing noxious heat stimuli, of whom 36 also received audio stimulation. Brain connectivity during pain was organized in four modules matching those identified through iEEG, na
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Varshney, Yash V., and Azizuddin Khan. "Imagined Speech Classification Using Six Phonetically Distributed Words." Frontiers in Signal Processing 2 (March 25, 2022). http://dx.doi.org/10.3389/frsip.2022.760643.

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Imagined speech can be used to send commands without any muscle movement or emitting audio. The current status of research is in the early stage, and there is a shortage of open-access datasets for imagined speech analysis. We have proposed an openly accessible electroencephalograph (EEG) dataset for six imagined words in this work. We have selected six phonetically distributed, monosyllabic, and emotionally neutral words from W-22 CID word lists. The phonetic distribution of words consisted of the different places of consonants’ articulation and different positions of tongue advancement for v
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Dauer, Tysen, Duc T. Nguyen, Nick Gang, Jacek P. Dmochowski, Jonathan Berger, and Blair Kaneshiro. "Inter-subject Correlation While Listening to Minimalist Music: A Study of Electrophysiological and Behavioral Responses to Steve Reich's Piano Phase." Frontiers in Neuroscience 15 (December 9, 2021). http://dx.doi.org/10.3389/fnins.2021.702067.

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Musical minimalism utilizes the temporal manipulation of restricted collections of rhythmic, melodic, and/or harmonic materials. One example, Steve Reich's Piano Phase, offers listeners readily audible formal structure with unpredictable events at the local level. For example, pattern recurrences may generate strong expectations which are violated by small temporal and pitch deviations. A hyper-detailed listening strategy prompted by these minute deviations stands in contrast to the type of listening engagement typically cultivated around functional tonal Western music. Recent research has sug
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Choy, Chi S., Qiang Fang, Katrina Neville, et al. "Virtual reality and motor imagery for early post-stroke rehabilitation." BioMedical Engineering OnLine 22, no. 1 (2023). http://dx.doi.org/10.1186/s12938-023-01124-9.

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Abstract Background Motor impairment is a common consequence of stroke causing difficulty in independent movement. The first month of post-stroke rehabilitation is the most effective period for recovery. Movement imagination, known as motor imagery, in combination with virtual reality may provide a way for stroke patients with severe motor disabilities to begin rehabilitation. Methods The aim of this study is to verify whether motor imagery and virtual reality help to activate stroke patients’ motor cortex. 16 acute/subacute (< 6 months) stroke patients participated in this study. All parti
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