22 papers · ranked by Valyu relevance
Marc M. Himmelberg, Federico G. Segala, Ryan T. Maloney, Julie M. Harris + 1 more
Two stereoscopic cues that underlie the perception of motion-in-depth (MID) are changes in retinal disparity over time (CD) and interocular velocity differences (IOVD). These cues have independent spatiotemporal sensitivity profiles, depend upon different low-level stimulus properties, and are potentially processed…
Raheel Zafar, Sarat C. Dass, Aamir Saeed Malik, Bin He
Electroencephalogram (EEG)-based decoding human brain activity is challenging, owing to the low spatial resolution of EEG. However, EEG is an important technique, especially for brain-computer interface applications. In this study, a novel algorithm is proposed to decode brain activity associated with different types…
Thomas A. Carlson, Tijl Grootswagers, Amanda K. Robinson
The human brain is constantly processing and integrating information in order to make decisions and interact with the world, for tasks from recognizing a familiar face to playing a game of tennis. These complex cognitive processes require communication between large populations of neurons. The noninvasive neuroimaging…
Ling Huang, Manuel Varlet, Tijl Grootswagers
High-density EEG recording enhances spatial resolution for neural signal decoding, yet the relationship between electrode density and decoding performance, as well as the minimum number of electrodes required for effective decoding, remains unclear. To address this, we systematically investigated the decoding accuracy…
Alejandro Santos-Mayo, Faith Gilbert, Laura Ahumada, Caitlin Traiser + 4 more
Neuroscience research has increasingly used decoding techniques, in which multivariate statistical methods identify patterns in neural data that allow the classification of experimental conditions or participant groups. Typically, the features used for decoding are spatial in nature, including voxel patterns and…
Matteo Ferrante, Tommaso Boccato, Stefano Bargione, Nicola Toschi
Decoding visual representations from human brain activity has emerged as a thriving research domain, particularly in the context of brain-computer interfaces. Our study presents an innovative method that employs to classify and reconstruct images from the ImageNet dataset using electroencephalography (EEG) data from…
Ksenia Volkova, Mikhail A. Lebedev, Alexander Kaplan, Alexei Ossadtchi
'Alexei Ossadtchi'] Electrocorticography (ECoG) holds promise to provide efficient neuroprosthetic solutions for people suffering from neurological disabilities. This recording technique combines adequate temporal and spatial resolution with the lower risks of medical complications compared to the other invasive…
Xiaoqian Mao, Mengfan Li, Wei Li, Linwei Niu + 3 more
'Genshe Chen'] The most popular noninvasive Brain Robot Interaction (BRI) technology uses the electroencephalogram- (EEG-) based Brain Computer Interface (BCI), to serve as an additional communication channel, for robot control via brainwaves. This technology is promising for elderly or disabled patient assistance with…
Roman Dolgopolyi, Antonis Chatzipanagiotou
An advanced emotion classification model was developed using a CNN-Transformer architecture for emotion recognition from EEG brain wave signals, effectively distinguishing among three emotional states, positive, neutral, and negative. The model achieved a testing accuracy of 91%, outperforming traditional models such…
Ildar Rakhmatulin
In recent years, neural networks showed unprecedented growth that ultimately influenced dozens of different industries, including signal processing for the electroencephalography (EEG) process. Electroencephalography, although it appeared in the first half of the 20th century, was not changed the physical principles of…
Ahmad Chaddad, Yihang Wu, Reem Kateb, Ahmed Bouridane + 2 more
The electroencephalography (EEG) signal is a noninvasive and complex signal that has numerous applications in biomedical fields, including sleep and the brain-computer interface. Given its complexity, researchers have proposed several advanced preprocessing and feature extraction methods to analyze EEG signals. In this…
Ben McCartney, Jesus Martinez-del-Rincon, Barry Devereux, Brian Murphy
Brain decoding — the process of inferring a person’s momentary cognitive state from their brain activity — has enormous potential in the field of human-computer interaction. In this study we propose a zero-shot EEG-to-image brain decoding approach which makes use of state-of-the-art EEG preprocessing and feature…
Christos Orovas, Theodosios Sapounidis, Christina Volioti, Euclid Keramopoulos + 1 more
'Euclid Keramopoulos' 'Francesco Carlo Morabito'] Education is an activity that involves great cognitive load for learning, understanding, concentrating, and other high-level cognitive tasks. The use of the electroencephalogram (EEG) and other brain imaging techniques in education has opened the scientific field of…
K. Sheela sobana Rani, S Pravinth Raja, M. Sinthuja, B Vidhya Banu + 2 more
EEG, or Electroencephalogram, is an instrument that examines the brain's functions while it is executing any activity. EEG signals to aid in the identification of brain processes and movements and are thus useful in the detection of neurobiological illnesses. Pulses have a very weak magnitude and are recorded from peak…
Pedro M. R. Reis, Felix Hebenstreit, Florian Gabsteiger, Vinzenz von Tscharner + 1 more
EEG involves the recording, analysis, and interpretation of voltages recorded on the human scalp which originate from brain gray matter. EEG is one of the most popular methods of studying and understanding the processes that underlie behavior. This is so, because EEG is relatively cheap, easy to wear, light weight and…
Ildar Rakhmatulin
This manuscript presented brain-computer interface (STM32 and ADS1299) with the embedded board with sensors to monitor the subject's state and environment. To reduce power consumption and device size, we used sensors made in Micro-Electro-Mechanical Systems technology (MEMS) - a gyroscope, accelerometer, and…
Amanda K Robinson, Praveen Venkatesh, Matthew J. Boring, Michael J. Tarr + 2 more
Standard human EEG systems based on spatial Nyquist estimates suggest that 20-30 mm electrode spacing suffices to capture neural signals on the scalp, but recent studies posit that increasing sensor density can provide higher resolution neural information. Here, we compared “super-Nyquist” density EEG (“SND”) with…
Gonzalo M. Rojas, Carolina Alvarez, Carlos Montoya, María de la Iglesia-Vayá + 2 more
Electroencephalography (EEG) is the standard diagnosis method for a wide variety of diseases such as epilepsy, sleep disorders, encephalopathies, and coma, among others. Resting-state functional magnetic resonance (rs-fMRI) is currently a technique used in research in both healthy individuals as well as patients. EEG…
Radek Martinek, Martina Ladrova, Michaela Sidikova, Rene Jaros + 5 more
'Khosrow Behbehani' 'Radana Kahankova' 'Aleksandra Kawala-Sterniuk' 'Sung-Phil Kim' 'Yvonne Tran'] As it was mentioned in the previous part of this work (Part I)-the advanced signal processing methods are one of the quickest and the most dynamically developing scientific areas of biomedical engineering with their…
Vangelis P. Oikonomou, Georgios Liaros, Kostantinos Georgiadis, Elisavet Chatzilari + 3 more
'Elisavet Chatzilari' 'Katerina Adam' 'Spiros Nikolopoulos' 'Ioannis Kompatsiaris'] Brain-computer interfaces (BCIs) have been gaining momentum in making human-computer interaction more natural, especially for people with neuro-muscular disabilities. Among the existing solutions the systems relying on…
Emanuele Quattrocchi, Baptiste Py, Adeleke Maradesa, Quentin Meyer + 2 more
Electrochemical impedance spectroscopy (EIS) is a characterization technique widely used to evaluate the properties of electrochemical systems. The distribution of relaxation times (DRT) has emerged as a model-free alternative to equivalent circuits and physical models to circumvent the inherent challenges of EIS…
Xudan Yao, Jason Hui, Ian Kinloch, Mark Bissett
Despite their excellent mechanical performance, carbon fibre reinforced polymer (CFRP) composites are limited by the interfacial properties due to the inherent nature of laminated structures. One way to modify the interface is by the inclusion of nanomaterials on the surface of carbon fibres. Here, we use…