Olga Sourina

Olga Sourina
Nanyang Technological University | ntu

About

158
Publications
61,255
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3,630
Citations
Citations since 2016
57 Research Items
2665 Citations
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20162017201820192020202120220100200300400
20162017201820192020202120220100200300400

Publications

Publications (158)
Article
Deep learning for electroencephalogram-based classification is confronted with data scarcity, due to the time-consuming and expensive data collection procedure. Data augmentation has been shown as an effective way to improve data efficiency. In addition, contrastive learning has recently been shown to hold great promise in learning effective repres...
Chapter
Humanoid robots gaining popularity in the service industry all over the world. When designing humanoid robots, product designers put additional thought into the aesthetic design to avoid the complications that arise from the “uncanny valley”. It has long been found that genders, personalities, and cultural upbringings may affect individual ratings...
Article
In the context of electroencephalogram (EEG)-based driver drowsiness recognition, it is still challenging to design a calibration-free system, since EEG signals vary significantly among different subjects and recording sessions. Many efforts have been made to use deep learning methods for mental state recognition from EEG signals. However, existing...
Article
Full-text available
Shunting of trains is a task that requires meticulous adherence to all steps to guarantee safety for everyone involved during and after the procedure. These steps are currently taught using classical teaching materials, such as printouts, videos and training by experienced supervisors. However, due to limited availability of locomotives, hours for...
Preprint
Full-text available
For EEG-based drowsiness recognition, it is desirable to use subject-independent recognition since conducting calibration on each subject is time-consuming. In this paper, we propose a novel Convolutional Neural Network (CNN)-Long Short-Term Memory (LSTM) model for subject-independent drowsiness recognition from single-channel EEG signals. Differen...
Conference Paper
Abstract— The maritime industry is switching to new types of fuel such as Liquefied Natural Gas (LNG). On one hand, these kinds of fuel are more sustainable to the environment, on the other hand, training on handling such fuel safely and dealing with emergency situation is necessary. Videos and lecturebased learning is commonly used to deliver such...
Preprint
Full-text available
Driver drowsiness is one of main factors leading to road fatalities and hazards in the transportation industry. Electroencephalography (EEG) has been considered as one of the best physiological signals to detect drivers drowsy states, since it directly measures neurophysiological activities in the brain. However, designing a calibration-free system...
Preprint
Full-text available
In the context of electroencephalogram (EEG)-based driver drowsiness recognition, it is still a challenging task to design a calibration-free system, since there exists a significant variability of EEG signals among different subjects and recording sessions. As deep learning has received much research attention in recent years, many efforts have be...
Article
Driver drowsiness is one of the main factors leading to road fatalities and hazards in the transportation industry. Electroencephalography (EEG) has been considered as one of the best physiological signals to detect drivers' drowsy states, since it directly measures neurophysiological activities in the brain. However, designing a calibration-free s...
Article
Situation awareness (SA) has received much attention in recent years because of its importance for operators of dynamic systems. Electroencephalography (EEG) can be used to measure mental states of operators related to SA. However, cross-subject EEG-based SA recognition is a critical challenge, as data distributions of different subjects vary signi...
Article
Mental fatigue is one of the major factors leading to human errors. To avoid failures caused by mental fatigue, researchers are working on ways to detect/monitor fatigue using different types of signals. Electroencephalography (EEG) signal is one of the most popular methods to recognize mental fatigue since it directly measures the neurophysiologic...
Chapter
Full-text available
The first impression of robot appearance normally affects the interaction with physical robots. Hence, it is critically important to evaluate the humanoid robot appearance design. This study towards evaluating humanoid robot design based on global eye-tracking metrics. Two methods are selected to extract global eye-tracking metrics, including bin-a...
Article
Over the years, safety in maritime industries has been reinforced by many state-of-the-art technologies. However, the accident rate hasn’t dropped significantly with the advanced technology onboard. The main cause of this phenomenon is human errors which drive researchers to study human factors in the maritime domain. One of the key factors that co...
Article
This paper presents research results on the causes and effects of human errors in relation to typical ship design factors, such as noise, vibrations and ship motions. Following a review of the relevant literature, aimed to the identification and quantification of pertinent parameters and effects, a detailed questionnaire has been developed and answ...
Chapter
Full-text available
In this paper, Holding Stack Management (HSM), Continuous Climb Operations (CCO), Continuous Descent Operations (CDO), and Trajectory Based Operations (TBO) procedures are assessed in relation to the use of an additional 3D display. Two display seetings are compared, namely 2D+3D and 2D only. Twelve Air Traffic Control Officers (ATCOs) took part in...
Article
This paper describes an open access electroencephalography (EEG) dataset for multitasking mental workload activity induced by a single-session simultaneous capacity (SIMKAP) experiment with 48 subjects. To validate the database, EEG spectral activity was evaluated with EEGLAB and the significant channels and activities for the experiment are highli...
Article
Affective brain-computer interface (aBCI) introduces personal affective factors to human-computer interaction. The state-of-the-art aBCI tailors its classifier to each individual user to achieve accurate emotion classification. A subject-independent classifier that is trained on pooled data from multiple subjects generally leads to inferior accurac...
Chapter
Many studies have shown that most maritime accidents are attributed to human error as the initiating cause, resulting in a need for study of human factors to improve safety in maritime transportation. Among the various techniques, Electroencephalography (EEG) has the key advantage of high time resolution, with the possibility to continuously monito...
Chapter
NeuroFeedback Training (NFT) is a type of biofeedback training using Electroencephalogram (EEG) that allows the subjects to do self-regulation during the training according to their real-time brain activities. The purpose of this study is to optimize focused attention in expert rifle shooters with the use of NFT tools and to enhance shooting perfor...
Article
Study objectives: Automated sleep staging has been previously limited by a combination of clinical and physiological heterogeneity. Both factors are in principle addressable with large data sets that enable robust calibration. However, the impact of sample size remains uncertain. The objectives are to investigate the extent to which machine learni...
Chapter
Currently, Air Traffic Control (ATC) systems are reliable with automation supports, however, the increased traffic density and complex air traffic situations bring new challenges to ATC systems and air-traffic controllers (ATCOs). We conduct an experiment to evaluate the current ATC system and test conflict resolution automation and tactile user in...
Conference Paper
Haptic interaction is a form of a user-computer interaction where physical forces are delivered to the user via vibrations, displacements and rotations of special haptic devices. When quality of the experience of the haptic interaction is assessed, mostly subjective tests using various questionnaires are performed. We proposed novel neurocognitive...
Article
Full-text available
Polychronous neuronal group (PNG), a type of cell assembly, is one of the putative mechanisms for neural information representation. According to the reader-centric definition, some readout neurons can become selective to the information represented by polychronous neuronal groups under ongoing activity. Here, in computational models, we show that...
Presentation
Full-text available
Presentation on "25th Annual Computational Neuroscience Meeting: CNS-2016 " BMC Neuroscience 17, 112-113 (2016).
Chapter
Created intentionally or spontaneously, cyberworlds are information spaces and communities that immensely augment the way we interact, participate in business and receive information throughout the world. This paper reports position statements presented at the plenary panel of the 2015th International Conference on Cyberworlds. First, the problems...
Chapter
Electroencephalogram (EEG) techniques are traditionally used in the medical field. Recent research work focuses on applying these techniques to daily life with wireless and relatively low-price EEG devices available in the market. As a result, applications such as neurofeedback training, neuromarketing, emotion, stress, mental workload recognition,...
Conference Paper
Maritime accident statistics show that the majority of accidents/incidents are attributed to human errors as the initiating cause. Some studies put this as high as 95% of all accidents (collision, grounding, fire, occupational accidents, etc). The traditional way to investigate human factors in maritime industry is the statistical analysis of accid...
Article
Full-text available
In this paper, we propose a real-time adaptive prediction method to calculate smooth and accurate haptic feedback in complex scenarios. Smooth haptic feedback is an important task for haptic rendering with complex virtual objects. However, commonly the update rate of the haptic rendering may drop down during multi-point contact in complex scenarios...
Article
Full-text available
In human–computer interaction (HCI), electroencephalogram (EEG) signals can be added as an additional input to computer. An integration of real-time EEG-based human emotion recognition algorithms in human–computer interfaces can make the users experience more complete, more engaging, less emotionally stressful or more stressful depending on the tar...
Chapter
Full-text available
NeuroFeedback Training (NFT) can be used to enhance cognitive abilities in healthy adults. In this paper, we propose and implement a neurofeedback system which integrates an individual theta/beta based neurofeedback algorithm in a ?Shooting? game. The system includes an algorithm of calculation of an Individual Alpha Peak Frequency (IAPF), Individu...
Conference Paper
Full-text available
ICGenealogy: towards a common topology of neuronal ion channel function and genealogy in model and experiment Ion channels are fundamental constituents determining the function of single neurons and neuronal circuits. To understand their complex interactions, the field of computational modeling has proven essential: since its emergence, thousands...
Conference Paper
In this paper, we proposed a driver drowsiness detection method for which only eyelid movement information was required. The proposed method consists of two major parts. 1) In order to obtain accurate eye openness estimation, a vision-based eye openness recognition method was proposed to obtain an regression model that directly gave degree of eye o...
Conference Paper
Full-text available
Everyone experiences stress in life. Moderate stress can be beneficial to human; however, excessive stress is harmful to the health. To monitor stress, different methods can be used. In this work, an algorithm for stress level recognition from Electroencephalogram (EEG) is proposed. To validate the algorithm, an experiment is designed and carried o...
Conference Paper
Full-text available
Real-time EEG (Electroencephalogram)-based user's emotion, mental workload and stress monitoring is a new direction in research and development of human-machine interfaces. It has attracted recently more attention from the research community and industry as wireless portable EEG devices became easily available on the market. EEG-based technology ha...
Conference Paper
Full-text available
Currently, neurofeedback training can be used not only to treat the patients with attention deficit hyperactivity disorder, learning difficulties, etc. but also to improve cognitive abilities of healthy people. Training protocols based on alpha, theta, or theta/beta power calculated from Electroencephalogram (EEG) are commonly used in the neurofeed...
Conference Paper
Full-text available
Due to the precise spike timing in neural coding, spiking neural network (SNN) possesses richer spatiotemporal dynamics compared to neural networks with firing rate coding. One of the distinct features of SNN, polychronous neuronal group (PNG), receives much attention from both computational neuroscience and machine learning communities. However, a...
Chapter
Recently, new types of sensors such as electroencephalogram (EEG) devices became available for game development. This makes possible to adapt games using brain states recognition, for example, emotion recognition from EEG or to propose neurofeedback games. In this work, real-time emotion recognition and fractal dimension-based neurofeedback algorit...
Book
This book provides a detailed update on the applications of Serious Games in Healthcare and Education sector. In short, it provides an all rounded research and industry updates about the current and future advances in this area. These are the two sectors that are developing rapidly with direct applications of serious games. With advances in techno...
Article
Recently, new interactive devices such as hap tic devices became available for game development. 6DOF hap tic devices give the user an opportunity 'to feel' the simulated virtual environment in the way similar to the real world. Hap tic-based interaction can add a new dimension to 'serious games' development. The user can 'feel' objects surfaces an...
Conference Paper
Driver’s high workload caused by distractions has become one of the major concerns for road safety. This paper presents a data-driven method using machine learning algorithms to detect high workload caused by surrogate in-vehicle secondary tasks conducted in an on-road experiment with real traffic. The data were collected using an instrumented vehi...
Article
Full-text available
In this paper, a real-time Electroencephalogram (EEG)-based emotion recognition algorithm using Higuchi Fractal Dimension (FD) Spectrum is proposed. As EEG is a nonlinear and multi-fractal signal, its FD spectrum can give a better understanding of the nonlinear property of EEG. Three values are selected from the whole spectrum and are combined with...
Conference Paper
Full-text available
Nowadays, the human computer interfaces can be designed to be adaptive and emotion-enabled. The recognized emotions of the user can help make the user’s experience more complete, more engaging, less stressful or more stressful depending on the target of the applications. Such affective human-computer interfaces are getting more attention from resea...
Conference Paper
Full-text available
In this paper, we propose a novel approach to search for protein-protein complementary pairs in collaborative virtual environment. This method employs visual and force feedback tools to search for the optimal interaction between proteins. The search is manual with force feedback consisting of a repulsion or attraction force. We developed a prototyp...
Chapter
Full-text available
Emotional engagement during mental tasks performance when the difficulty level of mental tasks increases is studied using Electroencephalogram (EEG) recorded by Emotiv Epoch device. A real-time EEG-based emotion recognition algorithm using Valence-Arousal-Dominance emotion model is applied. An experiment with 5 levels of workload is proposed and ca...
Chapter
Full-text available
In this paper, we proposed a real-time subject-dependent EEG-based emotion recognition algorithm and tested it on experiments’ databases and the benchmark database DEAP. The algorithm consists of two parts: feature extraction and data classification with Support Vector Machine (SVM). Use of a Fractal Dimension feature in combination with statistica...
Conference Paper
Full-text available
In this paper, we propose and develop a novel adaptive haptic- based serious game for post stroke rehabilitation. Real-time patients emotions monitoring based on the Electroencephalogram (EEG) is used as an additional game control. A subject-dependent algorithm recognizing negative and positive emotions from EEG is integrated. Force feedback is pro...
Article
Full-text available
Recently, physically-based simulations with haptics interaction attracted many researchers. In this paper, we propose an adaptive Six Degrees-of-Freedom (6-DOF) haptic rendering algorithm based on virtual coupling, which can automatically adjust virtual coupling parameters according to mass values of the simulated virtual tools. The algorithm can o...
Conference Paper
Smooth haptic force feedback is an important task for multirate 6-DOF haptic rendering for both rigid and deformable objects. The update rate of the haptic force may be too low and changed during the simulation as the high computation time is required for complex physical simulation. Therefore, to implement a stable and smooth haptic rendering, we...
Conference Paper
Full-text available
Emotion recognition from Electroencephalogram (EEG) rapidly gains interest from research community. Two affective EEG databases are presented in this paper. Two experiments are conducted to set up the databases. Audio and visual stimuli are used to evoke emotions during the experiments. The stimuli are selected from IADS and IAPS databases.14 subje...
Conference Paper
Full-text available