Search results for: EEG,IMAGINARY MOTION,BRAIN INJURIES,MULTIMODAL INTERFACES,POLYSENSORY STIMULATION
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Michał Lech dr inż.
PeopleMichał Lech was born in Gdynia in 1983. In 2007 he graduated from the faculty of Electronics, Telecommunications and Informatics of Gdansk University of Technology. In June 2013, he received his Ph.D. degree. The subject of the dissertation was: “A Method and Algorithms for Controlling the Sound Mixing Processes by Hand Gestures Recognized Using Computer Vision”. The main focus of the thesis was the bias of audio perception caused...
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A Study in Experimental Methods of Human-Computer Communication for Patients After Severe Brain Injuries
PublicationExperimental research in the domain of multimedia technology applied to medical practice is discussed, employing a prototype of integrated multimodal system to assist diagnosis and polysensory stimulation of patients after severe brain injury. The system being developed includes among others: eye gaze tracker, and EEG monitoring of non-communicating patients after severe brain injuries. The proposed solutions are used for collecting...
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Comparison of Classification Methods for EEG Signals of Real and Imaginary Motion
PublicationThe classification of EEG signals provides an important element of brain-computer interface (BCI) applications, underlying an efficient interaction between a human and a computer application. The BCI applications can be especially useful for people with disabilities. Numerous experiments aim at recognition of motion intent of left or right hand being useful for locked-in-state or paralyzed subjects in controlling computer applications....
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Multimodal system for diagnosis and polysensory stimulation of subjects with communication disorders
PublicationAn experimental multimodal system, designed for polysensory diagnosis and stimulation of persons with impaired communication skills or even non-communicative subjects is presented. The user interface includes an eye tracking device and the EEG monitoring of the subject. Furthermore, the system consists of a device for objective hearing testing and an autostereoscopic projection system designed to stimulate subjects through their...
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Multifactor consciousness level assessment of participants with acquired brain injuries employing human–computer interfaces
PublicationBackground A lack of communication with people suffering from acquired brain injuries may lead to drawing erroneous conclusions regarding the diagnosis or therapy of patients. Information technology and neuroscience make it possible to enhance the diagnostic and rehabilitation process of patients with traumatic brain injury or post-hypoxia. In this paper, we present a new method for evaluation possibility of communication and the...
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Multimodal Approach For Polysensory Stimulation And Diagnosis Of Subjects With Severe Communication Disorders
Publicationis evaluated on 9 patients, data analysis methods are described, and experiments of correlating Glasgow Coma Scale with extracted features describing subjects performance in therapeutic exercises exploiting EEG and eyetracker are presented. Performance metrics are proposed, and k-means clusters used to define concepts for mental states related to EEG and eyetracking activity. Finally, it is shown that the strongest correlations...
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Problems in estimation of hand grip force based on EMG signal
PublicationThere has recently been a significant increase in the number of publications on and applications of bioelectric signals for diagnostic purposes. While the use of ECG (electrocardiography) is not surprising, the use of signals from registration of brain activity (EEG) and muscles activity (EMG) still finds new applications in various fields. The authors focus on the use of EMG signals for estimating hand grip force. Currently,...
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Real and imaginary motion classification based on rough set analysis of EEG signals for multimedia applications
PublicationRough set-based approach to the classification of EEG signals of real and imaginary motion is presented. The pre-processing and signal parametrization procedures are described, the rough set theory is briefly introduced, and several classification scenarios and parameters selection methods are proposed. Classification results are provided and discussed with their potential utilization for multimedia applications controlled by the...
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Comparison of Methods for Real and Imaginary Motion Classification from EEG Signals
PublicationA method for feature extraction and results of classification of EEG signals obtained from performed and imagined motion are presented. A set of 615 features was obtained to serve for the recognition of type and laterality of motion using 8 different classifications approaches. A comparison of achieved classifiers accuracy is presented in the paper, and then conclusions and discussion are provided. Among applied algorithms the...
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Multimodal human-computer interfaces based on advanced video and audio analysis
PublicationMultimodal interfaces development history is reviewed briefly in the introduction. Some applications of multimodal interfaces to education software for disabled people are presented. One of them, the LipMouse is a novel, vision-based human-computer interface that tracks user’s lip movements and detect lips gestures. A new approach to diagnosing Parkinson’s disease is also shown. The progression of the disease can be measured employing...
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Multimodal human-computer interfaces based on advanced video and audio analysis
PublicationMultimodal interfaces development history is reviewed briefly in the introduction. Examples of applications of multimodal interfaces to education software and for the disabled people are presented, including interactive electronic whiteboard based on video image analysis, application for controlling computers with mouth gestures and the audio interface for speech stretching for hearing impaired and stuttering people. The Smart...
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Consciousness Study of Subjects with Unresponsive Wakefulness Syndrome Employing Multimodal Interfaces
PublicationThe paper presents a novel multimodal-based methodology for consciousness study of individuals with unresponsive wakefulness syndrome. Two interfaces were employed in the experiments: eye gaze tracking system – CyberEye developed at the Multimedia Systems Department, and EEG device with electrode placement in the international 10-20 standard. It was a pilot study for checking if it is possible to determine objective methods based...
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New Applications of Multimodal Human-Computer Interfaces
PublicationMultimodal computer interfaces and examples of their applications to education software and for the disabled people are presented. The proposed interfaces include the interactive electronic whiteboard based on video image analysis, application for controlling computers with gestures and the audio interface for speech stretching for hearing impaired and stuttering people. Application of the eye-gaze tracking system to awareness...
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Cross-domain applications of multimodal human-computer interfaces
PublicationDeveloped multimodal interfaces for education applications and for disabled people are presented, including interactive electronic whiteboard based on video image analysis, application for controlling computers with mouth gestures and audio interface for speech stretching for hearing impaired and stuttering people and intelligent pen allowing for diagnosing and ameliorating developmental dyslexia. The eye-gaze tracking system named...
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Automatic Clustering of EEG-Based Data Associated with Brain Activity
PublicationThe aim of this paper is to present a system for automatic assigning electroencephalographic (EEG) signals to appropriate classes associated with brain activity. The EEG signals are acquired from a headset consisting of 14 electrodes placed on skull. Data gathered are first processed by the Independent Component Analysis algorithm to obtain estimates of signals generated by primary sources reflecting the activity of the brain....
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Direct electrical stimulation of the human brain has inverse effects on the theta and gamma neural activities
PublicationObjective: Our goal was to analyze the electrophysiological response to direct electrical stimulation (DES) systematically applied at a wide range of parameters and anatomical sites, with particular focus on neural activities associated with memory and cognition. Methods: We used a large set of intracranial EEG (iEEG) recordings with DES from 45 subjects with electrodes...
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Method for Clustering of Brain Activity Data Derived from EEG Signals
PublicationA method for assessing separability of EEG signals associated with three classes of brain activity is proposed. The EEG signals are acquired from 23 subjects, gathered from a headset consisting of 14 electrodes. Data are processed by applying Discrete Wavelet Transform (DWT) for the signal analysis and an autoencoder neural network for the brain activity separation. Processing involves 74 wavelets from 3 DWT families: Coiflets,...
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Brain Stimulation
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Direct electrical brain stimulation of human memory: lessons learnt and future perspectives
PublicationModulation of cognitive functions supporting human declarative memory is one of the grand challenges of neuroscience, and of vast importance for a variety of neuropsychiatric, neurodegenerative and neurodevelopmental diseases. Despite a recent surge of successful attempts at improving performance in a range of memory tasks, the optimal approaches and parameters for memory enhancement have yet to be determined. On a more fundamental...
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Deep learning approach on surface EEG based Brain Computer Interface
PublicationIn this work we analysed the application of con-volutional neural networks in motor imagery classification for the Brain Computer Interface (BCI) purposes. To increase the accuracy of classification we proposed the solution that combines the Common Spatial Pattern (CSP) with convolutional network (ConvNet). The electroencephalography (EEG) is one of the modalities we try to use for controlling the prosthetic arm. Therefor in this...
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Rough Set-Based Classification of EEG Signals Related to Real and Imagery Motion
PublicationA rough set-based approach to classification of EEG signals registered while subjects were performing real and imagery motions is presented in the paper. The appropriate subset of EEG channels is selected, the recordings are segmented, and features are extracted, based on time-frequency decomposition of the signal. Rough set classifier is trained in several scenarios, comparing accuracy of classification for real and imagery motion....
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CyberEye: New Eye-Tracking Interfaces for Assessment and Modulation of Cognitive Functions beyond the Brain
PublicationThe emergence of innovative neurotechnologies in global brain projects has accelerated research and clinical applications of BCIs beyond sensory and motor functions. Both invasive and noninvasive sensors are developed to interface with cognitive functions engaged in thinking, communication, or remembering. The detection of eye movements by a camera offers a particularly attractive external sensor for computer interfaces to monitor,...
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublicationMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
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Brain-computer interaction based on EEG signal and gaze-tracking information = Analiza interackji mózg-komputer wykorzystująca sygnał EEg i informacje z systemu śledzenia punktu fiksacji wzroku
PublicationThe article presents an attempt to integrate EEG signal analysis with information about human visual activities, i.e. gaze fixation point. The results from gaze-tracking-based measurement were combined with the standard EEG analysis. A search for correlation between the brain activity and the region of the screen observed by the user was performed. The preliminary stage of the study consists in electrooculography (EOG) signal processing....
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Human Computer Interface for Tracking Eye Movements Improves Assessment and Diagnosis of Patients With Acquired Brain Injuries
PublicationOne of the first clinical signs differentiating the minimally conscious state from the vegetative state is the presence of smooth pursuit eye movements occurring in direct response to moving salient stimuli. Glasgow Coma Scale (GCS) is one of the most commonly used diagnostic tools for acute phase assessment of the level of consciousness, together with a neurological examination. These classic measures are limited to qualitative...
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Journal on Multimodal User Interfaces
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Brain-Computer Interfaces
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Deep brain stimulation: new possibilities for the treatment of mental disorders
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Direct brain stimulation modulates encoding states and memory performance in humans
PublicationPeople often forget information because they fail to effectively encode it. Here, we test the hypothesis that targeted electrical stimulation can modulate neural encoding states and subsequent memory outcomes. Using recordings from neurosurgical epilepsy patients with intracranially implanted electrodes, we trained multivariate classifiers to discriminate spectral activity during learning that predicted remembering from forgetting,...
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New methods for assessment and stimulation of non-communicative patients employing advanced multimodal HCI . Nowe metody oceny i stymulacji pacjentów niekomunikatywnych z wykorzystaniem zaawansowanych interfejsów multimodalnych człowiek-komputer
PublicationIn most cases of patients with locomotor system damage it is possible to find a solution to the medical problems originating from the injury. However, it is much more difficult to prevent cognitive and emotional impairments. Therefore, we believe that the technological support of therapists working with such patients on an everyday basis may be essential. We have acquired experience in designing and providing diagnostic and therapeutic...
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Deep brain stimulation in obsessive-compulsive disorder – case report of two patients
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Sleep assessment in obsessive-compulsive disorder treated with deep brain stimulation - double case report of morning and evening chronotype patients
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Various neuromodulation methods including Deep Brain Stimulation of the medial forebrain bundle combined with psychopharmacotherapy of treatment-resistant depression—Case report
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Fast and Efficient Four-Class Motor Imagery EEG Signals Analysis Using CSP-Ridge Regression Algorithm for the Purpose of Brain-Computer Interface."
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Assessment of Therapeutic Progress After Acquired Brain Injury Employing Electroencephalography and Autoencoder Neural Networks
PublicationA method developed for parametrization of EEG signals gathered from participants with acquired brain injuries is shown. Signals were recorded during therapeutic session consisting of a series of computer assisted exercises. Data acquisition was performed in a neurorehabilitation center located in Poland. The presented method may be used for comparing the performance of subjects with acquired brain injuries (ABI) who are involved...
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Electrical Stimulation Modulates High Gamma Activity and Human Memory Performance
PublicationDirect electrical stimulation of the brain has emerged as a powerful treatment for multiple neurological diseases, and as a potential technique to enhance human cognition. Despite its application in a range of brain disorders, it remains unclear how stimulation of discrete brain areas affects memory performance and the underlying electrophysiological activities. Here, we investigated the effect of direct electrical stimulation...
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Michał Tomasz Kucewicz dr
PeopleMichal Kucewicz was born in 1986 in Gdansk. In 2005 he completed International Baccalaureate programme in Topolowka (III High School in Gdańsk). Thanks to the G. D. Fahrenheit scholarship, he moved to the United Kingdom to study neuroscience. He received his Bachelor’s and Master’s degree from the Cambridge University, and his doctoral degree from the University of Bristol specializing in electrophysiology of memory and cognitive...
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International Conference on Multimodal Interaction (International Conference on Multimodal Interfaces)
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Piotr Odya dr inż.
PeoplePiotr Odya was born in Gdansk in 1974. He received his M.Sc. in 1999 from the Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, Poland. His thesis was related to the problem of sound quality improvement in the contemporary broadcasting studio. He is interested in video editing and multichannel sound systems. The goal of Mr. Odya Ph.D. thesis concerned methods and algorithms for correcting...
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Joanna Rymaszewska prof. dr hab. n. med.
PeopleCV Joanna Rymaszewska Wroclaw University of Science and Technology, Wroclaw, Poland +48 601 98 26 24, joanna.rymaszewska@pwr.edu.pl orcid.org/0000-0001-8985-3592 2023 → Professor of Wroclaw University of Science and Technology (WUST), Poland 2011 → 2023 Professor of Wroclaw Medical University (WMU), PL 2016 → 2022 Head of the Department of Psychiatry, Wroclaw Medical University 2016 → 2022 Head of the Clinic of Psychiatry,...
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Pursuing the Deep-Learning-Based Classification of Exposed and Imagined Colors from EEG
PublicationEEG-based brain-computer interfaces are systems aiming to integrate disabled people into their environments. Nevertheless, their control could not be intuitive or depend on an active external stimulator to generate the responses for interacting with it. Targeting the second issue, a novel paradigm is explored in this paper, which depends on a passive stimulus by measuring the EEG responses of a subject to the primary colors (red,...
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Wykłady neuronaukowe
EventsCentrum BioTechMed zaprasza na dwa wykłady neuronaukowe prowadzone przez profesorów wizytujących Politechnikę Gdańską.
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Intelligent multimedia solutions supporting special education needs.
PublicationThe role of computers in school education is briefly discussed. Multimodal interfaces development history is shortly reviewed. Examples of applications of multimodal interfaces for learners with special educational needs are presented, including interactive electronic whiteboard based on video image analysis, application for controlling computers with facial expression and speech stretching audio interface representing audio modality....
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Intelligent video and audio applications for learning enhancement
PublicationThe role of computers in school education is briefly discussed. Multimodal interfaces development history is shortly reviewed. Examples of applications of multimodal interfaces for learners with special educational needs are presented, including interactive electronic whiteboard based on video image analysis, application for controlling computers with facial expression and speech stretching audio interface representing audio modality....
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Tensor Decomposition for Imagined Speech Discrimination in EEG
PublicationMost of the researches in Electroencephalogram(EEG)-based Brain-Computer Interfaces (BCI) are focused on the use of motor imagery. As an attempt to improve the control of these interfaces, the use of language instead of movement has been recently explored, in the form of imagined speech. This work aims for the discrimination of imagined words in electroencephalogram signals. For this purpose, the analysis of multiple variables...
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Human memory enhancement through electrical stimulation in the temporal cortex
PublicationDirect electrical stimulation of the human brain can elicit sensory and motor perceptions as well as recall of memories. Stimulating higher order association areas of the lateral temporal cortex in particular was reported to activate visual and auditory memory representations of past experiences (Penfield and Perot, 1963). We hypothesized that this effect could be used to modulate memory processing. Recent attempts at memory enhancement...
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How Can We Identify Electrophysiological iEEG Activities Associated with Cognitive Functions?
PublicationElectrophysiological activities of the brain are engaged in its various functions and give rise to a wide spectrum of low and high frequency oscillations in the intracranial EEG (iEEG) signals, commonly known as the brain waves. The iEEG spectral activities are distributed across networks of cortical and subcortical areas arranged into hierarchical processing streams. It remains a major challenge to identify these activities in...
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Krzysztof Kutt dr inż.
PeopleComputer scientist and psychologist trying to combine expertise from both disciplines into something cool. My research activity focuses on the development of affective HCI/BCI interfaces (based on multimodal fusion of signals and contextual data), methods for processing sensory data (including semantization of such data) and the development of knowledge-based systems (in particular knowledge graphs and semantic web systems).
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Closed-loop stimulation of temporal cortex rescues functional networks and improves memory
PublicationMemory failures are frustrating and often the result of ineffective encoding. One approach to improving memory outcomes is through direct modulation of brain activity with electrical stimulation. Previous efforts, however, have reported inconsistent effects when using open-loop stimulation and often target the hippocampus and medial temporal lobes. Here we use a closed-loop system to monitor and decode neural activity from direct...
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Interictal high-frequency oscillations in focal human epilepsy
PublicationPURPOSE OF REVIEW: Localization of focal epileptic brain is critical for successful epilepsy surgery and focal brain stimulation. Despite significant progress, roughly half of all patients undergoing focal surgical resection, and most patients receiving focal electrical stimulation, are not seizure free. There is intense interest in high-frequency oscillations (HFOs) recorded with intracranial electroencephalography as potential...