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Showing 1 to 20 of 42 for “"Brain computer interface (BCI)"”.

  1. Development of Brain Computer Interface (BCI) system for integration with Functional Electrical Stimulation (FES) application

    Brain-Computer Interface (BCI) is a communication tool that translates human desire for other devices. The intention is for the majority of patients who were not able to move as stroke, spinal cord injury and traumatic brain injury. The goal of this study was to develop and analysis of offline and …

    uthm Repository record for Development of Brain Computer Interface (BCI) system for integration with Functional Electrical Stimulation (FES) application (opens in a new tab)

  2. Detection of mental task related EEG for brain computer interface implementation (using SVM classification approach)

    Brain computer interface (BCI) technology provides a method of communication and control for people with severe motor disabilities. This thesis explores the application of a Fast Fourier transform and support vector machine (FFT-SVM) to the problem of mental task detection in EEG-based brain

    cape-town Repository record for Detection of mental task related EEG for brain computer interface implementation (using SVM classification approach) (opens in a new tab)

  3. The effects of mental training on brain computer interface performance with distractions

    The overall success of a brain computer interface (BCI) is largely dependent on the features used to make decisions. Noise in the electroencephalography (EEG) increases the difficulty of acquiring meaningful features. Previous literature suggests teaching subjects meditation and relaxation …

    rowan Repository record for The effects of mental training on brain computer interface performance with distractions (opens in a new tab)

  4. EEG signal classification for wheelchair control application

    BrainComputer Interface (BCI) requires generating control signals for external device by analyzing and processing the internal brain signal. Person with severe impairment or spinal cord injury has loss of ability to do anything. This project about the EEG signals classification for wheelchair …

    uthm Repository record for EEG signal classification for wheelchair control application (opens in a new tab)

  5. P300-Based BCI Performance Prediction through Examination of Paradigm Manipulations and Principal Components Analysis.

    … a loss of nearly all voluntary muscle control. A brain-computer interface (BCI) using the P300 event-related potential provides communication that does not depend on neuromuscular activity and can be useful for those with LIS. Currently, there is no way of determining the effectiveness of …

    etsu Repository record for P300-Based BCI Performance Prediction through Examination of Paradigm Manipulations and Principal Components Analysis. (opens in a new tab)

  6. Improving Brain-Computer Interface Performance: Giving the P300 Speller Some Color.

    … face the possibility of the loss of speech. A Brain-Computer Interface (BCI) can provide a means for communication through non-muscular control. Current BCI systems use characters that flash from gray to white (GW), making adjacent character difficult to distinguish from the target. The current …

    etsu Repository record for Improving Brain-Computer Interface Performance: Giving the P300 Speller Some Color. (opens in a new tab)

  7. The Design and Implementation of an Extensible Brain-Computer Interface

    An implantable brain computer interface: BCI) includes tissue interface hardware, signal conditioning circuitry, analog-to-digital conversion: ADC) circuitry and some sort of computing hardware to discriminate desired waveforms from noise. Within an experimental paradigm the tissue interface and …

    wustl Repository record for The Design and Implementation of an Extensible Brain-Computer Interface (opens in a new tab)

  8. Neural Adaptation and the Effect of Interelectrode Spacing on Epidural Electrocorticography for Brain-Computer Interfaces

    … a safe and reliable recording technique for both Brain-Computer Interface: BCI) applications as well as neurophysiology studies. This thesis describes some of the first real-time closed-loop BCI studies of chronic ECoG in non-human primates. Epidural microECoG electrodes developed in our lab were …

    wustl Repository record for Neural Adaptation and the Effect of Interelectrode Spacing on Epidural Electrocorticography for Brain-Computer Interfaces (opens in a new tab)

  9. Adaptation and Control State Detection Techniques for Brain-Computer Interfaces

    A brain computer interface (BCI) is an alternate channel of communication between the user and the computer, without having to go through the usual neuromuscular pathways. Using BCI, disabled patients can communicate with a computer or control a prosthetic device just by modulating his/her brain

    nus Repository record for Adaptation and Control State Detection Techniques for Brain-Computer Interfaces (opens in a new tab)

  10. Evaluation Of Paradigms For A P300 Based Brain Computer Interface Speller

    … to compare a few different paradigms for the brain computer interface (BCI) virtual speller using the P300 signal. The paradigms consist of electrodes to record electroencephalogram signal (EEG), software to analyze the data, and a computer where the subject's EEG is the input for a virtual …

    nodak Repository record for Evaluation Of Paradigms For A P300 Based Brain Computer Interface Speller (opens in a new tab)

  11. Responsive IoT : using biosignals to connect humans and smart devices

    … IoT devices through visual, voice or tactile interfaces. More natural and organic interaction requires more sophisticated communication methods. This thesis explores seamless interfaces between human and IoT devices. In particular, I focus on using biological signals as the interface to …

    mit Repository record for Responsive IoT : using biosignals to connect humans and smart devices (opens in a new tab)

  12. Brain computer interface based neurorehabilitation technique using a commercially available EEG headset

    … the therapeutic virtual or robotic movement. Brain Computer Interface (BCI) aims to open up a new rehabilitation option for clinical population having no residual movement due to disease or injury to the central or peripheral nervous system. Brain activity contains a wide variety of electrical …

    njit Repository record for Brain computer interface based neurorehabilitation technique using a commercially available EEG headset (opens in a new tab)

  13. Near-Infrared Spectroscopy for Brain Computer Interfacing

    A brain-computer interface (BCI) gives those suffering from neuromuscular impairments a means to interact and communicate with their surrounding environment. A BCI translates physiological signals, typically electrical, detected from the brain to control an output device. A significant problem with …

    maynooth Repository record for Near-Infrared Spectroscopy for Brain Computer Interfacing (opens in a new tab)

  14. Development of A Versatile Multichannel CWNIRS Instrument for Optical Brain-Computer Interface Applications

    … spectroscopy (CWNIRS) instrument for brain-computer interface (BCI) applications. Specifically, it was of interest to assess what gains could be achieved by using a multichannel device compared to the single channel device implemented by Coyle in 2004. Moreover, the multichannel …

    maynooth Repository record for Development of A Versatile Multichannel CWNIRS Instrument for Optical Brain-Computer Interface Applications (opens in a new tab)

  15. On Controlling a Pediatric Lower-Limb Exoskeleton Using Finite-State Machine and Electroencephalography

    … therapy sessions. Integrating that with a brain-computer interface (BCI) could further optimize the learning process and accelerate motor function recovery. To address this need, the Laboratory for Non-Invasive Brain-Machine Interface Systems at the University of Houston in collaboration …

    houston Repository record for On Controlling a Pediatric Lower-Limb Exoskeleton Using Finite-State Machine and Electroencephalography (opens in a new tab)

  16. Brain-Computer Interface Fatigue in Children: Mechanisms and Impact

    … are often unable to exercise such autonomy. Brain-computer interface (BCI) technology offer children with QCP unique opportunities for communication, environmental exploration, learning, and play. BCI research is rapidly developing but has neglected pediatric populations. Like many …

    calgary Repository record for Brain-Computer Interface Fatigue in Children: Mechanisms and Impact (opens in a new tab)

  17. Event detection in EEG signals for brain computer interface using expectation-maximation algorithm

    … witnessed a steady growth in research related to Brain Computer Interface (BCI), which offers a non-muscular communication pathway to patients disabled due to neurological disorders. BCI works by recording brain signals (example; electroencephalography (EEG)) and translating them into …

    strathclyde Repository record for Event detection in EEG signals for brain computer interface using expectation-maximation algorithm (opens in a new tab)

  18. An analysis of EEG signals present during target search

    … appeared highlighting the applicability of using Brain Computer Interface (BCI) technology to utilise a subjects visual system to classify images. This technique involves classifying a users EEG (Electroencephalography) signals as they view images presented on a screen. The premise is that images …

    dcu Repository record for An analysis of EEG signals present during target search (opens in a new tab)

  19. Hand (Motor) Movement Imagery Classification of EEG Using Takagi-Sugeno-Kang Fuzzy-Inference Neural Network

    … from a neuroprosthetic device modulated by a Brain-Computer Interface (BCI). These devices restore independence by replacing peripheral nervous system functions such as peripheral control. Although there are currently devices under investigation, contemporary methods fail to offer adaptability …

    calpoly Repository record for Hand (Motor) Movement Imagery Classification of EEG Using Takagi-Sugeno-Kang Fuzzy-Inference Neural Network (opens in a new tab)

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