BCI is a direct communication pathway between the brain and external devices. Electroencephalographic (EEG) based Brain Computer Interface (BCI) equipment usage are getting popular in recent researches. The brain waves (Alfa, Beta, Delta,... more
Brain-computer interface (BCI) or brain-machine interface (BMI) is a way to communicate between the brain and hardware without the use of muscles or the peripheral nervous system. Simultaneous EEG+fNIRS metric have recently been... more
Auditory brain-computer interfaces (BCIs) serve as an access pathway for individuals who present as locked-in and have concomitant visual impairments, but they do not perform as well as visual BCIs. Since hybrid BCIs that combine... more
Brain-computer interface (BCI) systems based on functional near-infrared spectroscopy (fNIRS) have been used as a way of facilitating communication between the brain and peripheral devices. The BCI provides an option to improve the... more
Brain Computing interface technology represents a very highly growing field now-a-days for the research because of its unique applications system. In this paper we investigate classification methods of mental commands based on EEG data... more
All rights reserved Near infrared (NIR) spectroscopy can optically measure the concentrations of oxygenated and deoxygenated cerebral haemoglobin (henceforth abbreviated as HbO and Hb, respectively). An NIR device typically consists of an... more
The trends in movement-related functional activity measurement for brain-computer interface (BCI) are mostly associated with the central lobe of the brain. This consideration may be a faulty approach for the paralyzed patient. This... more
We Shows a novel virtual fitting room framework using a depth sensor, which provides a realistic fitting experience with customized motion filters, size adjustments and physical simulation. The proposed scaling method adjusts the avatar... more
Most of the traditional works on emotion recognition utilize manifestation of emotion in face, voice, gesture/posture and bio-potential signals of the subjects. However, these modalities of emotion recognition cannot totally justify its... more
This work investigates the classification of finger-tapping task images constructed for the initial dip duration of hemodynamics (HR) associated with the small brain area of the left motor cortex using functional near-infrared... more
In this paper we demonstrate the coupling of an autonomous planning and control framework for whole-body humanoid motion, with a brain-computer interface (BCI) system in order to achieve online realtime biasing and correction of the... more
Brain Computer Interfaces (BCI) has become a vital field of biomedical engineering and computation, which uses electrical signals obtained from electroencephalogram exams (EEG) to provide assistive technologies (AT) for humans. The goal... more
Brain-Computer Interface (BCI) is a promising technology that enables people affected by neuromuscular disorders to control external devices like a wheelchair or prosthesis with the help of their brain signals. Functional near-infrared... more
Brain-computer interfaces (BCIs) allow individuals to use only cognitive activities to interact with their environment. The widespread use of BCIs is limited, due in part to their lack of user-friendliness. The main goal of this work was... more
Brain-Computer Interface (BCI) machines are capable of obtaining brain activities by conducting Electroencephalogram tests. Developments on both BCI and Machine Learning allowed various researchers to develop and study various BCI control... more
This paper presents the conceptual framework for a study of musical experience and the associated architecture centred on Human-Humanoid Interaction (HHI). On the grounds of the theoretical and experimental literature on the biological... more
The study and analysis of the electrical activity of the brain is valuable in understanding the human mental state, intentions and will. This aids the development of Brain Computer Interface (BCI), facilitating communication between the... more
Artificial limbs and exoskeletons have been widely used in a variety of applications, from military to medicine. The Defence Advanced Research Projects Agency (DARPA) primarily focuses on developing exoskeletons to aid ground soldiers in... more
Brain-Computer Interface can be non-invasive devices that obtain signals generated from the brain and are then manipulated to suit various applications. A popular application for BCI is interfacing with robotics; and, each BCI-Robotics... more
Brain-Computer Interface (BCI) machines are capable of obtaining brain activities by conducting Electroencephalogram tests. Developments on both BCI and Machine Learning allowed various researchers to develop and study various BCI control... more
This paper presents the conceptual framework for a study of musical experience and the associated architecture centred on Human-Humanoid Interaction (HHI). On the grounds of the theoretical and experimental literature on the biological... more
Classification of electroencephalogram (EEG) signal is important in mental decoding for brain-computer interfaces (BCI). We introduced a feature extraction approach based on frequency domain analysis to improve the classification... more
In this paper, a new adaptive neural network classifier (ANNC) of EEG-P300 signals from mental activities is proposed. To overcome an overtraining of the classifier caused by noisy and non-stationary data, the EEG signals are filtered and... more
The dwindling financial performance and the constant pressure to reduce cost and human intervention from boring tasks and repetitive led to the complexity of software programming languages blurring the lines between digital, physical and... more
This paper considers the problem of collision-free navigation of omnidirectional mobile robots in environments with obstacles. Information from a monocular camera, encoders, and an inertial measurement unit is used to achieve the task.... more
The main notion of this paper is to identify the cognitive load during a mental arithmetic task experiment using fNIRS signals. The first objective is to classify the difficulty level and the state of inactivity during the given task. To... more
Today, millions of peoples are suffering due to the lack of a functional arm preventing from doing things. In Sri Lanka there are about over thousands of people are suffering from disabilities. Sri Lanka Ministry of Health state that the... more
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Stroke and neurodegenerative diseases, among a range of other neurologic disorders, can cause chronic paralysis. Patients suffering from paralysis may remain unable to achieve even basic everyday tasks such as liquid intake. Currently,... more
The assistive, adaptive, and rehabilitative applications of EEG-based robot control and navigation are undergoing a major transformation in dimension as well as scope. Under the background of artificial intelligence, medical and... more
The study and analysis of the electrical activity of the brain is valuable in understanding the human mental state, intentions and will. This aids the development of Brain Computer Interface (BCI), facilitating communication between the... more
This paper presents the conceptual framework for a study of musical experience and the associated architecture centred on Human-Humanoid Interaction (HHI). On the grounds of the theoretical and experimental literature on the biological... more
A Virtual Trial Room application utilizing Augmented Reality which enables a client to undertake on virtual garments. The client posture and profundity is followed utilizing the Microsoft Kinect sensor and virtual garments are lined up... more
Functional near-infrared spectroscopy (fNIRS) is a comparatively new noninvasive, portable, and easy-to-use brain imaging modality. However, complicated dexterous tasks such as individual finger-tapping, particularly using one hand, have... more
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Many people suffer from movement disabilities and would benefit from an assistive mobility device with practical control. This paper demonstrates a face-machine interface system that uses motion artifacts from electroencephalogram (EEG)... more
P300 evoked potential is an electroencephalographic (EEG) signal obtained at the central-parietal region of the brain in response to rare or unexpected events. In this work, an experiment on the detection of a P-300 rhythm for potential... more
In this paper is illustrated the cognitive architecture of a humanoid robot based on the proposed paradigm of Latent Semantic Analysis (LSA). This paradigm is a step towards the simulation of an emotional behavior of a robot interacting... more
Nowadays the UX design become on a next level. Together with new way of interaction are introduced as finger and hand movement. The technology offer and thought-driven approach with so called brain-computer interface (BCI). This... more
Ota et al. PFC Neurofeedback Improves Hand Dexterity performance improvement rates in the motor rehabilitation task. The results suggest that the aPFC might shape activity in the somatosensory motor-related areas to improve hand... more
A brain-computer interface (BCI) is a communication system that allows the use of brain activity to control computers or other external devices. It can, by bypassing the peripheral nervous system, provide a means of communication for... more
Brain computer interfaces (BCI) provide a direct communication link between the brain and a computer or other external devices. They offer an extended degree of freedom either by strengthening or by substituting human peripheral working... more
pierre(dot)gergondet(at)aist.go.jp Summary. In this paper, we present our approach to design a brain-computer interface (BCI) that allows the user to perform multitask humanoid control. We efficiently integrate techniques from computer... more
Despite motion artifacts are a major source of noise in fNIRS infant data, how to approach motion correction in this population has only recently started to be investigated. Homer2 offers a wide range of motion correction methods and... more
We report results of a study that utilizes a BCI to drive an interactive interface countermeasure that allows users to self-regulate sustained attention while performing an ecologically valid, long-duration business logistics task. An... more
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Neurofeedback is a promising tool for brain rehabilitation and peak performance training. Neurofeedback approaches usually rely on a single brain imaging modality such as EEG or fMRI. Combining these modalities for neurofeedback training... more
We propose event-related cortical sources estimation from subject-independent electroencephalography (EEG) recordings for motor imagery brain computer interface (BCI). By using wavelet-based maximum entropy on the mean (wMEM),... more