Electroencephalography (EEG) signals are frequently contaminated with unwanted electrooculographic (EOG) artifacts. Blinks and eye movements generate large amplitude peaks that corrupt EEG measurements. Independent component analysis (ICA) has been u...
Ocular contamination of EEG data is an important and very common problem in the diagnosis of neurobiological events. An effective approach is proposed in this paper to remove ocular artifacts from the raw EEG recording. First, it conducts the blind s...
Electroencephalogram (EEG) signals immensely suffer from several physiological artifacts, including electrooculogram (EOG), electromyogram (EMG), and electrocardiogram (ECG) artifacts, which must be removed to ensure EEG’s usability. This paper...
Background: Portable electroencephalogram (EEG) systems are often used in health care applications to record brain signals because their ease of use. An electrooculogram (EOG) is a common, low frequency, high amplitude artifact of the eye blink signa...
Steady-state visual evoked potentials (SSVEPs) are one of the key paradigms used in brain–computer interface (BCI) systems. Their performance, however, is substantially degraded by EEG artifacts of muscular, motion-related, and ocular origin. T...
This work presents a new on-line adaptive filter, which is based on a similarity analysis between standard electrode locations, in order to reduce artifacts and common interferences throughout electroencephalography (EEG) signals, but preserving the...
Brain computer interfaces are currently considered to greatly enhance assistive technologies and improve the experiences of people with special needs in the workplace. The proposed adaptive control model for smart offices provides a complete prototyp...
The occurrence of physiological artifacts generated by eye movements in electrical brain activity (electroencephalography, EEG) is a well-known problem in clinical practice. In order to increase the accuracy of the detection of eye movements during E...
Electrooculography is a technique for measuring the corneo-retinal standing potential of the human eye. The resulting signal is called the electrooculogram (EOG). The primary applications are in ophthalmological diagnosis and in recording eye movemen...
Magnetoencephalography (MEG) detects very weak magnetic fields originating from the neurons so as to study human brain functions. The original detected MEG data always include interference generated by blinks, which can be called blink artifacts. Bli...
With the development of portable EEG acquisition systems, the collected EEG has gradually changed from being multi-channel to few-channel or single-channel, thus the removal of single-channel EEG signal artifacts is extremely significant. For the art...
An efficient processing approach is essential for increasing identification accuracy since the electroencephalogram (EEG) signals produced by the Brain–Computer Interface (BCI) apparatus are nonlinear, nonstationary, and time-varying. The inter...
This manuscript describes an implementation of scripts of code aimed at reducing the influence of artifacts, specifically focused on ocular artifacts, in the measurement and processing of electroencephalogram (EEG) signals. This process is of importa...
Electrooculography (EOG) serves as a widely employed technique for tracking saccadic eye movements in a diverse array of applications. These encompass the identification of various medical conditions and the development of interfaces facilitating hum...
A wearable electroencephalogram (EEG) device for continuous monitoring of patients suffering from epilepsy would provide valuable information for the management of the disease. Currently no EEG setup is small and unobtrusive enough to be used in dail...
Electroencephalography (EEG) signal acquisition is often affected by artifacts, challenging applications such as brain disease diagnosis and Brain-Computer Interfaces (BCIs). This paper proposes TF-Denoiser, a deep learning model using a joint time-f...
Recently, the use of portable electroencephalogram (EEG) devices to record brain signals in both health care monitoring and in other applications, such as fatigue detection in drivers, has been increased due to its low cost and ease of use. However,...
Eye blink is an important and inevitable artifact during scalp electroencephalogram (EEG) recording. The main problem in EEG signal processing is how to identify eye blink components automatically with independent component analysis (ICA). Taking int...
Biopotential signals are mainly characterized by low amplitude and thus often distorted by extraneous interferences, such as power line interference in the recording environment and movement artifacts during the acquisition process. With the presence...