Machine learning algorithms for epilepsy detection based on published EEG databases: A systematic review

A Miltiadous, KD Tzimourta, N Giannakeas… - IEEE …, 2022 - ieeexplore.ieee.org
Epilepsy is the only neurological condition for which electroencephalography (EEG) is the
primary diagnostic and important prognostic clinical tool. However, the manual inspection of …

Trends of human-robot collaboration in industry contexts: Handover, learning, and metrics

A Castro, F Silva, V Santos - Sensors, 2021 - mdpi.com
Repetitive industrial tasks can be easily performed by traditional robotic systems. However,
many other works require cognitive knowledge that only humans can provide. Human-Robot …

Physical human–robot collaboration: Robotic systems, learning methods, collaborative strategies, sensors, and actuators

UE Ogenyi, J Liu, C Yang, Z Ju… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
This article presents a state-of-the-art survey on the robotic systems, sensors, actuators, and
collaborative strategies for physical human-robot collaboration (pHRC). This article starts …

Time series shapelet-based movement intention detection toward asynchronous BCI for stroke rehabilitation

T Janyalikit, CA Ratanamahatana - IEEE Access, 2022 - ieeexplore.ieee.org
Brain computer interface (BCI) systems for neurorehabilitation have received increasing
attention over the past decade. These systems provide an alternative approach to restore …

Automated classification of eight different Electroencephalogram (EEG) bands using hybrid of Fast Fourier Transform (FFT) with machine learning methods

NSM Nor, NHAH Malim, NAP Rostam… - Neuroscience …, 2022 - neuroscirn.org
Analysing and processing the EEG dataset is crucial. Countless actions have been taken to
ensure that the researcher in brain studies always achieves informative data and produces …

One‐dimensional atrous conv‐net based architecture for automatic diagnosis of epilepsy using electroencephalography signals and its brain–computer interface …

P Handa, M Gupta, E Gupta, N Goel - Expert Systems, 2024 - Wiley Online Library
Precise monitoring and diagnosis of epilepsy by manual analysis of EEG signals are
challenging due to the low doctor‐to‐patient ratio, and shortage of medical resources. To …

Active touch classification using EEG signals

V Aspiotis, D Peschos, KD Tzimourta… - 2021 6th South-East …, 2021 - ieeexplore.ieee.org
Touch is a fundamental aspect of human interaction with the surrounding environment. It
affects individuals' development in different manners and figures prominently in everyday …

An experimental protocol for exploration of stress in an immersive VR scenario with EEG

A Miltiadous, V Aspiotis, K Sakkas… - 2022 7th South-East …, 2022 - ieeexplore.ieee.org
Stress is a subject always relevant to scientific research due to the numerous implications in
human life. Typical biomarkers used in the physiological evaluation of stress include …

Feature Extraction for a Genetic Programming-Based Brain-Computer Interface

GH de Souza, GO Faria, LP Motta… - Brazilian Conference on …, 2022 - Springer
Abstract Brain-Computer Interfaces (BCI) open a two-way communication channel between
a computer and the brain: while the brain can control the computer, the computer can induce …

Versatile brain-computer-interface for severely-disabled people

S Masaad, S Jassim, L Mahdi… - International Journal of …, 2021 - journal.uob.edu.bh
A versatile Brain Computer Interface (BCI) system is designed and implemented to assist
people with severe disabilities in achieving a fair level of autonomy. The versatility of the …