Physical principles of brain–computer interfaces and their applications for rehabilitation, robotics and control of human brain states
Brain–computer interfaces (BCIs) development is closely related to physics. In this paper, we
review the physical principles of BCIs, and underlying novel approaches for registration …
review the physical principles of BCIs, and underlying novel approaches for registration …
Compressed sensing approach for physiological signals: A review
The immense progress in physiological signal acquisition and processing in health
monitoring allowed a better understanding of patient disease detection and diagnosis. With …
monitoring allowed a better understanding of patient disease detection and diagnosis. With …
[LIBRO][B] The illustrated wavelet transform handbook: introductory theory and applications in science, engineering, medicine and finance
PS Addison - 2017 - taylorfrancis.com
This second edition of The Illustrated Wavelet Transform Handbook: Introductory Theory and
Applications in Science, Engineering, Medicine and Finance has been fully updated and …
Applications in Science, Engineering, Medicine and Finance has been fully updated and …
A novel approach for classification of epileptic seizures using matrix determinant
Objective: An epileptic seizure is recognized as a neurological disorder caused by transient
and unexpected disturbance resulting from the excessive synchronous activity of the …
and unexpected disturbance resulting from the excessive synchronous activity of the …
Application of entropy for automated detection of neurological disorders with electroencephalogram signals: a review of the last decade (2012-2022)
An automated Neurological Disorder detection system can be considered as a cost-effective
and resource efficient tool for medical and healthcare applications. In automated …
and resource efficient tool for medical and healthcare applications. In automated …
Epileptic seizure classification using level-crossing EEG sampling and ensemble of sub-problems classifier
Epilepsy is a disorder of the brain characterized by seizures and requires constant
monitoring particularly in serious patients. Electroencephalogram (EEG) signals are …
monitoring particularly in serious patients. Electroencephalogram (EEG) signals are …
Trends in compressive sensing for EEG signal processing applications
The tremendous progress of big data acquisition and processing in the field of neural
engineering has enabled a better understanding of the patient's brain disorders with their …
engineering has enabled a better understanding of the patient's brain disorders with their …
Effective epileptic seizure detection by using level-crossing EEG sampling sub-bands statistical features selection and machine learning for mobile healthcare
Mobile healthcare is an emerging approach which can be realized by using cloud-
connected biomedical implants. In this context, a level-crossing sampling and adaptive-rate …
connected biomedical implants. In this context, a level-crossing sampling and adaptive-rate …
An EEMD-ICA approach to enhancing artifact rejection for noisy multivariate neural data
As neural data are generally noisy, artifact rejection is crucial for data preprocessing. It has
long been a grand research challenge for an approach which is able: 1) to remove the …
long been a grand research challenge for an approach which is able: 1) to remove the …
Classification of epileptic seizures using wavelet packet log energy and norm entropies with recurrent Elman neural network classifier
Electroencephalogram shortly termed as EEG is considered as the fundamental segment for
the assessment of the neural activities in the brain. In cognitive neuroscience domain, EEG …
the assessment of the neural activities in the brain. In cognitive neuroscience domain, EEG …