Automated Schizophrenia detection using local descriptors with EEG signals
Schizophrenia (SZ) is a severe mental disorder characterized by behavioral imbalance and
impaired cognitive ability. This paper proposes a local descriptors-based automated …
impaired cognitive ability. This paper proposes a local descriptors-based automated …
Obstructive sleep apnea detection using discrete wavelet transform-based statistical features
Motivation and objective Obstructive sleep apnea (OSA) is a sleep disorder identified in
nearly 10% of middle-aged people, which deteriorates the normal functioning of human …
nearly 10% of middle-aged people, which deteriorates the normal functioning of human …
An Overview of Recent Approaches in Brain–Computer Interface Systems Using Electroencephalography
This chapter provides essential information about electroencephalography (EEG) signal
analysis for the brain–computer interface (BCI). The BCI translates the brain activity signals …
analysis for the brain–computer interface (BCI). The BCI translates the brain activity signals …
EEG-based classification of normal and seizure types using relaxed local neighbour difference pattern and artificial neural network
NJ Sairamya, MSP Subathra - Knowledge-Based Systems, 2022 - Elsevier
Diagnosis of epileptic seizure types is vital for the neurologists to comprehend the cortical
connectivity of the brain, and to initiate the apt treatment for the epileptic subjects at the …
connectivity of the brain, and to initiate the apt treatment for the epileptic subjects at the …
Advanced framework for epilepsy detection through image-based EEG signal analysis
PT Krishnan, SK Erramchetty… - Frontiers in Human …, 2024 - frontiersin.org
Background Recurrent and unpredictable seizures characterize epilepsy, a neurological
disorder affecting millions worldwide. Epilepsy diagnosis is crucial for timely treatment and …
disorder affecting millions worldwide. Epilepsy diagnosis is crucial for timely treatment and …
Gabor filter-based statistical features for ADHD detection
Attention deficit/hyperactivity disorder (ADHD) is a neuropsychological disorder that occurs
in children and is characterized by inattention, impulsivity, and hyperactivity. Early and …
in children and is characterized by inattention, impulsivity, and hyperactivity. Early and …
A novel RSW&TST framework of MCPs detection for abnormal pattern recognition on large-scale time series and pathological signals in epilepsy
J Qi, Y Zhu, F Pu, P Zhang - Plos one, 2021 - journals.plos.org
To quickly and efficiently recognize abnormal patterns from large-scale time series and
pathological signals in epilepsy, this paper presents here a preliminary RSW&TST …
pathological signals in epilepsy, this paper presents here a preliminary RSW&TST …
A Proposal for a Data-Driven Approach to the Influence of Music on Heart Dynamics
E Idrobo-Ávila, H Loaiza-Correa… - Frontiers in …, 2021 - frontiersin.org
Electrocardiographic signals (ECG) and heart rate viability measurements (HRV) provide
information in a range of specialist fields, extending to musical perception. The ECG signal …
information in a range of specialist fields, extending to musical perception. The ECG signal …
Classification of ultra-short-term ECG samples: studies on events containing violence
H Ferdinando - 2020 - oulurepo.oulu.fi
Tiivistelmä Väkivalta on vakava globaali ongelma, joka saattaa aiheuttaa kohteille
huomattavaa kärsimystä ja pitkäaikaisia seuraamuksia. Se vaikuttaa kaikkiin osapuoliin …
huomattavaa kärsimystä ja pitkäaikaisia seuraamuksia. Se vaikuttaa kaikkiin osapuoliin …
A Weighted Error Distance Metrics (WEDM) for Performance Evaluation on Multiple Change‐Point (MCP) Detection in Synthetic Time Series
JP Qi, F Pu, Y Zhu, P Zhang - Computational Intelligence and …, 2022 - Wiley Online Library
Change‐point detection (CPD) is to find abrupt changes in time‐series data. Various
computational algorithms have been developed for CPD applications. To compare the …
computational algorithms have been developed for CPD applications. To compare the …