Obstructive sleep apnoea detection using convolutional neural network based deep learning framework
This letter presents an automated obstructive sleep apnoea (OSA) detection method with
high accuracy, based on a deep learning framework employing convolutional neural …
high accuracy, based on a deep learning framework employing convolutional neural …
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 …
Automatic identification of schizophrenia using EEG signals based on discrete wavelet transform and RLNDiP technique with ANN
Schizophrenia (ScZ) is a detrimental condition of the brain often associated with depression,
anxiety, and socio-psychological problems. In the traditional diagnosis approach, the results …
anxiety, and socio-psychological problems. In the traditional diagnosis approach, the results …
Performance evaluation of the spectral autocorrelation function and autoregressive models for automated sleep apnea detection using single-lead ECG signal
Background and objective: This paper addresses the automated recognition of obstructive
sleep apnea (OSA) from the analysis of single-lead ECG signals. This is one of the most …
sleep apnea (OSA) from the analysis of single-lead ECG signals. This is one of the most …
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 …
Computer aided detection of breathing disorder from ballistocardiography signal using convolutional neural network
Sleep-related breathing disorders are diseases related to pharyngeal airway collapse. It can
lead to several health problems such as somnolence, poorer daytime cognitive …
lead to several health problems such as somnolence, poorer daytime cognitive …
[HTML][HTML] Apnea detection in polysomnographic recordings using machine learning techniques
M Piorecky, M Bartoň, V Koudelka, J Buskova… - Diagnostics, 2021 - mdpi.com
Sleep disorders are diagnosed in sleep laboratories by polysomnography, a multi-
parameter examination that monitors biological signals during sleep. The subsequent …
parameter examination that monitors biological signals during sleep. The subsequent …
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 …
Multi-bit Local Neighborhood Difference Pattern Optimization for Seizure Detection of West Syndrome EEG Signals
W Zhang, D Wu, J Cao, L Jiang… - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
West syndrome is a common age-related epileptic encephalopathy, which seriously
threatens children's intellectual development. The accurate detection of seizures in the …
threatens children's intellectual development. The accurate detection of seizures in the …
Gabor filter-based one-dimensional local phase descriptors for obstructive sleep apnea detection using single-lead ECG
TS Kumar, V Kanhangad - IEEE sensors letters, 2018 - ieeexplore.ieee.org
Obstructive sleep apnea (OSA) isa sleep disorder that causes abnormal and periodic breath
interruptions during sleep. In this article, we present a novel one-dimensional (1-D) phase …
interruptions during sleep. In this article, we present a novel one-dimensional (1-D) phase …