Automated detection of schizophrenia using deep learning: a review for the last decade

M Sharma, RK Patel, A Garg, R SanTan… - Physiological …, 2023 - iopscience.iop.org
Schizophrenia (SZ) is a devastating mental disorder that disrupts higher brain functions like
thought, perception, etc., with a profound impact on the individual's life. Deep learning (DL) …

Pulse oximetry SpO 2 signal for automated identification of sleep apnea: a review and future trends

M Sharma, K Kumar, P Kumar, RS Tan… - Physiological …, 2022 - iopscience.iop.org
Sleep apnea (SA) is characterized by intermittent episodes of apnea or hypopnea paused or
reduced breathing, respectively each lasting at least ten seconds that occur during sleep. SA …

[HTML][HTML] An explainable deep-learning model to stage sleep states in children and propose novel EEG-related patterns in sleep apnea

F Vaquerizo-Villar, GC Gutiérrez-Tobal, E Calvo… - Computers in Biology …, 2023 - Elsevier
Automatic deep-learning models used for sleep scoring in children with obstructive sleep
apnea (OSA) are perceived as black boxes, limiting their implementation in clinical settings …

An automated wavelet-based sleep scoring model using EEG, EMG, and EOG signals with more than 8000 subjects

M Sharma, A Yadav, J Tiwari, M Karabatak… - International Journal of …, 2022 - mdpi.com
Human life necessitates high-quality sleep. However, humans suffer from a lower quality of
life because of sleep disorders. The identification of sleep stages is necessary to predict the …

A novel automated robust dual-channel EEG-based sleep scoring system using optimal half-band pair linear-phase biorthogonal wavelet filter bank

M Sharma, P Makwana, RS Chad, UR Acharya - Applied Intelligence, 2023 - Springer
Nowadays, the hectic work life of people has led to sleep deprivation. This may further result
in sleep-related disorders and adverse physiological conditions. Therefore, sleep study has …

SelANet: decision-assisting selective sleep apnea detection based on confidence score

B Bark, B Nam, IY Kim - BMC Medical Informatics and Decision Making, 2023 - Springer
Background One of the most common sleep disorders is sleep apnea syndrome. To
diagnose sleep apnea syndrome, polysomnography is typically used, but it has limitations in …

[HTML][HTML] Ventilation causing an average CO2 concentration of 1,000 ppm negatively affects sleep: A field-lab study on healthy young people

M Kang, Y Yan, C Guo, Y Liu, X Fan, P Wargocki… - Building and …, 2024 - Elsevier
Poor bedroom ventilation, leading to poor indoor air quality (IAQ), has been shown to reduce
sleep quality. Ventilation causing a carbon dioxide (CO 2) concentration of 1,000 ppm is …

Automated insomnia detection using wavelet scattering network technique with single-channel EEG signals

M Sharma, D Anand, S Verma, UR Acharya - Engineering Applications of …, 2023 - Elsevier
Sleep is crucial for both the physical and mental well-being of human life. As the sleep
pattern varies in every individual, it is essential to develop a methodology that enables us to …

Multi-resolution assessment of ECG sensor data for sleep apnea detection using wide neural network

K Gupta, V Bajaj, S Jain - IEEE Sensors Journal, 2024 - ieeexplore.ieee.org
Sleep apnea (SA) is a noncommunicable medical condition associated with sleep,
characterized by recurrent interruptions in breathing during sleep. Electrocardiogram (ECG) …

[HTML][HTML] DCDA-Net: dual-convolutional dual-attention network for obstructive sleep apnea diagnosis from single-lead electrocardiograms

N Ullah, T Mahmood, SG Kim, SH Nam, H Sultan… - … Applications of Artificial …, 2023 - Elsevier
Obstructive sleep apnea (OSA) is a breathing-related chronic disease in which the soft
palate and tongue collapse and block the upper airway for at least 10 s during sleep. It can …