[HTML][HTML] Epileptic EEG patterns recognition through machine learning techniques and relevant time–frequency features

S Chaibi, C Mahjoub, W Ayadi… - Biomedical Engineering …, 2024 - degruyter.com
Objectives The present study is designed to explore the process of epileptic patterns'
automatic detection, specifically, epileptic spikes and high-frequency oscillations (HFOs), via …

A minimalist method toward severity assessment and progression monitoring of obstructive sleep apnea on the edge

MJ Rahman, BI Morshed - ACM Transactions on Computing for …, 2021 - dl.acm.org
Artificial Intelligence-enabled applications on edge devices have the potential to
revolutionize disease detection and monitoring in future smart health (sHealth) systems. In …

Smart health integrated framework and topology (SHIFT) for smart and connected community

BI Morshed - 2021 IEEE International Conference on Electro …, 2021 - ieeexplore.ieee.org
A smart and connected communities (S&CC) will utilize existing and emerging technologies
to collect heterogeneous spatiotemporally distributed data and artificial intelligence (AI) to …

Meticulous Deep Learning Evolved Drowse Orchestrate Emotionless Community sleep Apnea

R Uma, A Devi, A Imayavathi… - … , Computing and Internet …, 2022 - ieeexplore.ieee.org
It's far more important to become aware of sleep stages for the prognosisof sleep issues.
There are a variety of sleep problems, due to the factobstructive sleep apnea (OSA) is one of …

Automatic Sleep Scoring Toolbox and Its Application in Sleep Apnea

R Yan, F Li, X Wang, T Ristaniemi, F Cong - E-Business and …, 2020 - Springer
Sleep scoring is a fundamental but time-consuming process in any sleep laboratory.
Automatic sleep scoring is crucial and urgent to help address the increasing unmet needs …