Respiratory effort signal based sleep apnea detection system using improved random forest classifier

A Prabha, J Yadav, A Rani, V Singh - IETE Journal of Research, 2023 - Taylor & Francis
This work aims to develop a minimally obtrusive simple system for the automatic detection
and classification of sleep apnea (SA) events using the single-channel abdomen respiratory …

Detection and classification of sleep apnea using genetic algorithms and SVM‐based classification of thoracic respiratory effort and oximetric signal features

Z Abedi, N Naghavi… - Computational Intelligence, 2017 - Wiley Online Library
Sleep apnea is a relatively prevalent breathing disorder characterized by temporary
interruptions in airflow during sleep. There are 2 major types of sleep apnea. Obstructive …

Detection of sleep apnea from electrocardiogram and pulse oximetry signals using random forest

J Zhu, A Zhou, Q Gong, Y Zhou, J Huang, Z Chen - Applied Sciences, 2022 - mdpi.com
Sleep apnea (SA) is a common sleep disorder which could impair the human physiological
system. Therefore, early diagnosis of SA is of great interest. The traditional method of …

[HTML][HTML] ECG and SpO2 signal-based real-time sleep apnea detection using feed-forward artificial neural network

T Paul, O Hassan, K Alaboud, H Islam… - AMIA Summits on …, 2022 - ncbi.nlm.nih.gov
Sleep apnea (SA) is a common sleep disorder characterized by respiratory disturbance
during sleep. Polysomnography (PSG) is the gold standard for apnea diagnosis, but it is time …

End-to end decision support system for sleep apnea detection and Apnea-Hypopnea Index calculation using hybrid feature vector and Machine learning

RS Arslan, H Ulutas, AS Köksal, M Bakir… - Biocybernetics and …, 2023 - Elsevier
Sleep apnea is a disease that occurs due to the decrease in oxygen saturation in the blood
and directly affects people's lives. Detection of sleep apnea is crucial for assessing sleep …

[PDF][PDF] WAKE detection during sleep using random forest for sleep apnea syndrome patient

I Nakari, Y Tajima, R Takano, A Toboru… - AAAI Spring …, 2019 - ceur-ws.org
This paper proposed the new WAKE detection method for sleep apnea syndrome: SAS
patients. In many non-contact method for sleep stage estimation, it is difficult to detect WAKE …

A hybrid feature selection and extraction methods for sleep apnea detection using bio-signals

X Li, SH Ling, S Su - Sensors, 2020 - mdpi.com
People with sleep apnea (SA) are at increased risk of having stroke and cardiovascular
diseases. Polysomnography (PSG) is used to detect SA. This paper conducts feature …

Sleep apnea detection using electrocardiogram signal input to FAWT and optimize ensemble classifier

H Pant, HK Dhanda, S Taran - Measurement, 2022 - Elsevier
Sleep apnea refers to a sleep disorder consist of inconsistent breathing during sleep for
extensive duration of time. During this, one faces difficulty in breathing leading to loss of …

Automated detection of sleep apnea using sparse residual entropy features with various dictionaries extracted from heart rate and EDR signals

CSSS Viswabhargav, RK Tripathy… - Computers in biology and …, 2019 - Elsevier
Sleep is a prominent physiological activity in our daily life. Sleep apnea is the category of
sleep disorder during which the breathing of the person diminishes causing the alternation …

[PDF][PDF] Performance comparison of ANN classifiers for sleep apnea detection based on ECG signal analysis using hilbert transform

J Bali, A Nandi, PS Hiremath - International Journal Of Computers …, 2018 - researchgate.net
In this paper, a methodology for sleep apnea detection based on ECG signal analysis using
Hilbert transform is proposed. The proposed work comprises a sequential procedure of …