[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 …

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 …

Sleep Apnea Detection Method Based on Improved Random Forest.

X Wan, Y Liu, L Yang, C Zeng… - International Journal of …, 2023 - search.ebscohost.com
Random forest (RF) helps to solve problems such as the detection of sleep apnea (SA) by
constructing multiple decision trees, but there is no definite rule for the selection of input …

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 …

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 …

Sleep apnea classification using random forest via ECG

AP Razi, Z Einalou, M Manthouri - Sleep and Vigilance, 2021 - Springer
Sleep apnea (SA) is among the most common sleep-related disorders, which is defined as
the interruption of airflow in the airways for at least 10 s. Apnea can lead to different types of …

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 …

Diagnosis of Sleep Apnea using Artificial neural network and binary particle Swarm optimization for feature selection

S Surani, A Sheta, H Turabieh, J Park, S Mathur… - Chest, 2019 - journal.chestnet.org
PURPOSE: Sleep apnea (SA) is known as one of the significant and well-known types of
sleep disorders. SA occurs with an intermittent stopping or reduction of breathing during …

Development of a sleep apnea detection algorithm using long short-term memory and heart rate variability

A Iwasaki, C Nakayama, K Fujiwara… - 2019 41st Annual …, 2019 - ieeexplore.ieee.org
Sleep apnea syndrome (SAS) is a prevalent disorder which causes daytime fatigue with the
increased risk of lifestyle diseases. A large number of patients are undiagnosed and …