Application of artificial intelligence in the diagnosis of sleep apnea
G Bazoukis, SC Bollepalli, CT Chung, X Li… - Journal of Clinical …, 2023 - jcsm.aasm.org
Study Objectives: Machine learning (ML) models have been employed in the setting of sleep
disorders. This review aims to summarize the existing data about the role of ML techniques …
disorders. This review aims to summarize the existing data about the role of ML techniques …
Obstructive sleep apnea screening by heart rate variability-based apnea/normal respiration discriminant model
C Nakayama, K Fujiwara, Y Sumi… - Physiological …, 2019 - iopscience.iop.org
Objective: Obstructive sleep apnea (OSA) is a common sleep disorder; however, most
patients are undiagnosed and untreated because it is difficult for patients themselves to …
patients are undiagnosed and untreated because it is difficult for patients themselves to …
Clinical usefulness of new RR interval analysis using the wearable heart rate sensor WHS-1 to identify obstructive sleep apnea: OSA and RRI analysis using a …
T Arikawa, T Nakajima, H Yazawa, H Kaneda… - Journal of Clinical …, 2020 - mdpi.com
Obstructive sleep apnea (OSA) is highly associated with cardiovascular diseases, but most
patients remain undiagnosed. Cyclic variation of heart rate (CVHR) occurs during the night …
patients remain undiagnosed. Cyclic variation of heart rate (CVHR) occurs during the night …
Analysis of heart rate signals during meditation using visibility graph complexity
M Nasrolahzadeh, Z Mohammadpoory… - Cognitive …, 2019 - Springer
In the dynamics analysis of heart rate, the complexity of visibility graphs (VGs) is seen as a
sign of short term variability in signals. The present study was conducted to investigate the …
sign of short term variability in signals. The present study was conducted to investigate the …
Cardiovascular changes in children with obstructive sleep apnea and obesity after treatment with noninvasive ventilation
VG Kirk, H Edgell, H Joshi, E Constantin… - Journal of Clinical …, 2020 - jcsm.aasm.org
Study Objectives: Adults with obesity and obstructive sleep apnea (OSA) are at risk for
cardiometabolic disease, and this risk likely extends to children with both conditions …
cardiometabolic disease, and this risk likely extends to children with both conditions …
Cardiac parasympathetic index identifies subjects with adult obstructive sleep apnea: A simultaneous polysomnographic-heart rate variability study
M Salsone, B Vescio, A Quattrone, F Roccia… - PloS one, 2018 - journals.plos.org
Objective To evaluate circadian fluctuations and night/day ratio of Heart Rate Variability
(HRV) spectral components in patients with obstructive sleep apnea (OSA) in comparison …
(HRV) spectral components in patients with obstructive sleep apnea (OSA) in comparison …
Missing RRI interpolation algorithm based on locally weighted partial least squares for precise heart rate variability analysis
K Kamata, K Fujiwara, T Kinoshita, M Kano - Sensors, 2018 - mdpi.com
The RR interval (RRI) fluctuation in electrocardiogram (ECG) is called heart rate variability
(HRV), which reflects activities of the autonomic nervous system (ANS) and has been used …
(HRV), which reflects activities of the autonomic nervous system (ANS) and has been used …
[PDF][PDF] Analysis of efficient biometric index using heart rate variability for remote monitoring of obstructive sleep apnea
Objective: Obstructive sleep apnea (OSA) associated health problems are undiagnosed due
to the expensive and realistic limitations of overnight PSG examination. In this research, an …
to the expensive and realistic limitations of overnight PSG examination. In this research, an …
Physiological signals fusion oriented to diagnosis-A review
YF Uribe, KC Alvarez-Uribe… - Advances in Computing …, 2018 - Springer
The analysis of physiological signals is widely used for the development of diagnosis
support tools in medicine, and it is currently an open research field. The use of multiple …
support tools in medicine, and it is currently an open research field. The use of multiple …
Literature Review of Deep Learning for Physiological signal Analysis
N Ortiz, RDH Beleno, MA Pérez… - Authorea …, 2023 - essopenarchive.org
Deep Learning (DL) has proved to be a promising methodology for classification,
recognition, prediction and end-to-end tasks. Recently it has proved its high potential in …
recognition, prediction and end-to-end tasks. Recently it has proved its high potential in …