scholarly journals 0439 Nonlinear Dynamics Forecasting for Personalize Prognosis of Obstructive Sleep Apnea Onsets

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A168-A169
Author(s):  
T Le
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Real Time ◽  
Dirichlet Process ◽  
Clinical Symptoms ◽  
Risk Indicators ◽  
Dirichlet Process Mixture ◽  
Obstructive Sleep ◽  
Estimated Risk ◽  
Normal States

Abstract Introduction The emphasis on disease prevention, early detection, and preventive treatments will revolutionize the way sleep clinicians evaluate their patients. Obstructive Sleep Apnea (OSA) is one of the most prevalent sleep disorders with approximately 100 millions patients been diagnosed worldwide. The effectiveness of sleep disorder therapies can be enhanced by providing personalized and real-time prediction of OSA episode onsets. Previous attempts at OSA prediction are limited to capturing the nonlinear, nonstationary dynamics of the underlying physiological processes. Methods This paper reports an investigation into heart rate dynamics aiming to predict in real time the onsets of OSA episode before the clinical symptoms appear. The method includes (a) a representation of a transition state space network to characterize dynamic transition of apneic states (b) a Dirichlet-Process Mixture-Gaussian-Process prognostic method for estimating the distribution of the time estimate the remaining time until the onset of an impending OSA episode by considering the stochastic evolution of the normal states to an anomalous (apnea) Results The approach was tested using three datasets including (1) 20 records from 14 OSA subjects in benchmark ECG apnea databases (Physionet.org), (2) records of eight subjects from previous work. The average prediction accuracy (R2) is reported as 0.75%, with 87% of observations within the 95% confidence interval. Estimated risk indicators at 1 to 3 min till apnea onset are reported as 85.8 %, 80.2 %, and 75.5 %, respectively. Conclusion The present prognosis approach can be integrated with wearable devices to facilitate individualized treatments and timely prevention therapies. Support N/A

scholarly journals PREVALENCE OF OBSTRUCTIVE SLEEP APNEA IN AN INDIAN POPULATION: USING STOPBANG QUESTIONNAIRE

2018 ◽  
Vol 11 (11) ◽  
pp. 100 ◽  
Author(s):  
Snigdha Pattanaik ◽  
Rajagopal R ◽  
Neeta Mohanty ◽  
Swati Pattanaik
Keyword(s):  
Quality Of Life ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Clinical Symptoms ◽  
Age Groups ◽  
Age Group ◽  
Prime Concern ◽  
Obstructive Sleep ◽  
Significant Difference

Objective: Obstructive sleep apnea (OSA) is a condition characterized by complete/partial obstruction of the upper airway that disrupts normal sleep pattern. It has become highly prevalent and negatively affects the quality of life. Reports show ≥4% of men and ≥2% of women, and mostly, the obese individuals are affected by OSA. OSA is independently associated with an increased likelihood of hypertension, cardiovascular disease, and diminished quality of life. Hence, it becomes a prime concern for health-care personnel to diagnose it at earliest. A screening tool is necessary to stratify patients based on their clinical symptoms, their physical examinations, and their risk factors. Thus, this study was taken up to assess the prevalence of OSA using the STOP-Bang questionnaire.Methods: A total number of 1012 participants were selected using random sampling technique from various community health camps for the study. The participants were asked to fill in the STOP-Bang questionnaire. All questionnaire respondents were precisely briefed about this study in a face-to-face interview. Data obtained from the survey were subjected to statistics, and descriptive analysis was done.Results: The prevalence of OSA was found to be 13.7% by using the Stop Bang questionnaire. It was found that the prevalence of OSA was highest in the age group of 50–59 (21.7%) and least in the age group of 18–29 (12.0%). Gender-wise distribution of OSA based on the scoring was seen to be more, among males (14.8%) and females showed a prevalence of 12.9%.Conclusion: This study concludes that the STOP-Bang method of screening showed a prevalence of 13.7%. However, the prevalence of OSA did not show any significant difference in various age groups; it was found that males had a higher prevalence of OSA compared to females.

scholarly journals Clinical symptoms and related factors of obstructive sleep apnea among overweight and obese taxi drivers

2015 ◽  
Vol 24 (4) ◽  
pp. 206-14 ◽  
Author(s):  
Agus D. Susanto ◽  
Barmawi Hisyam ◽  
Lientje S. Maurits ◽  
Faisal Yunus
Keyword(s):  
Risk Factors ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Sleep Duration ◽  
Clinical Symptoms ◽  
Taxi Drivers ◽  
Unrefreshing Sleep ◽  
Obstructive Sleep ◽  
The Family ◽  
Waking Up

Background: Obstructive sleep apnea (OSA) is common condition in commercial drivers while overweight and obesity as the most important risk factors. This study aimed to know the clinical symptoms and risk factors of OSA in overweight and obese taxi drivers in Jakarta, Indonesia. Methods: A cross-sectional study was done in 103 taxi drivers in Jakarta from November 2011–September 2013, by systematic random sampling from 10 taxi stations. Inclusion criteria were taxi drivers with body mass index (BMI) which 23–29.9 and mild or moderate OSA. Portable polysomnography (PSG) test was used to diagnose OSA. Parametric and nonparametric test were used in bivariate analysis. Logistic regression multivariable was used to final evaluate risk factors of OSA.Results: There were 54 (52.4%) of 103 drivers with OSA and 49 (47.6%) without OSA. Clinical symptoms found significantly (p<0.05) were snoring, unrefreshing sleep, occasional sleep while driving, and headache or nausea on waking up in the morning. Risk factors for OSA were increased BMI (OR=0.60, 95% CI=0.45–0.79, p=0.001), snoring history in the family (OR=4.92, 95% CI=1.82–13.31, p=0.002) and sleep duration <7 hours within 24 hours (OR=5.14, 95% CI=1.37–19.23, p=0.015).Conclusion: Clinical symptoms of OSA were snoring, unrefreshing sleep, occasional sleep while driving and headache or nausea on waking up in the morning. Risk factors of OSA were increased BMI, snoring history in the family and sleep duration <7 hours within 24 hours.

scholarly journals Analysis of the Correlation between Sleep Hygiene and Clinical Symptoms in Obstructive Sleep Apnea Patients

2011 ◽  
Vol 145 (2_suppl) ◽  
pp. P130-P130
Author(s):  
Joonseok Lee ◽  
Kunhee Lee ◽  
Seungyoup Shin ◽  
Sungwan Kim ◽  
Su Young Jung
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Clinical Symptoms ◽  
Sleep Hygiene ◽  
Obstructive Sleep

scholarly journals Yolo4Apnea: Real-time Detection of Obstructive Sleep Apnea

2020 ◽  
Author(s):  
Sondre Hamnvik ◽  
Pierre Bernabé ◽  
Sagar Sen
Keyword(s):  
Obstructive Sleep Apnea ◽  
Heart Disease ◽  
Deep Learning ◽  
Sleep Apnea ◽  
Real Time ◽  
Source Code ◽  
Learning System ◽  
Breathing Patterns ◽  
Obstructive Sleep ◽  
Abdominal Breathing

Obstructive sleep apnea is a serious sleep disorder that affects an estimated one billion adults worldwide. It causes breathing to repeatedly stop and start during sleep which over years increases the risk of hypertension, heart disease, stroke, Alzheimer's, and cancer. In this demo, we present Yolo4Apnea a deep learning system extending You Only Look Once (Yolo) system to detect sleep apnea events from abdominal breathing patterns in real-time enabling immediate awareness and action. Abdominal breathing is measured using a respiratory inductance plethysmography sensor worn around the stomach. The source code is available at https://github.com/simula-vias/Yolo4Apnea

scholarly journals Clinical Symptoms Associated With Brief Obstructive Sleep Apnea in Normal Infants

SLEEP ◽  
1993 ◽  
Vol 16 (5) ◽  
pp. 409-413 ◽  
Author(s):  
A. Kahn ◽  
J. Groswasser ◽  
M. Sottiaux ◽  
E. Rebuffat ◽  
M. Sunseri ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Clinical Symptoms ◽  
Obstructive Sleep
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