scholarly journals Validation of a novel sleep-monitoring system for diagnosing obstructive sleep apnea: A comparison with polysomnography

2016 ◽  
Vol 12 (5) ◽  
pp. 2937-2941 ◽  
Author(s):  
Lili Meng ◽  
Huajun Xu ◽  
Jian Guan ◽  
Hongliang Yi ◽  
Hongmin Wu ◽  
...  
SLEEP ◽  
2009 ◽  
Vol 32 (5) ◽  
pp. 629-636 ◽  
Author(s):  
Rogerio Santos-Silva ◽  
Denis E. Sartori ◽  
Viviane Truksinas ◽  
Eveli Truksinas ◽  
Fabiana F. F. D Alonso ◽  
...  

SLEEP ◽  
2019 ◽  
Vol 42 (Supplement_1) ◽  
pp. A229-A229
Author(s):  
Xiaosong Dong ◽  
Hui Zhi ◽  
Jianan Chen ◽  
Fang Han ◽  
Rui Zhao

2019 ◽  
Vol 3 (1) ◽  
pp. 3 ◽  
Author(s):  
Vinh Phuc Tran ◽  
Adel Ali Al-Jumaily ◽  
Syed Mohammed Shamsul Islam

Today’s rapid growth of elderly populations and aging problems coupled with the prevalence of obstructive sleep apnea (OSA) and other health related issues have affected many aspects of society. This has led to high demands for a more robust healthcare monitoring, diagnosing and treatments facilities. In particular to Sleep Medicine, sleep has a key role to play in both physical and mental health. The quality and duration of sleep have a direct and significant impact on people’s learning, memory, metabolism, weight, safety, mood, cardio-vascular health, diseases, and immune system function. The gold-standard for OSA diagnosis is the overnight sleep monitoring system using polysomnography (PSG). However, despite the quality and reliability of the PSG system, it is not well suited for long-term continuous usage due to limited mobility as well as causing possible irritation, distress, and discomfort to patients during the monitoring process. These limitations have led to stronger demands for non-contact sleep monitoring systems. The aim of this paper is to provide a comprehensive review of the current state of non-contact Doppler radar sleep monitoring technology and provide an outline of current challenges and make recommendations on future research directions to practically realize and commercialize the technology for everyday usage.


Author(s):  
Mansi Gupta ◽  
Pranav Ish ◽  
Shibdas Chakrabarti ◽  
Manas Kamal Sen ◽  
Prabhakar Mishra ◽  
...  

Portable sleep monitoring (PSM) is a promising alternative diagnostic tool for Obstructive Sleep Apnea (OSA) especially in high burden resource limited settings. We aimed to determine the diagnostic accuracy and feasibility of PSM device-based studies in patients presenting for evaluation of OSA at a tertiary care hospital in North-India. PSM studies (using a Type-III PSM device) were compared for technical reliability and diagnostic accuracy with the standard laboratory-based Type-I polysomnography (PSG). Patients were also interviewed about their experience on undergoing an unsupervised PSM studies. Fifty patients (68% males) were enrolled in the study, of which only 30% patients expressed their concerns about undergoing unsupervised PSM studies which included safety issues, ease of use, diagnostic accuracy, etc. Technical acceptability criteria were easily met by the PSM studies with signal loss in 12% studies (complete data loss and inaccessible data in 6% studies), warranting repetition sleep studies in four patients. The overall sensitivity of PSM device (AHI ≥5) was 93.5% (area under curve; AUC: 0.87). The diagnostic accuracy was 68.5%, 80%, and 91.4% for mild, moderate, and severe cases of OSA, respectively. An overall strong correlation was observed between PSM-AHI (apnoea-hypopnoea index) and PSG (r>0.85, p≤0.001), especially in severe OSA. The observed sensitivity was >90% for AHI>20 (clinically significant OSA), with high specificity of 91% for severe OSA (AUC: 0.94, 0.97 for AHI>20, AHI>30 respectively). The overall Bland-Altman concordance analysis also demonstrated only a small dispersion for PSM studies with a Cronbach’s coefficient of 0.95. Therefore, there is good diagnostic accuracy as well as feasibility of home-based portable sleep studies in Indian patients. It can be promoted for widespread use in high burden countries like India for diagnosing and managing appropriately selected stable patients with high clinical probability of OSA, especially during the ongoing crises of COVID-19 pandemic.


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