Figure 1
Image representing the placement of electrodes for electroencephalogram during polysomnography. The electrode placement and nomenclature follow the International 10-20 system. Illustrated by the authors. M, mastoid; F, frontal; C, central; O, occipital.
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Sleep apnea is a sleep disorder that includes symptoms such as snoring and apnea during sleep and daytime drowsiness. This disorder reduces a person’s quality of life and can also cause serious problems that interfere with one’s social life. Both non-surgical, such as positive pressure treatment, and surgical treatments can be performed to improve...
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Obstructive sleep apnea (OSA) is a common sleep disorder characterized by repetitive upper airway obstruction, intermittent hypoxemia, and recurrent awakenings during sleep. The most used treatment for this syndrome is a device that generates a positive airway pressure—Continuous Positive Airway Pressure (CPAP), but it works continuously, whether o...
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... With the recent rise in obesity and an aging population, the rate of sleep apnea is steeply increasing, necessitating further research into the condition. A diagnosis of sleep apnea requires a polysomnography test in a medical facility, which patients find burdensome because of the high costs and unfamiliar environment [3]. Moreover, it is practically challenging to refer all patients suspected of having sleep apnea for testing, making alternative pre-screening tools such as the Berlin and STOP-BANG questionnaires crucial [4]. ...
Sleep apnea has emerged as a significant health issue in modern society, with self-diagnosis and effective management becoming increasingly important. Among the most renowned methods for self-diagnosis, the STOP-BANG questionnaire is widely recognized as a simple yet effective tool for diagnosing and assessing the risk of sleep apnea. However, its sensitivity and specificity have limitations, necessitating the need for tools with higher performance. Consequently, this study aimed to enhance the accuracy of sleep apnea diagnoses by integrating machine learning with the STOP-BANG questionnaire. Research through actual cases was conducted based on the data of 262 patients undergoing polysomnography, confirming sleep apnea with a STOP-BANG score of ≥3 and an Apnea–Hypopnea Index (AHI) of ≥5. The accuracy, sensitivity, and specificity were derived by comparing Apnea–Hypopnea Index scores with STOP-BANG scores. When applying machine learning models, four hyperparameter-tuned models were utilized: K-Nearest Neighbor (K-NN), Logistic Regression, Random Forest, and Support Vector Machine (SVM). Among them, the K-NN model with a K value of 11 demonstrated superior performance, achieving a sensitivity of 0.94, specificity of 0.85, and overall accuracy of 0.92. These results highlight the potential of combining traditional STOP-BANG diagnostic tools with machine learning technology, offering new directions for future research in self-diagnosis and the preliminary diagnosis of sleep-related disorders in clinical settings.
Human being spends around one third of life in sleep, so normal sleep characteristics and its disorders have been the focus of attention of many scientists and physicians since long ago. The historical art works and scientific documents about sleep are the proof of this reality. However, modern sleep medicine with its own diagnostic procedures, therapeutic strategies, and sleep monitoring techniques is a new branch of medicine that has been introduced to the world not more than half a decade ago, primarily in the second half of the 20th century.
Physicians and scientists in any branch of medicine have encountered challenges and obstacles while taking their primary steps. It is not surprising that we, as sleep specialists and scientists, may encounter many problems during the process of developing this new branch of medicine in our country. Although these problems differ in many aspects among various countries, there are some similarities.
Since the development of sleep medicine, many professional sleep societies have evolved, many exclusive sleep journals have been published, guideline for accreditation of centers have been developed and also formalized fellowship training programs in medical universities all over the world have been established. Such developments have been helpful in reaching some milestones in overcoming some obstacles and challenges, although there is still a long way to reach the peak. Sharing the information regarding the situation of sleep medicine practice and training as well as challenges that each of us face in our daily practice and research can help us continue to improve global sleep health.
While writing this chapter we connected to the major sleep scientists and physicians all over the world and asked for sharing their knowledge of development of sleep medicine in their countries. We discovered extremely valuable resources of what is going on in the practice of sleep medicine each country. In this chapter we will discuss the topic of sleep medicine in a couple of countries including China, Iran, South Korea, Russia, India, Saudi Arabia, Vietnam, Egypt, Armenia, Turkey, Nigeria and Morroco. For each country, we will first give some general information about the countries, their health care systems, sleep medicine practices, training, fellowship programs, and sleep medicine societies. Finally, we will discuss the costs of practicing sleep medicine and go through the challenges of practicing in this new field of medicine in each country.
