Institute of Robotics and Cybernetics, Slovak University of Technology, Ilkovičova 3, 84104 Bratislava, Slovakia.
Adv Respir Med. 2024 Aug 14;92(4):318-328. doi: 10.3390/arm92040030.
Obstructive Sleep Apnea (OSA) is a common disorder affecting both adults and children. It is characterized by repeated episodes of apnea (stopped breathing) and hypopnea (reduced breathing), which result in intermittent hypoxia. We recognize pediatric and adult OSA, and this paper focuses on pediatric OSA. While adults often suffer from daytime sleepiness, children are more likely to develop behavioral abnormalities. Early diagnosis and treatment are important to prevent negative effects on children's development. Without the treatment, children may be at increased risk of developing high blood pressure or other heart problems. The gold standard for OSA diagnosis is the polysomnography (sleep study) PSG performed at a sleep center. Not only is it an expensive procedure, but it can also be very stressful, especially for children. Patients have to stay at the sleep center during the night. Therefore, screening tools are very important. Multiple studies have shown that OSA screening tools can be based on facial anatomical landmarks. Anatomical landmarks are landmarks located at specific anatomical locations. For the purpose of the screening tool, a specific list of anatomical locations needs to be identified. We are presenting a survey study of the automatic identification of these landmarks on 3D scans of the patient's head. We are considering and comparing both knowledge-based and AI-based identification techniques, with a focus on the development of the automatic OSA screening tool.
阻塞性睡眠呼吸暂停(OSA)是一种常见的疾病,影响成人和儿童。其特征是反复出现呼吸暂停(停止呼吸)和呼吸不足(呼吸减少),导致间歇性缺氧。我们认识到儿童和成人的 OSA,本文重点介绍儿童 OSA。虽然成年人经常患有日间嗜睡,但儿童更有可能出现行为异常。早期诊断和治疗对于防止对儿童发育产生负面影响非常重要。如果不进行治疗,儿童可能面临患高血压或其他心脏问题的风险增加。OSA 诊断的金标准是在睡眠中心进行的多导睡眠图(睡眠研究)PSG。这不仅是一个昂贵的程序,而且对儿童来说可能非常有压力。患者必须在睡眠中心过夜。因此,筛选工具非常重要。多项研究表明,OSA 筛查工具可以基于面部解剖学标志。解剖学标志是位于特定解剖位置的标志。为了筛查工具的目的,需要确定特定的解剖位置列表。我们正在进行一项关于自动识别患者头部 3D 扫描中这些标志的调查研究。我们正在考虑和比较基于知识和基于人工智能的识别技术,重点是开发自动 OSA 筛查工具。