IEEE J Biomed Health Inform. 2023 May;27(5):2264-2275. doi: 10.1109/JBHI.2023.3235391. Epub 2023 May 4.
Alzheimer's Disease and Related Dementia (ADRD) is growing at alarming rates, putting research and development of diagnostic methods at the forefront of the biomedical research community. Sleep disorder has been proposed as an early sign of Mild Cognitive Impairment (MCI) in Alzheimer's disease. Although several clinical studies have been conducted to assess sleep and association with early MCI, reliable and efficient algorithms to detect MCI in home-based sleep studies are needed in order to address both healthcare costs and patient discomfort in hospital/lab-based sleep studies.
In this paper, an innovative MCI detection method is proposed using an overnight recording of movements associated with sleep combined with advanced signal processing and artificial intelligence. A new diagnostic parameter is introduced which is extracted from the correlation between high frequency, sleep-related movements and respiratory changes during sleep. The newly defined parameter, Time-Lag (TL), is proposed as a distinguishing criterion that indicates movement stimulation of brainstem respiratory regulation that may modulate hypoxemia risk during sleep and serve as an effective parameter for early detection of MCI in ADRD. By implementing Neural Networks (NN) and Kernel algorithms with choosing TL as the principle component in MCI detection, high sensitivity (86.75% for NN and 65% for Kernel method), specificity (89.25% and 100%), and accuracy (88% and 82.5%) have been achieved.
阿尔茨海默病及相关痴呆（ADRD）的发病率正在以惊人的速度增长，这使得医学研究人员必须将研发诊断方法放在首位。睡眠障碍已被提出作为阿尔茨海默病轻度认知障碍（MCI）的早期标志。尽管已经进行了几项临床研究来评估睡眠与早期 MCI 的关联，但需要可靠且高效的算法来检测家庭睡眠研究中的 MCI，以解决基于医院/实验室的睡眠研究中的医疗保健成本和患者不适的问题。
在本文中，提出了一种使用与睡眠相关的运动的整夜记录以及先进的信号处理和人工智能相结合的创新 MCI 检测方法。引入了一个新的诊断参数，该参数是从睡眠期间高频、与睡眠相关的运动与呼吸变化之间的相关性中提取出来的。新定义的参数，时滞（TL），被提议作为一个区分标准，表明脑干呼吸调节的运动刺激可能会调节睡眠期间的低氧血症风险，并作为 ADRD 中早期检测 MCI 的有效参数。通过使用神经网络（NN）和核算法，并选择 TL 作为 MCI 检测的主要成分，实现了高灵敏度（NN 为 86.75%，核方法为 65%）、高特异性（NN 为 89.25%，核方法为 100%）和高准确性（NN 为 88%，核方法为 82.5%）。
