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周期性腿部运动检测器的设计与验证

Design and validation of a periodic leg movement detector.

作者信息

Moore Hyatt, Leary Eileen, Lee Seo-Young, Carrillo Oscar, Stubbs Robin, Peppard Paul, Young Terry, Widrow Bernard, Mignot Emmanuel

机构信息

Center for Sleep Sciences and Medicine, Stanford University, Palo Alto, California, United States of America; Department of Electrical Engineering, Stanford University, Palo Alto, California, United States of America.

Center for Sleep Sciences and Medicine, Stanford University, Palo Alto, California, United States of America.

出版信息

PLoS One. 2014 Dec 9;9(12):e114565. doi: 10.1371/journal.pone.0114565. eCollection 2014.

Abstract

Periodic Limb Movements (PLMs) are episodic, involuntary movements caused by fairly specific muscle contractions that occur during sleep and can be scored during nocturnal polysomnography (NPSG). Because leg movements (LM) may be accompanied by an arousal or sleep fragmentation, a high PLM index (i.e. average number of PLMs per hour) may have an effect on an individual's overall health and wellbeing. This study presents the design and validation of the Stanford PLM automatic detector (S-PLMAD), a robust, automated leg movement detector to score PLM. NPSG studies from adult participants of the Wisconsin Sleep Cohort (WSC, n = 1,073, 2000-2004) and successive Stanford Sleep Cohort (SSC) patients (n = 760, 1999-2007) undergoing baseline NPSG were used in the design and validation of this study. The scoring algorithm of the S-PLMAD was initially based on the 2007 American Association of Sleep Medicine clinical scoring rules. It was first tested against other published algorithms using manually scored LM in the WSC. Rules were then modified to accommodate baseline noise and electrocardiography interference and to better exclude LM adjacent to respiratory events. The S-PLMAD incorporates adaptive noise cancelling of cardiac interference and noise-floor adjustable detection thresholds, removes LM secondary to sleep disordered breathing within 5 sec of respiratory events, and is robust to transient artifacts. Furthermore, it provides PLM indices for sleep (PLMS) and wake plus periodicity index and other metrics. To validate the final S-PLMAD, experts visually scored 78 studies in normal sleepers and patients with restless legs syndrome, sleep disordered breathing, rapid eye movement sleep behavior disorder, narcolepsy-cataplexy, insomnia, and delayed sleep phase syndrome. PLM indices were highly correlated between expert, visually scored PLMS and automatic scorings (r² = 0.94 in WSC and r² = 0.94 in SSC). In conclusion, The S-PLMAD is a robust and high throughput PLM detector that functions well in controls and sleep disorder patients.

摘要

周期性肢体运动(PLMs)是由睡眠期间相当特定的肌肉收缩引起的发作性、非自主运动,可在夜间多导睡眠图(NPSG)期间进行评分。由于腿部运动(LM)可能伴有觉醒或睡眠片段化,高PLM指数(即每小时PLMs的平均数)可能会对个体的整体健康和幸福感产生影响。本研究介绍了斯坦福PLM自动检测器(S-PLMAD)的设计与验证,这是一种用于对PLM进行评分的强大的自动腿部运动检测器。本研究的设计与验证使用了威斯康星睡眠队列(WSC,n = 1073,2000 - 2004年)成年参与者以及后续斯坦福睡眠队列(SSC)患者(n = 760,1999 - 2007年)在进行基线NPSG时的研究数据。S-PLMAD的评分算法最初基于2007年美国睡眠医学协会的临床评分规则。它首先在WSC中使用手动评分的LM与其他已发表的算法进行测试。然后对规则进行修改,以适应基线噪声和心电图干扰,并更好地排除与呼吸事件相邻的LM。S-PLMAD采用了心脏干扰的自适应噪声消除和噪声底限可调检测阈值,在呼吸事件的5秒内去除继发于睡眠呼吸障碍的LM,并且对瞬态伪影具有鲁棒性。此外,它还提供睡眠期间的PLM指数(PLMS)以及觉醒加周期性指数和其他指标。为了验证最终的S-PLMAD,专家对78项正常睡眠者以及患有不宁腿综合征、睡眠呼吸障碍、快速眼动睡眠行为障碍、发作性睡病 - 猝倒、失眠和睡眠相位延迟综合征患者的研究进行了视觉评分。专家视觉评分的PLMS与自动评分之间的PLM指数高度相关(WSC中r² = 0.94,SSC中r² = 0.94)。总之,S-PLMAD是一种强大且高通量的PLM检测器,在对照组和睡眠障碍患者中表现良好。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cbab/4260847/b74f12e1e75d/pone.0114565.g001.jpg

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