Possibility of ECGs to improve reliability of detection system of inclining sleep stages by grouped a waves
Possibility of ECGs to improve reliability of detection system of inclining sleep stages by grouped a waves
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心电图通过分组波提高倾斜睡眠阶段检测系统可靠性的可能性
DOI：
10.1109/iembs.1993.979203
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发表时间：
1993
期刊：
影响因子：
--
通讯作者：
N. Daimon
中科院分区：
文献类型：
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作者：
S. Ninomija;M. Funada;Y. Yazu;H. Ide;N. Daimon
为了预防交通事故的发生，开发了一种能及时发现驾驶员睡眠状态并对驾驶员进行危险状态预警的系统。我们发现在驾驶员的睡眠状态下会出现一种特殊的脑电现象，称为A波群，并将A波群所表征的睡眠状态定义为“倾斜睡眠（低清醒）阶段”，然后，我们设计了一个利用A波群识别驾驶员倾斜睡眠阶段的子系统。分系统的第一类误差为2%，第二类误差为25 ~ 35%。为了提高系统的可靠性，我们对驾驶过程中的心电图进行了详细的分析。结果表明，EEG更适合于驾驶员的睡眠状态，ECG也被用来提高这种检测子系统的可靠性。1 .引言重要的是要开发一个系统，以防止由驾驶员打瞌睡造成的交通事故。我们分析了在驾驶汽车或其他简单的工作时的脑电图（EEGa）。作为结果。我们发现，在大多数情况下，会出现一种特殊的EEC 8，称为A波群。然后将出现a波群的状态定义为“倾斜睡眠阶段”，并设计了一个利用a波群自动检测倾斜睡眠阶段的系统。系统不能检测倾斜睡眠的比率为2%，系统将非倾斜睡眠阶段检测为倾斜睡眠阶段的比率约为25%-35%。由于要求不忽略这种检测系统的休眠阶段，因此使该系统满足这种性质。但我们希望改进系统更可靠，然后我们不仅测量EEG，还测量心电图（ECC）并分析它们。因为据报道，ECG与人类的疲劳密切相关。在人体工程学领域。本文分析了脑电图和心电图，观察了两者之间的关系，并探讨了心电图作为完善睡眠分期检测系统的可能性。
In order to prevent traffic accidents, developing a system which find out sleepy states of drivers and warning them the dangerous state. W e have found that special EEG8 called grouped a waves appear in sleepy state of drivers, and defined the sleepy states characterized by grouped a waves as ’inclining sleep (low awake) stage‘, And then, we made a subsystem to find out inclining Sleep stages of drivers using grouped a waves. The first kind of error about the subsystem is 2% and tne second kind Of that is 25”35%. In order to improve the reliability of the system, we analyze ECG6 as detail as EEGs during driving. As the results, EEGs is more suitable to sleepy states of drivers and ECGs are also used t o improve the reliability of such a detection-subsystem. 1 . INTRODUCTION It is important to develop a system to prevent traffic accidents caused by drivers‘ dozing off. We have analyzed electroencephalograms (EEGa) during driving a car or other simple works. As the results. we find out the fact that a special EEC8 called as grouped a waves appear in most cases. Then we defined the state which is characterized by the appearance o f grouped a waves as ‘inclining sleep stage’ and made a system which automatically detects inclining sleep stage using grouped a waves‘’. The ratio which the system can not detect inclining sleep is 2% and the ratfo which the system detects non-inclining sleep stage as inclining sleep stage is about 25%-35%. Since it is required not to overlook sleepy stages to such a detection system, the system w e made satisfied such property. But we wish to refine the system more reliable, and then we measure not only EEGs but also electrocardiographs (ECCs) and analyze them. Because i t is reported that ECGs are deeply concerned with fatigue of human beings‘’. in t h e f i led of ergonomics. In this paper, we analyze both of EEGs and ECGs, observe the relations between them, and discuss the possibility of ECGs to refine the detection system of fnclining sleep stages.