Activity and Sleep Apnea Monitoring of Aged-Person using Image Processing.

D. Shin, G. H. Shin, S. Huh
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Abstract

Objective: As the rapid progress of aged society, there must be solutions of preparation against unpredicted accidents for aged solitary people. The most important thing that we must consider is the unconstraint of daily life. So, we are to develop a system and algorithm which meet our objectives. Methods: We have monitored the degree of activity of the aged solitary person. The CCD camera was used not to disturb the daily activity and we evaluated the degree of activity using image processing on personal computer. The activity monitoring during night was assumed by sleeping on the bed, so the major method was breath monitoring during sleeping. On the other hand, daily activity was monitored by wide viewing camera in the living room. To prevent the privacy trouble, the acquired image was converted to binary form and the degree of breath and moving factor was estimated. Results: In this paper we propose a new processing algorithm to accurately measure breathing characteristics in sleep apnea sufferers. We improved the conventional center-of-mass method and further applied the projection-profile method. As a result, we have improved breath measurement accuracy. In a comparison with conventional polysomnography, our method was 92% effective in detecting apnea cases. Conclusion: As a result of this study, we can monitor sleep apnea more simply and with no sleep interference. In measuring the activity of daily life, these improved algorithms were applied. So, we established a monitoring method of no-constrained, quantitative measurement for the aged solitary people during the whole day. (Journal of Korean Society of Medical Informatics 13-4, 393-401, 2007)
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基于图像处理的老年人活动与睡眠呼吸暂停监测。
目的:随着老龄化社会的快速发展,必须为独居老人的意外事故做好准备。我们必须考虑的最重要的事情是日常生活的自由。所以,我们要开发一个系统和算法来满足我们的目标。方法:对独居老人的活动程度进行监测。在不干扰日常活动的情况下,采用CCD摄像机拍摄,并在个人电脑上进行图像处理,评估活动程度。夜间活动监测以卧床方式进行,主要方法为睡眠呼吸监测。另一方面,他们的日常活动是由客厅里的宽摄像头监控的。为了防止隐私问题,将采集到的图像转换为二值形式,并对图像的呼吸程度和运动因子进行估计。结果:本文提出了一种新的处理算法,可以准确测量睡眠呼吸暂停患者的呼吸特征。对传统质心法进行了改进,进一步应用了投影剖面法。因此,我们提高了呼吸测量的准确性。与传统的多导睡眠图相比,我们的方法检测呼吸暂停病例的有效率为92%。结论:这项研究的结果是,我们可以更简单地监测睡眠呼吸暂停,没有睡眠干扰。在测量日常生活活动时,应用了这些改进的算法。为此,我们建立了一种对独居老人全天无约束、定量测量的监测方法。(韩国医学信息学会杂志13- 4,393 -401,2007)
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