本文關(guān)鍵詞： 非接觸式心率測量 攝像頭相位誤差 系統(tǒng)時鐘抖動誤差 疲勞狀態(tài)檢測 多信息融合　出處：《天津大學(xué)》2016年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著生活節(jié)奏的加快和娛樂性活動的增多,人們每天用于休息的時間越來越短,從而很難能夠以較充足的精力投入到每天的工作和學(xué)習(xí)中,這不但直接影響自己的工作能力而且在特殊的行業(yè)很有可能造成極大的經(jīng)濟損失和人員傷亡。特別是在航空航天、長途運輸、大型服務(wù)器監(jiān)管等行業(yè),一旦操作員在精神疲勞狀態(tài)下工作,將會使整個系統(tǒng)處于極其危險的境地。而目前,精神疲勞的檢測設(shè)備往往都存在很多缺點,難以應(yīng)用于這些場合,因此,急需一種新型的疲勞狀態(tài)檢測系統(tǒng)。本文提出了一種基于機器視覺的多信息融合的疲勞狀態(tài)檢測系統(tǒng),首先,提出一種基于機器視覺的心率檢測方法,并針對該檢測系統(tǒng)中存在的CMOS攝像頭引起的相位誤差和圖像采集系統(tǒng)引起的時鐘抖動誤差,提出了基于幅頻疊加算法的相位誤差消除方法和基于時間表的三次樣條插值方法消除采集系統(tǒng)延時引起的隨機誤差,從而提高了該檢測系統(tǒng)的測量精度。其次,將這種心率檢測算法通過插值重構(gòu)后做心率變異性分析,并結(jié)合實驗發(fā)現(xiàn)基于機器視覺的心率變異性分析中的時域均值和頻域高頻分量與人的疲勞狀態(tài)具有一定的相關(guān)性,因此可以采用時域均值和頻域高頻分量作為疲勞狀態(tài)研究的特征量。最后,將這種心率變異性分析的疲勞狀態(tài)檢測方法和P80疲勞判定標準相結(jié)合,并通過實驗驗證了融合后的系統(tǒng)能夠判斷出受試者不同的疲勞狀態(tài)和深度疲勞狀態(tài),同時也提出了融合模型,可以根據(jù)不同的應(yīng)用場景設(shè)置不同的疲勞檢測深度,從而達到對疲勞狀態(tài)預(yù)警的作用。因此,這種基于一個攝像頭的多信息融合的疲勞狀態(tài)檢測方法可以用于不同深度的疲勞檢測和預(yù)警,并且具有操作簡單、成本低廉、無侵入性等優(yōu)點,具有極大的應(yīng)用價值。
[Abstract]:With the quickening pace of life and the increase of recreational activities, people spend less and less time to rest every day, so it is difficult to devote more energy to daily work and study. This not only directly affects their own working ability but also may cause great economic losses and casualties in special industries, especially in aerospace, long-distance transportation, large-scale server supervision and other industries. Once the operator works in the state of mental fatigue, the whole system will be in a very dangerous situation. At present, the mental fatigue detection equipment often has a lot of shortcomings, so it is difficult to be used in these situations. A new fatigue state detection system is urgently needed. In this paper, a new fatigue state detection system based on multi-information fusion of machine vision is proposed. Firstly, a heart rate detection method based on machine vision is proposed. The phase error caused by the CMOS camera and the clock jitter error caused by the image acquisition system are analyzed. The phase error elimination method based on amplitude-frequency superposition algorithm and cubic spline interpolation method based on timesheet are proposed to eliminate the random error caused by the delay of the acquisition system, thus improving the measurement accuracy of the detection system. The heart rate variability is analyzed by interpolation reconstruction. Combined with experiments, it is found that the time-domain mean and frequency-domain high-frequency components of HRV analysis based on machine vision have a certain correlation with human fatigue state. Therefore, the time-domain mean and frequency domain high-frequency component can be used as the characteristic value of fatigue state research. Finally, the fatigue state detection method of heart rate variability analysis and P80 fatigue criterion can be combined. The experimental results show that the fusion system can judge the different fatigue state and the deep fatigue state of the subjects, and the fusion model is also proposed. Different fatigue detection depth can be set according to different application scenarios, so as to achieve the function of early warning of fatigue state. This multi-information fusion fatigue state detection method based on a single camera can be used for fatigue detection and early warning at different depths, and has the advantages of simple operation, low cost, no invasion and so on. It has great application value.
【學(xué)位授予單位】：天津大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：TP391.41

【參考文獻】

相關(guān)期刊論文 前10條

1 姜兆普;許勇;趙檢群;;基于眼部特征的疲勞檢測算法[J];計算機系統(tǒng)應(yīng)用;2014年08期

2 熊慧;楊雪;周梅;李剛;林凌;;光譜儀動態(tài)采樣時間特性的研究[J];光譜學(xué)與光譜分析;2014年04期

3 韓清鵬;;利用EEG信號的小波包變換與非線性分析實現(xiàn)精神疲勞狀態(tài)的判定[J];振動與沖擊;2013年02期

4 劉丹;劉智;孫偉;董洋;劉建華;;卷簾式快門CMOS數(shù)字相機測速系統(tǒng)標定技術(shù)[J];吉林大學(xué)學(xué)報(信息科學(xué)版);2012年06期

5 袁翔;孫香梅;;疲勞駕駛檢測方法研究進展[J];汽車工程學(xué)報;2012年03期

6 李都厚;劉群;袁偉;劉浩學(xué);;疲勞駕駛與交通事故關(guān)系[J];交通運輸工程學(xué)報;2010年02期

7 董占勛;孫守遷;吳群;徐娟芳;;心率變異性與駕駛疲勞相關(guān)性研究[J];浙江大學(xué)學(xué)報(工學(xué)版);2010年01期

8 劉智;柴華;李娜娜;;CMOS圖像傳感器中卷簾式快門特性及其應(yīng)用[J];光學(xué)精密工程;2009年08期

9 毛U，

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