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  1. NTU Theses and Dissertations Repository
  2. 工學院
  3. 土木工程學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/74193
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor曾惠斌(Hui-Ping TSERNG)
dc.contributor.authorKun-Yi Chenen
dc.contributor.author陳錕鎰zh_TW
dc.date.accessioned2021-06-17T08:23:45Z-
dc.date.available2021-02-22
dc.date.copyright2021-02-22
dc.date.issued2020
dc.date.submitted2021-01-27
dc.identifier.citation(2018). 107年勞動檢查年報. 勞動部職業安全衛生署.
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Jeyhani, V., Mahdiani, S., Peltokangas, M., Vehkaoja, A. (2015). Comparison of HRV Parameters Derived from Photoplethysmography. 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), (pp. 5952-5955).
Kraus U, Schneider A, Breitner S, Hampel R, Rückerl R, Pitz M, Geruschkat U, Belcredi P, Radon K, Peters A. (2013, 5). Individual daytime noise exposure during routine activities and heart rate variability in adults: a repeated measures study. Environ Health Perspect(121), pp. 607-612.
Kristal, E. B. (1995, 7). Acute and chronic effects of noise exposure on blood pressure and heart rate among industrial employees: the Cordis Study. Archives of Environmental Health: An International Journal(50), pp. 298-304.
Leti T, Bricout VA. (2013, 1). Interest of analyses of heart rate variability in the prevention of fatigue states in senior runners. Autonomic Neuroscience, 173(1-2), pp. 14-21.
Maiti, R. (2008). Workload assessment in building construction related activities in India. Applied Ergonomics(39), pp. 754-765.
Molina GE, Fontana KE, Porto LG, Junqueira LF Jr. (2016, 8). Post-exercise heart-rate recovery correlates to resting heart-rate variability in healthy men. Clinical Autonomic Research, 26(6), pp. 415-421.
N. Pradhan, S. R. (2017). Classification of the quality of wristband-based photoplethysmography signals. IEEE International Symposium on Medical Measurements and Applications (MeMeA), (pp. 269-274).
P. Madhan Mohan, V. Nagarajan, S. R. Das and Rajesh M. (2015). Heart rate measurement from wearable Photoplethysmographic sensor using Spot and tracking methods. 2015 International Conference on Communications and Signal Processing (ICCSP), (pp. 1276-1280). Melmaruvathur.
S. Hwang, SH. Leeb. (2017). Wristband-type wearable health devices to measure construction workers'. Automation in Construction(83), pp. 330-340.
S.J. Hwang, J.O. Seo, H. Jebelli, S.H. Lee. (2016). Feasibility analysis of heart rate monitoring of construction workers. Automation in Construction(71), pp. 372-381.
Schanze, T. (2018). Compression and Noise Reduction of Biomedical Signals by Singular Value Decomposition. IFAC PapersOnLine(51-2), pp. 361-366.
Sedighi Maman Z., Alamdar Yazdi M. A., Cavuoto L. A., Megahed F. M. (2017, 11). A data-driven approach to modeling physical fatigue in the workplace using wearable sensors. applied ergonomics(65), pp. 515-529.
Tafalla, R. (1997, 4). Noise, physiology, and human performance: The potential role of effort. Journal of Occupational Health Psychology(2), pp. 148-155.
Tarvainen MP, Niskanen JP, Lipponen JA, Ranta-Aho PO, Karjalainen PA. (2014). Kubios HRV--heart rate variability analysis software. computer method and programs in biomedicine, 113(1), pp. 210-220.
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Zhu S, Tan K, Zhang X, Liu Z, Liu B. (2015). MICROST: A mixed approach for heart rate monitoring during intensive physical exercise using wrist-type PPG Signals. Annual International Conference of the IEEE Engineering in Medicine and Biology Society, (pp. 2347-2350).
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陳維政, 鄭其恒, 陳錕鎰, 楊采寧. (2019). 潛盾隧道場域勞工生理監測策略及管理期中報告.
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/74193-
dc.description.abstract營造業現場勞工安全事故一直是土木工程產業的重要議題,尤其高風險的特殊環境施工作業所造成的職業災害更是不容小覷。根據勞動部重大職業災害2009-2018年統計數據顯示,營建產業僱傭人數只佔整體產業的9%,卻造成整體職業災害中致死人數的47%。並根據其細部統計,近年來營造業現場中之侷限空間造成的職災比例逐年升高,其中隧道施工場所亦為此類現場,因此屬高風險場域。造成勞工安全事故發生的原因,其中以疲勞與精神壓力最為普遍,在長時間精神壓力下亦會累積疲勞程度。因此,加強勞工精神壓力的管理,預先在可能產生意外的情況下警示勞工,防患未然,有效降低勞安事故的發生機率,是本篇論文所要探討之重點。根據文獻得知,精神壓力可藉由個人心理指標心率變異數(Heart Rate Varability,HRV)計算,而心率則是運算心率變異數指標中數據的起點。因此,本研究引進目前新興科技:光體積變化描記圖法(Photoplethysmography,PPG) 技術之心率感測手環,在不影響勞工施作工項的條件下,於隧道施作現場進行數據取樣,收集現場勞工的心率時序變化資料。本研究使用國科會相關研究「隧道工程局限空間環境勞工生理監測策略及管理系統之研究」中研究人員陳維政博士生收集之數據,以當事人知情同意下進行數據後續處理。數據收集隧道施工中重點8個工項進行一個月數據收集,後續心率變異數各指標以KubiosHRV軟體運算。評估以不同工項、工時、環境條件(噪音)下,勞工的心理壓力程度。依據本研究結果發現,長時間施作隧道內部工項之勞工心理壓力程度較高,因此判斷為重點監測族群;而工作時段以下午時段顯示勞工心理壓力程度較高,推斷因工作負荷的累積與下午工時較長導致;噪音部分,根據統計結果顯示,受噪音影響之工項勞工中,高噪音程度與低程度之心率變異數指標的平均值無明顯差距,但以台車運輸手及潛盾機操作手心率變異數極距在高噪音環境下相對較低,推估可能原因為高噪音發生條件時為這兩項工項暫停作業階段,因此心理狀態變動較小。
本研究因數據收集現場限制造成數據中斷情形及設備本身限制,後續數據以內插方式補上中間缺漏數據,分析過程已盡可能選擇完整數據單元進行運算。因此未來研究若能夠解決數據收集的種種限制條件,並加上原本心率手環的資料儲存空間,將能夠更進一步得到更多筆的資料提供後續分析。
zh_TW
dc.description.abstracthe issue of occupational accidents in construction worksite especially for high-risk activities is always a great concern in the civil engineering industry. According to the statistical yearbook, Minister of Labor, among the number of employees within all the occupation, there are merely 9% working in construction engineering. However, it has caused almost 47% of the number of fatality. Especially in some hazardous occupations such as tunnel construction, the number has accelerated gradually. Among all the factors, fatigue and stress are the commonest. They can be detected in both physiological and psychological ways. In this paper, heart rate variability (HRV) analysis is applied, which has been proved as a representation of the psychological state, utilizing PPG wristbands, medical signal analyze software Kubios and statistical methods. The data set was collected by a senior, Wei Cheng Chen. The usage of the data set has been authorized by him officially. Data collection included 8 work tasks in the construction worksite of a shield tunnel for a month of data collection. Parameters of HRV were measured during the daytime of work from 7a.m to 7p.m. The data then be evaluated and categorized according to different tasks, work period and environmental condition, which is the noise. According to the result, we can identify that tasks which need to be conducted inside the tunnel pile up more psychological stress to the labors. In condition, the value of HRV parameters appear to be higher during the afternoon period than the ones in the morning. We can then speculate that due to the accumulative tiredness accompanied by a longer period of working hours, the labors experience more psychological stress during the afternoon hours. For the noise evaluation, within the labors that were influenced by noise condition, the mean value of their HRV parameters are surprisingly similar. However, we can see the span of them are smaller during the high-noise condition when their works are paused. Thus, their HRV parameters are relatively stable. With these result and observation, we can detect which task and when the labors feel more stressful which might cause accident. Therefore, the construction managing teams are able to prevent it in advance.
In this research, due to the limitation of the site and the uncertainty of the whole crews, the condition of data collection was not as well as we expected. Thus, we were forced to compensate the lacked data by further calculation. However, in the research, most of the data span we analyzed are the one with best completeness. If the future research is able to solve these limitations, more data can be analyzed which means the result will be even more accurate.
en
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Previous issue date: 2020
en
dc.description.tableofcontents誌謝 i
摘要 iii
Abstract v
第一章 緒論 1
1.1 研究背景與動機 1
1.1.1 侷限空間 2
1.1.2 穿戴式生理監測裝置 3
1.2 研究目的 3
1.3 論文架構 4
第二章 文獻回顧 7
2.1 侷限空間施工相關法規 7
2.1.1 職業安全法規 7
2.1.2 侷限空間法規 8
2.2 個人心率感測穿戴式裝置 9
2.2.1 PPG原理及應用 9
2.2.2 穿戴式裝置於實務之應用 10
2.3 心率變異數 10
2.3.1 心率變異數指標 10
2.3.2 心率變異數相關研究 12
2.4 噪音影響性 13
2.4.1 噪音相關法規 13
2.4.2 噪音對於勞動者影響研究 14
第三章 數據收集及分析方法 15
3.1 隧道潛盾工程 15
3.1.1 場域介紹 15
3.1.2 受試對象及工項 16
3.1.3 IRB程序及核准 18
3.1.4 儀器配置 18
3.2 心率變異數分析 20
3.2.1 數據處理方法 20
3.2.2 顯著性分析 23
3.3 小結 24
第四章 數據分析成果 25
4.1 心率變異數分析 25
4.1.1 原始數據問題 25
4.1.2 時域分析結果 26
4.1.3 頻域分析結果 28
4.2 噪音分析結果 30
4.3 小結 33
第五章 各因子影響結果討論 34
5.1 工作任務因子 34
5.1.1 地面任務 36
5.1.2 隧道內部任務 38
5.1.3 重點監測對象 38
5.2 時間影響結果 39
5.2.1 上午、下午工作時段 41
5.2.2 休息時段 42
5.2.3 疲勞程度累積 43
5.3 噪音因子影響結果 44
5.4 結果比對 46
5.5 小結 48
第六章 結論與建議 49
6.1 結論 49
6.2 研究範圍與限制 50
6.3 建議與後續研究 51
參考資料 53
dc.language.isozh-TW
dc.subjectPPGzh_TW
dc.subject隧道工程zh_TW
dc.subject心率變異數zh_TW
dc.subjectKubioszh_TW
dc.subject工作負荷zh_TW
dc.subjectKubiosen
dc.subjectPPGen
dc.subjectworkloaden
dc.subjectHRVen
dc.subjecttunnel constructionen
dc.title以PPG心率手環及心率變異數分析評估隧道工程勞工精神負荷zh_TW
dc.titleApplication of PPG Wristband on Fatigue and Stress Evaluation of Tunnel Construction Using Heart Rate Variabilityen
dc.typeThesis
dc.date.schoolyear109-1
dc.description.degree碩士
dc.contributor.oralexamcommittee陳柏翰(Po-Han CHEN),林正平(Cheng-Ping Lin),李欣運(Hsin-Yun Lee)
dc.subject.keywordPPG,隧道工程,心率變異數,Kubios,工作負荷,zh_TW
dc.subject.keywordPPG,tunnel construction,HRV,Kubios,workload,en
dc.relation.page56
dc.identifier.doi10.6342/NTU202100155
dc.rights.note有償授權
dc.date.accepted2021-01-28
dc.contributor.author-college工學院zh_TW
dc.contributor.author-dept土木工程學研究所zh_TW
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