Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/9098
DC FieldValueLanguage
dc.contributor張振豪zh_TW
dc.contributorChen-Hao Changen_US
dc.contributor.author羅華義zh_TW
dc.contributor.authorLuo, Hua-Ien_US
dc.contributor.other電機工程學系所zh_TW
dc.date2012en_US
dc.date.accessioned2014-06-06T06:42:39Z-
dc.date.available2014-06-06T06:42:39Z-
dc.identifierU0005-2108201201320800en_US
dc.identifier.citation[1] Anonymous, “12-Lead ECG monitoring with EASI lead system”, Agilent Technologies, application note, 2000. [2] 陳學儒, A High-Precision Real-Time Premature Ventricular Contraction(PVC) Detection System Based on Wavelet Transform, 國立中興大學電機工程學系碩士學位論文, 2011. [3] N. V. Thakor and Y.-S. Zhu, “Applications of adaptive filtering to ECG analysis: noise cancellation and arrhythmia detection,” IEEE Transactions on Biomedical Engineering, vol. 38, no. 8, pp. 785-794, 1991. [4] 吳欣龍,“Introduction to AMBA Bus System,”工研院系統晶片技術中心. [5] A. Malliani, F. Lombardi, and M. Pagani, “Power spectrum analysis of heart rate variability: a tool to explore neural regulatory mechanisms”, Br Heart J 1994 71: 1-2. [6] 韓欽銓,陳映濃,王宇晨,黃敏彧, “打瞌睡警告及防撞系統,” 行政院國家科學委員會補助專題研究計畫期中報告, 2009. [7] R.-D. Chiu and S.-H. Wu, “A BAN system for real time ECG monitoring : From wired to wireless measurements,” in Proc. IEEE Wireless Communications and Networking Conference (WCNC), March.2011, pp. 2107 – 2112. [8] V. Mukala, V. Lakafosis, A. Traille, and M.M. Tentzeris, “A novel Zigbee-based low-cost, low-power wireless EKG system,” in Proc. IEEE Microwave Symposium Digest (MTT), May. 2010, pp. 624 – 627. [9] B. A. Walker, A. H. Khandoker, and J. Black, “Low cost ECG monitor for developing countries,” in Proc. IEEE Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), Dec. 2009, pp. 195 – 199. [10] 曾永進, The Wireless Portable ECG Monitoring System via Bluetooth, 逢甲大學自動控制工程學系碩士論文, 2005. [11] A. Malliani, F. Lombardi, and M. Pagani, “Power spectrum analysis of heart rate variability: a tool to explore neural regulatory mechanisms,” British Heart Journal, 1994. [12] 方馨譽, “利用智慧型ECG信號處理來顯示人類情緒指數,” 大專生參與專題研究計劃, 2001. [13] P. Naiyanetr, P. Charoentong, and W. Charoensuk, “ECG system with heart rate variability application,” IEEE Region 10 Conference, Nov. 2004, pp. 435 - 437. [14] E. Michail, A. Kokonozi, and I. Chouvarda, “EEG and HRV markers of sleepiness and loss of control during car driving,” in Proc. Engineering in Medicine and Biology Society (EMBS), Aug. 2008, pp. 2566 – 2569. [15] W. Wu and J. Lee, “Improvement of HRV methodology for positive/negative emotion assessment,” in Proc. Collaborative Computing: Networking, Applications and Worksharing, Nov. 2009, pp. 1 – 6. [16] 林育德, Principle and Verification of ECG Signal Amplifier Design, 逢甲大學自動控制工程學系專題論文, 2005. [17] 黃明智, A Digital Signal Processing Based Method for Establishing the relationship Between the HRV and RDI, 國立中山大學機械與機電工程學系碩士論文, 2006. [18] 劉芸澧, Hardware Implementation of Wearable Electrocardiograph and Development of Nonlinear Analysis for Physiological Signals, 逢甲大學自動控制工程學系碩士論文, 2003. [19] 黃楷倫, Effect of Intermittent Hypoxia on Electroencephalogram, Blood Pressure and Cardiovascular Neural Regulation in Rats, 慈濟大學神經科學研究所碩士論文, 2008. [20] 胡威志, The Development of a Portable Biosignal Recording System, 中原大學生物醫學工程學系碩士學位論文, 2007. [21] Y.-W. Bai, W.-Y. Chu, C.-Y. Chen, Y.-T. Lee, Y.-C. Tsai, and C.-H. Tsai, “Adjustable 60Hz noise reduction by a notch filter for ECG signals,” in Proc. IEEE Instrumentation and Measurement Technology Conference, May 2004, pp. 1706 - 1711. [22] http://zh.wikipedia.org/wiki/ECG [23] http://zh.wikipedia.org/wiki/數字濾波器 [24] http://www.polar.fi/e_manuals/RCX3en_US
dc.identifier.urihttp://hdl.handle.net/11455/9098-
dc.description.abstract全世界的汽車普及率越來越高,近年來因駕駛員疲勞駕駛所引起的交通意外事故時有所聞,駕駛員之工作本質上屬於精神類型,當駕駛人疲勞時會有動作呆板、視線模糊、精神恍惚、反應遲鈍等現象,此時往往會出現短時間睡眠現象,嚴重時會失去對車輛的控制能力,此現象尤其容易發生在長時間且高速的行駛狀態,如果不經過短暫的休息或者改變駕駛人的注意力,仍勉強駕駛車輛則可能導致嚴重的交通意外發生。 一般的瞌睡的偵測法方可能使用點頭頻率或者眼部閉合的方法來判斷,但上述的方式通常是駕駛已經進入瞌睡狀態,因此無法在第一時間預防與警告駕駛人,本論文使用心率變異度(heart rate variability, HRV)在頻域上的分析來偵測駕駛人是否進入瞌睡狀態,此種方式有別於由外部擷取資訊來進行判斷,較能準確且即早的發現駕駛人是否已經進入短暫的睡眠狀態,有利於即早發出警告來防止交通意外的發生。 本論文提出的瞌睡偵測系統(drowsiness detection system)使用Cheetah development kit (CDK)來實現與驗證結果,在PC上發展出人機介面(graphical user interface, GUI),能即時的觀察到心電訊號(electrocardiography, ECG)的波形與心率變異度的功率頻譜密度(power spectral density, PSD)分析結果,本系統以嵌入式系統(embedded system)的方式實現,在硬體架構中加入軟硬體橋接器模組(HW-SW Bridge)讓擴充的硬體模組更容易整合到當前的系統中,以嵌入式系統的方式實現將有利於日後進行系統單晶片(system on chip, SOC)的發展與實現。zh_TW
dc.description.abstractVehicle penetration rate rapidly increases in the word. In recent years, car accidents caused by fatigued driving and drowsy driving are raised. Driving is spiritually exhausted types of work. There are several symptom of tired drowsy driving such as awkward movements, blurred vision, trance, unresponsive…etc.. While drowsy driving happens, it accompanies with short duration sleep and losing control of driving. Drowsy driving is usually happening during high-speed driving. If the driver doesn’t take a rest or keeps spirits up, drowsy driving might cause serious traffic accidents. Generally, measuring the frequency of nod or close of eyes are the methods to judge the drowsiness state. However, the measuring information can only be gotten during drowsy condition. Hence, it is hard to measure drowsy information and to warn drowsy driver earlier. The thesis will use frequency domain analysis of heart rate variability (HRV) to detect if drowsiness state happens. This way is different than detect by external feature. It can early and exactly detect whether short duration sleep happens. It is a profitable way to prevent traffic accidents. The thesis proposes a drowsiness detection system, which is implemented by Cheetah development kit (CDK) and uses graphical user interface (GUI) in PC. It can immediately display electrocardiography (ECG) waveform and power spectral density (PSD) analysis of heart rate variability. The system based on embedded system and hardware system added HW-SW Bridge that integrates easily for all system to promote system on chip (SOC) implementation in the future.en_US
dc.description.tableofcontents誌謝 I 中文摘要 II Abstract III 目錄 IV 圖目錄 VI 表目錄 VIII 第一章 緒論 1 1-1 研究背景與動機 1 1-2 論文架構 3 第二章 文獻探討 4 2-1 心電信號(Electrocardiography, ECG)簡介 4 2-1-1 心臟構造與除極波 4 2-1-2 艾因托文氏三角(Einthoven’s triangle) 6 2-1-3 ECG波形 8 2-2 心率變異度(Heart rate variability, HRV) 9 2-3 自律神經系統(Autonomic nervous system, ANS) 11 2-4 ECG標準資料庫 12 第三章 瞌睡偵測系統架構與理論 16 3-1 系統架構 16 3-2 小波分析(Wavelet analysis) 17 3-3 ECG雜訊源 18 3-4數位濾波器簡介 19 3-5 Advanced microcontroller bus architecture (AMBA)簡介 22 第四章 硬體實現與實驗結果 23 4-1 開發板簡介 23 4-2 硬體架構 25 4-3 軟體架講 28 4-4 硬體模組實現與驗證方法 30 4-4-1 Heart rate variability analysis (HRVA)模組 30 4-4-2 Denoise模組 34 4-4-3 HW-SW Bridge模組 37 4-5 GUI介面開發及功能說明 41 4-6 MIT-BIH資料處理 44 4-7 系統測試與驗證結果 46 4-8 電路合成 49 4-9 心率變異度功率頻譜密度分析 50 第五章 結論與未來展望 55 參考文獻 56zh_TW
dc.language.isozh_TWen_US
dc.publisher電機工程學系所zh_TW
dc.relation.urihttp://www.airitilibrary.com/Publication/alDetailedMesh1?DocID=U0005-2108201201320800en_US
dc.subject心率變異度zh_TW
dc.subjectheart rate variabilityen_US
dc.subject瞌睡偵測系統zh_TW
dc.subject人機介面zh_TW
dc.subject心電訊號zh_TW
dc.subject功率頻譜密度zh_TW
dc.subject嵌入式系統zh_TW
dc.subject軟硬體橋接器zh_TW
dc.subject系統單晶片zh_TW
dc.subjectdrowsiness detection systemen_US
dc.subjectCheetah development kiten_US
dc.subjectgraphical user interfaceen_US
dc.subjectelectrocardiographyen_US
dc.subjectpower spectral densityen_US
dc.subjectembedded systemen_US
dc.subjectHW-SW Bridgeen_US
dc.subjectsystem on chipen_US
dc.title以心率變異度之頻域分析為基礎所實現的嵌入式瞌睡偵測系統zh_TW
dc.titleEmbedded System Implementation of Drowsiness Detection Based on Frequency Domain Analysis of Heart Rate Variabilityen_US
dc.typeThesis and Dissertationzh_TW
Appears in Collections:電機工程學系所
文件中的檔案:

取得全文請前往華藝線上圖書館

Show simple item record
 
TAIR Related Article
 
Citations:


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.