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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 張璞曾(Fok-Ching Chong),林耀仁(Yaw-Jen Lin) | |
| dc.contributor.author | Shyh-Shin Chen | en |
| dc.contributor.author | 陳世欣 | zh_TW |
| dc.date.accessioned | 2021-06-15T05:16:26Z | - |
| dc.date.available | 2015-07-23 | |
| dc.date.copyright | 2010-07-23 | |
| dc.date.issued | 2010 | |
| dc.date.submitted | 2010-07-21 | |
| dc.identifier.citation | [1] J.Vander, H.Sherman, S.Luciano ,” Human Physiology: The Mechanisms of Body Function/8th Edition”text book,McGraw-Hill Education,PP387~396 ,June 2000.
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[22] ETSI, “Digital Video Broadcasting (DVB); Head-end implementation of DVB SimulCrypt,” ETSI TS 103 197 V1.3.1, January 2003 [23] Digital Audio-Visual Council, 'DAVIC 1.2 Specification' 1997 [24] Digital Video Broadcasting Project (DVB) org.'Digital Video Broadcasting (DVB)-Multimedia Home Platform (MHP) Specification 1.2.2' ETSI TS 102 727 V1.1.1, Jan.2010. [25] F.Jon,Sharp Laboratories of America, 'HAVi Technical Overview'April 2000. [26] G.Frank,”The Alan E. Lindsay ECG Tutorial V6.0”, July 2007. [27] 賴凌平 ,”賴氏心電圖”,藝軒圖書出版社 ,PP 7~12,Sep.2005. [28] American Heart Association Inc. European Society of Cardiology “Heart Rate Variability, Standards of measurement, physiological interpretation, and clinical use” European Heart Journal, PP.354-381, Mar.1996. [29] G.Kudaiberdieva, B.Gorenek, B.Timuralp,”Heart rate variability as a predictor of sudden cardiac death”, Anadolu Kardiyol Derg,Suppl 1, PP 68-70, July 2007. [30] O.Rompelman ,Ajrm Coenen, R.I. Kitney ' Measurement of heart-rate variability Part I-Comparative study of heart rate variability analysis methods' Med. & Biol. Eng. & Comput.,August 1976. [31] RD.Berger,S.Akselrod,D.Gordon,”An efficient algorithm for spectral analysis of heart rate variability” , IEEE Transactions on biomedical engineering,Vol. BME-33,NO.9,Sep.1986. [32] W. Charles “Implementing the Radix-4 Decimation in Frequency (DIF) Fast Fourier Transform (FFT) Algorithm Using a TMS320C80 DSP”AP REPORT: SPRA152, January 1998. [33] I.S. Uzun, A. Amira,A.Bouridane”FPGA Implementations of Fast Fourier Transforms for Real-Time Signal and Image Processing”IEE Proc.-Vis. Image Signal Process., Vol. 152, No. 3, June 2005 [34] Steven M. Kay, Stanley L. Marple ,”Spectrum Analysis-A Modern Perspective”IEEE Vol.69,No.11, November 1981 [35] Rod K. Dishmana,U.Yoshio Nakamura, Melissa E. Garcia,Ray W. Thompson, Andrea L. Dunnb, Steven N. Blair,”Heart rate variability, trait anxiety, and perceived stress among physically fit men and women” International Journal of Psychophysiology ,Page 121-133 , August 2000 [36] L. Salahuddin, J.Myeong Gi,K.Desok, L.Seong-Kyeon,W. Kim, W.Jong-Min ”Dependence ofHeart Rate Variability on Stress Factors of Stress Response Inventory”IEEE. July 2007. [37] D. Ramaekers,H.Ector,A.E.Aubert,A.Rubens,F.Vande Werf 'Heart rate variability and heart rate in healthy volunteers' European Heart Journal, Volume 19, Issue 9,Pp.1334-1341,March 1998. [38] Audio Precision, Inc. C.Richard Cabot,'Fundamentals of Modern Audio Measurement' August 1999. [39] Texas Instruments Incorporated”THS7316, 3-Channel HDTV Video Amplifier with 5th-Order Filters and 6-dB Gain”January 2008. [40] Tektronix,”High Definition Analog Component Measurement” Application note, 25W-16653-0, April 2008. [41] H.Stephen ,W.Garrett,A.James,”High-Speed Digital System Design”text book,PP.7~40,Aug.2000. 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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/46574 | - |
| dc.description.abstract | 少子化與高年齡社會的來臨 , 是先進國家所面臨的挑戰 , 其所面對的問題不單是在國家的競爭力 , 在醫療資源方面 , 如何做最有效的運用與管理 ,更是值得探討的問題。
讓高齡者能夠在幸福受尊敬的環境中 , 享有健全的居家健康自主管理是本實驗的主要目的之一 。 工作與生活等因素所導致的壓力 , 是生活在高競爭環境的現代人無法跳脫的 , 如何做有效的管理與釋放 , 是本實驗另一重要研究方向。 本研究針對這些問題提出一個有效率的方案 , 我們提供年長者一個便利的居家健康自主管理系統 , 其中包含壓力自主管理。 目前在健康照護以遠距醫療為重要的趨勢 , 許多研究單位無不盡心思索探討其發展走向 , 然卻因需額外支付檢測費用與需購買昂貴獨立健康管理系統等原因 , 使的遠距醫療並無真正普及。貼身華佗是本研究的思考方向 , 目標讓健康自主管理系統能夠與日常生活做最完美的結合。 數位居家多媒體中心 , 一直以來呈現著資訊電子與消費電子的角力戰 , 雙方在其技術與應用各有優劣勢與主要市場方向 ; 本研究將資訊系統嵌入式電腦與消費性系統數位機上盒 , 利用其技術功能性的優缺點 , 做改進與最佳化 , 並整合到居家健康自主管理系統。 因此 , 這個智慧型多媒體平台也提供附加裝置的幫助。 心率變異是由於自律神經活動所產生的波動現象 , 其可直接反映交感神經與副交感神經的平衡狀態。利用ECG的量測可直接反映HRV所呈現的狀態 , 許多臨床與研究資料都證明HRV的數值是可以用來分析壓力 、 糖尿病與慢性疲勞等檢測 , 其中受測者的性別、年紀與量測時的姿勢、情緒等因素都會影響其準確性。本研究所探討的頻域訊號 , 並計算出其能量頻譜密度 , 做為分析交感神經與副交感神經活動平衡與壓力的相互關係。 本研究利用數位居家多媒體的影音功能 , 提升量測結果 , 因此讓受測者在量測的同時 , 聆聽輕音樂與觀看大自然風景的影片 , 並規範量測姿勢 , 使受測者在輕鬆愉快不受外在環境影響進行量測。 從臨床試驗結果表示 , 根據我們的系統規格操作系統 , 經受測者測試的HRV紀錄顯示 , 它是與壓力有相關 , 這個系統是便利的且每個人都可以能去使用它。 | zh_TW |
| dc.description.abstract | The oncoming trend of decreasing new born children and increasing aging elders were important issues to every country. These may lead to serious problems in national competitiveness and resources for medical care. Therefore, measures must be made to ensure most effective utilization of the resources for medical care.
Another important issue is the high competitive environment of today. We are faced with pressure caused by workload and livelihood burden. Thus, besides wealth, to enjoy a happy life, we hope to be in good health. A useful stress-management system is an imminent. This paper presents an effective solution to these above problems. We provide the elder a friendly home health self-management system. An effective self stress-management system is also included in the package. Today telemedicine is important trend in health care. In spite of this, it is not popular for users have to pay extra for examination expenses and also the need to purchase individual health management machines. Here, we employ the idea of famous physician master, Hua-Tuo. An effective health self-management system must have perfect embedded integration in our daily life. The Digital Home Multimedia Centers have always been the main market direction in the technology and application. The advantages and disadvantages of technical and functional for the Embedded Computer Information System and Consumer Digital set-top box were carefully studied, integrated and optimized into our purposed system. Furthermore, an intelligent multimedia platform is also provided to facilitate add-on devices. Heart rate variability (HRV) is a fluctuation phenomenon produced by nervous activity. It could reflect the state of the equilibrium between the Sympathetic nervous system and the Parasympathetic nervous system directly. Real-time ECG can demonstrate the status of HRV directly. A variety of clinical usage and research materials proved that the value of the subject HRV can reflect the subject’s stress、diabetes and chronic fatigue etc. However, the subject’s sex、age、posture of measurement、emotional and other factors will affect the accuracy of measured HRV. Power spectral density of HRV is used to analyze the interrelationship between the Sympathetic nervous and the Parasympathetic nervous for under balance and stress situation. The use of home multimedia video and music functions may enhance good measurement results. The subject may listens to light music, watch nature scenery movie, and standardize gauging posture. Therefore during the measurement, the subject is in a relaxed happy mood and will not be affected by external environment. Results from clinical trial showed that the system operates according to our system specifications. The recorded HRV of subjects tested did show that it is related to stress. This system is friendly and everyone can be afforded to use it. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T05:16:26Z (GMT). No. of bitstreams: 1 ntu-99-P97945001-1.pdf: 4031038 bytes, checksum: 2c57e858505c2ef77e82041655286a18 (MD5) Previous issue date: 2010 | en |
| dc.description.tableofcontents | 口試委員會審定書………………………………………………… i
誌謝………………………………………………………………… ii 中文摘要…………………………………………………………… iv Abstract…………………………………………………………… v 目錄………………………………………………………………… vi 圖目錄……………………………………………………………… x 表目錄……………………………………………………………… xii 第一章 緒論……………………………………………………… 1 1-1. 心率變異理論分析………………………………………… 1 1-2. 研究動機…………………………………………………… 5 1-3. 文獻探討…………………………………………………… 9 1-4. 論文架構…………………………………………………… 13 第二章 系統介紹……………………………………………………16 2-1. 系統硬體架構……………………………………………… 16 2-1-1. 生理信號擷取 …………………………………………… 20 2-1-2. 資料處理與儲存 ……………………………………… 21 2-1-3. 前端模組信號擷取…………………………………………23 2-1-4. 影像處理與輸出………………………………………… 28 2-2. 系體軟體架構 …………………………………………… 34 第三章 原理探討與方法………………………………………… 37 3-1. ECG原理與分析…………………………………………… 37 3-2. HRV原理與演算法分析…………………………………… 41 3-2-1. 時域方法(Time domain methods)………………… 41 3-2-2. 頻域方法(Frequency domain methods)…………………44 3-2-3. 頻域分析演算…………………………………………… 47 3-3. HRV與壓力關係分析……………………………………… 55 第四章 實驗與結果探討………………………………………… 58 4-1. 系統線路訊號量測………………………………………… 58 4-2. 壓力自主量測管理與分析 ……………………………… 68 第五章 結論與未來展望………………………………………… 73 第六章 參考文獻………………………………………………… 74 | |
| dc.language.iso | zh-TW | |
| dc.subject | 交感神經 | zh_TW |
| dc.subject | 心率變異 | zh_TW |
| dc.subject | 副交感神經 | zh_TW |
| dc.subject | 壓力訊號 | zh_TW |
| dc.subject | 心電圖 | zh_TW |
| dc.subject | 數位機上盒 | zh_TW |
| dc.subject | Stress signals | en |
| dc.subject | HRV(Heart rate variability) | en |
| dc.subject | Sympathetic | en |
| dc.subject | Parasympathetic | en |
| dc.subject | STB(Set-Top-Box) | en |
| dc.subject | ECG(Electrocardiography) | en |
| dc.title | 居家多媒體平台~壓力自主管理 | zh_TW |
| dc.title | A Home Multimedia Platform ~Stress Self-Management | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 98-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.advisor-orcid | ,林耀仁(yjlin1952@gtrial.ctust.edu.tw) | |
| dc.contributor.oralexamcommittee | 余松年,林育德,陸哲駒,陳友倫 | |
| dc.subject.keyword | 壓力訊號,心電圖,心率變異,交感神經,副交感神經,數位機上盒, | zh_TW |
| dc.subject.keyword | Stress signals,ECG(Electrocardiography),HRV(Heart rate variability),Sympathetic,Parasympathetic,STB(Set-Top-Box), | en |
| dc.relation.page | 76 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2010-07-21 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 生醫電子與資訊學研究所 | zh_TW |
| 顯示於系所單位: | 生醫電子與資訊學研究所 | |
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