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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 洪一平(Yi-Ping Hung) | |
dc.contributor.author | Meng-Chieh Yu | en |
dc.contributor.author | 余孟杰 | zh_TW |
dc.date.accessioned | 2021-06-16T23:54:52Z | - |
dc.date.available | 2012-08-10 | |
dc.date.copyright | 2012-08-10 | |
dc.date.issued | 2012 | |
dc.date.submitted | 2012-07-19 | |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/65628 | - |
dc.description.abstract | 呼吸對於人類來說是很重要的一個生理行為。研究指出,合適且有效率地呼吸方式,可讓人們的身心更為健康。本研究著重於呼吸量測技術的研發及多媒體回饋技術,開發一系列的呼吸行為改善多媒體輔助系統,並透過實驗測試這些呼吸多媒體輔助系統對於呼吸行為改善之有效性,找出合適的多媒體回饋模式。
於呼吸感測的部分,我們透過感應性呼吸體積計(Respiratory Inductance Plethysmography, RIP)的感測方式,開發一套具有呼吸體積估測及呼吸情況分析之感測系統。其中的呼吸情況分析包含呼吸狀態(如呼吸頻率、呼吸深度)及呼吸模式(包含胸式呼吸、腹式呼吸)。此外,本研究提出一種以電腦視覺為基礎之呼吸感測技術,透過深度影像資訊偵測使用者胸、腹腔之幾何圖形呼吸變化,感測使用者的呼吸體積。此技術的優勢在於可以局部感測呼吸體積,如左肺、右肺、腹部,並已應用於肺部疾病病友之肺功能評估及測試。透過與肺活量計的通氣量實驗,實驗結果顯示於坐著情況下,該方法與肺活量計所量測的呼吸體積的一致性極高(r=0.966, p<0.01)。 於呼吸生理回饋的部分,我們提出六個多媒體回饋系統的主要功能,包含:反映、引導、評估、紀錄、分析、瀏覽。套用以上功能,並開發三套多媒體輔助呼吸學習系統來輔助使用者進行呼吸練習,包含一套國畫呼吸多媒體互動系統、一套星空多媒體呼吸練習系統、以及一套呼吸調控呼吸展示系統-呼吸毛公鼎。 於呼吸行為改善的部分,本研究整合呼吸感測技術及多媒體回饋技術,根據不同應用情境,開發四套多媒體回饋呼吸行為改善系統,包含一套腹式呼吸練習系統、一套靜坐時的呼吸調控系統、一套慢步經行時的呼吸調控及步伐輔助學習系統、及一套睡眠呼吸偵測及警示系統。此外,並針對上述系統進行使用性測試,用以驗證系統的呼吸偵測準確度、多媒體回饋模式有效性、以及呼吸習慣改善之效果,最後並進行問題探討及建議。 本研究專注於各式呼吸情況感測技術,用以即時記錄及分析使用者的呼吸情況,並提出多媒體回饋機制及整合感測技術開發出不同的呼吸習慣改善之系統,進而改善使用者的呼吸模式,達成預防醫學的終極目標。 | zh_TW |
dc.description.abstract | Breathing is a natural and important physiological behavior for human beings. Research shows that appropriate and efficient breathing behavior can make people healthier both in body and body. In this study, the main research issues include the respiratory measurement and respiratory biofeedback. Combining the topic of respiratory measurement and respiratory biofeedback, four breathing behavior change systems were developed. Furthermore, experiments were carried out to evaluate the effectiveness of these systems, respectively.
For respiratory measurement, the respiratory inductance plethysmography (RIP) is used to measure user’s respiration status. In this system, a length-to-volume calibration procedure was proposed to estimate the respiratory volume from the movements of the body circumference. Then, the respiratory volume and respiratory conditions could be estimated. The respiratory patterns include the respiratory status (such as respiratory rate and respiratory depth) and respiratory methods (such as chest breathing and abdominal breathing). In addition, a computer vision-based respiratory measurement was developed to measure the morphological changes of chest wall region in real-time using a commercial depth camera. This measurement technique can measure user’s respiratory volume without any contact of his body, and the regional respiratory volumes could be measured, i.e. the respiratory volume of left lung, right lung, and abdomen. This system has been used in National Taiwan University Hospital for evaluating the lung functions of the patients with thoracotomy. Moreover, the system was evaluated and compared with a standard reference device, spirometer. The results show strong agreement in respiratory volume measurement in sitting position [correlation coefficient: r=0.966, p<0.01]. Furthermore, the OEP system was used as the reference measurement to measure the thoracic/abdominal volume of the user in the experiment. For respiratory biofeedback, six functions of respiratory biofeedback are proposed, including the functions of reflection, guidance, evaluation, recording, analysis, and browsing. Besides, three respiratory biofeedback systems were developed to help users breathe well, including a skylight feedback system, a Chinese painting feedback system, and an interactive Mao-Kung Ting respiratory training system. Integrating the techniques of respiratory measurement and the principles of respiratory biofeedback, four respiratory biofeedback systems were developed, including an abdominal breath learning system, a breath-aware sitting meditation system, a Breathwalk-aware walking meditation system, and a sleep monitoring system using depth camera. In each system, experiments were carried out to evaluate the effectiveness of these systems, respectively. To conclude, this study focuses on the research issues of respiratory measurement and respiratory biofeedback, and develops a series of breathing behavior change systems. The goal of this study is to improve user’s breathing behaviors and toward the goal of preventive medicine. | en |
dc.description.provenance | Made available in DSpace on 2021-06-16T23:54:52Z (GMT). No. of bitstreams: 1 ntu-101-D95944008-1.pdf: 5279678 bytes, checksum: 867564c21448091223ef5a0f1186ad75 (MD5) Previous issue date: 2012 | en |
dc.description.tableofcontents | TABLE OF CONTENTS ............................................ ..................................................... VII
TABLE OF FIGURES ......................................................................................................... X CHAPTER 1 INTRODUCTION ......................................................................................... 1 1.1 Background and Motivation ..................................................................................... 1 1.2 Dissertation Overview .............................................................................................. 2 1.3 Contributions ............................................................................................................ 3 CHAPTER 2 LITERATURE REVIEW ............................................................................. 5 2.1 Respiratory Measurement ........................................................................................ 5 2.1.1 Contact Respiratory Measurement ....................................................................... 5 2.1.2 Noncontact Respiratory Measurement ................................................................. 9 2.2 Respiratory Biofeedback ........................................................................................ 12 CHAPTER 3 RESPIRATORY MEASUREMENT ......................................................... 17 3.1 Respiratory Inductance Plethysmography (RIP) .................................................... 17 3.1.1 System Framework............................................................................................. 17 3.1.2 Length-Volume Calibration of RIP .................................................................... 18 3.1.3 Experiment ......................................................................................................... 27 3.2 Computer Vision-based Measurement Using Depth Camera ................................ 34 3.2.1 System Framework............................................................................................. 34 3.2.2 Signal Processing ............................................................................................... 35 3.2.3 Experiments ....................................................................................................... 38 3.2.4 Discussion .......................................................................................................... 42 CHAPTER 4 RESPIRATORY BIOFEEDBACK ........................................................... 44 4.1 Six Functions of Respiratory Biofeedback ............................................................ 44 4.1.1 The Function of Reflection ................................................................................ 44 4.1.2 The Function of Guidance .................................................................................. 47 4.1.3 The Function of Evaluation ................................................................................ 48 4.1.4 The Functions of Recording, Analysis, and Browsing ....................................... 49 4.2 Examples of Implementation ................................................................................. 49 4.2.1 Chinese Painting and Airflow System ............................................................... 50 4.2.2 Skylight System ................................................................................................. 52 4.2.3 Interactive Mao-Kung Ting System ................................................................... 54 CHAPTER 5 APPLICATIONS ......................................................................................... 57 5.1 Abdominal Breath Learning ................................................................................... 57 5.1.1 Introduction ........................................................................................................ 57 5.1.2 System Framework............................................................................................. 58 5.1.3 Experiment ......................................................................................................... 62 5.1.4 Discussion .......................................................................................................... 66 5.2 Breathing for Sitting Meditation ............................................................................ 67 5.2.1 Introduction ........................................................................................................ 67 5.2.2 System Framework............................................................................................. 68 5.2.3 Experiment ......................................................................................................... 71 5.2.4 Discussion .......................................................................................................... 74 5.3 Breathing for Walking Meditation ......................................................................... 76 5.3.1 Introduction ........................................................................................................ 76 5.3.2 System Framework............................................................................................. 77 5.3.3 Experiments ....................................................................................................... 84 5.3.4 Discussions ......................................................................................................... 90 5.4 Respiratory Monitoring while Sleeping ................................................................. 91 5.4.1 Introduction ........................................................................................................ 91 5.4.2 System Framework............................................................................................. 92 5.4.3 Experiments ..................................................................................................... 102 5.4.4 Discussions ....................................................................................................... 107 CHAPTER 6 CONCLUSION .......................................................................................... 109 6.1 Review of this Study ............................................................................................ 109 6.2 Summary of the Dissertation ................................................................................ 113 6.3 Future Directions ................................................................................................. 115 LIST OF REFERENCES ................................................................................................... 117 | |
dc.language.iso | en | |
dc.title | 整合生理回饋及呼吸偵測技術於呼吸行為改善之研究 | zh_TW |
dc.title | Research on Integrating Respiratory Measurement and Biofeedback for Breathing Behavior Change | en |
dc.type | Thesis | |
dc.date.schoolyear | 100-2 | |
dc.description.degree | 博士 | |
dc.contributor.oralexamcommittee | 李明穗(Ming-Sui Lee),傅立成(Li-Chen Fu),陳永昇(Yong-Sheng Chen),陳晉興(Jin-Shing Chen),王昱海(Yuh-Hai Wang) | |
dc.subject.keyword | 呼吸感測,生理回饋,呼吸行為改善, | zh_TW |
dc.subject.keyword | Respiratory Measurement,Biofeedback,Breathing Behavior Change, | en |
dc.relation.page | 129 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2012-07-19 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 資訊網路與多媒體研究所 | zh_TW |
顯示於系所單位: | 資訊網路與多媒體研究所 |
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