Relevant bibliographies by topics / Apnea detection / Dissertations / Theses
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Dissertations / Theses on the topic 'Apnea detection'

Author: Grafiati
Published: 4 June 2021
Last updated: 2 February 2022

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1

Karci, Ersin. "Detection Of Post Apnea Sounds And Apnea Periods From Sleep Sounds." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12612964/index.pdf.

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Obstructive Sleep Apnea Syndrome (OSAS) is defined as a sleep related breathing disorder that causes the body to stop breathing for about 10 seconds and mostly ends with a loud sound due to the opening of the airway. OSAS is traditionally diagnosed using polysomnography, which requires a whole night stay at the sleep laboratory of a hospital, with multiple electrodes attached to the patient&#039<br>s body. Snoring is a symptom which may indicate presence of OSAS<br>thus investigation of snoring sounds, which can be recorded in the patient&#039<br>s own sleeping environment, has become popular
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2

Shewinvanakitkul, Prapan. "Automated Detection and Prediction of Sleep Apnea Events." Case Western Reserve University School of Graduate Studies / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=case1486490112558014.

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3

Tian, Tian. "An Ultra-Wide Band Radar Based Noncontact Device for Real-time Apnea Detection." Digital WPI, 2015. https://digitalcommons.wpi.edu/etd-theses/1092.

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"This thesis presents a real-time noncontact system that can monitor an infant's respiration and detect apnea when it occurs. For infants, bedside monitoring of respiratory signals using non-contact sensors is desirable at the hospital and for in-home care. Traditional approach employs acoustic sensors which can hardly detect infant breathing due to low SNR. In this thesis, a novel method is introduced by using a ultra-wideband (UWB) radar that obtains breathing signal from an infant's weak chest vibration. Furthermore, advanced signal processing techniques are proposed to monitor the breathin
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White, Daniel T. "Design of a Non-Contact Home Monitoring System for Audio Detection of Infant Apnea." DigitalCommons@CalPoly, 2015. https://digitalcommons.calpoly.edu/theses/1463.

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Infant apnea is a widespread condition in which infants fail to effectively breathe, and can lead to death. Clinical solutions exist for continuous monitoring of respirations in a hospital setting and requiring constant skin contact. This thesis investigates the construction of a proof of concept device that performs in-home monitoring without skin contact and with commonly available off-the-shelf components. The device constructed used a directional microphone to detect breathing sounds, an omnidirectional microphone to detect ambient noise as a baseline to help isolate the breathing sounds,
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5

Simons, Lara Andrea da Silva. "Automatic sleep apnea detection and sleep classification using the ECG and the SpO2 signals." Master's thesis, FCT - UNL, 2009. http://hdl.handle.net/10362/2649.

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Dissertation for a Masters Degree in Computer and Electronic Engineering<br>The present work describes the aspects to implement a system that can be used as a swift and accessible screening tool in patients whose complaints are compatible with OSAS (Obstructive Sleep Apnea Syndrome). This system only uses two signals, electrocardiogram (ECG) and the saturation of oxygen in arterial blood flow (SPO2). This system would be applied for the ambulatory automatic screening of OSAS, which currently are done in a Hospital environment, with a substantial waiting list. The system also would overcome
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Azarbarzin, Ali. "Snoring sounds analysis: automatic detection, higher order statistics, and its application for sleep apnea diagnosis." IEEE, 2011. http://hdl.handle.net/1993/9593.

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Snoring is a highly prevalent disorder affecting 20-40% of adult population. Snoring is also a major indicative of obstructive sleep apnea (OSA). Despite the magnitude of effort, the acoustical properties of snoring in relation to physiological states are not yet known. This thesis explores statistical properties of snoring sounds and their association with OSA. First, an unsupervised technique was developed to automatically extract the snoring sound segments from the lengthy recordings of respiratory sounds. This technique was tested over 5665 snoring sound segments of 30 participants and
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7

Cavusoglu, Mustafa. "An Efficient And Fast Method Of Snore Detection For Sleep Disorder Investigation." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608236/index.pdf.

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Snores are breath sounds that most people produce during sleep and they are reported to be a risk factor for various sleep disorders, such as obstructive sleep apnea syndrome (OSAS). Diagnosis of sleep disorders relies on the expertise of the clinician that inspects whole night polysomnography recordings. This inspection is time consuming and uncomfortable for the patient. There are surgical and therapeutic treatments. However, evaluation of the success of these methods also relies on subjective criteria and the expertise of the clinician. Thus, there is a strong need for a tool to analyze the
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8

Hastík, Matěj. "Detekce spánkové apnoe." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2015. http://www.nusl.cz/ntk/nusl-221327.

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This master‘s thesis deals with a detailed description of sleep apnea and methods of detection of sleep apnea. The first part of the work is focused on the physiology of sleep, sleep apnea itself, its distribution, symptoms, risk factors and treatment. The next part of the work deals with polysomnographic examination and methods for analysis of polysomnographic data. The last part is devoted to the procedure design for detecting sleep apnea by using only one kind of signal and by using more kinds of signals, implementation of these proposals, their testing on real data, evaluating the detectio
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9

Baldini, Laura. "Analisi delle funzionalità respiratorie." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2013. http://amslaurea.unibo.it/5001/.

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10

Montazeri, Ghahjaverestan Nasim. "Early detection of cardiac arrhythmia based on Bayesian methods from ECG data." Thesis, Rennes 1, 2015. http://www.theses.fr/2015REN1S061/document.

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L'apnée est une complication fréquente chez les nouveaux-nés prématurés. L'un des problèmes les plus fréquents est l'épisode d'apnée bradycardie dont la répétition influence de manière négative le développement de l'enfant. C'est pourquoi les enfants prématurés sont surveillés en continu par un système de monitoring. Depuis la mise en place de ce système, l'espérance de vie et le pronostic de vie des prématurés ont été considérablement améliorés et ainsi la mortalité réduite. En effet, les avancées technologiques en électronique, informatique et télécommunications ont conduit à l'élaboration d
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Macey, Paul Michael. "Apnoea detection." Thesis, University of Canterbury. Electrical and Electronic Engineering, 1998. http://hdl.handle.net/10092/6888.

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This thesis is concerned with the detection of apnoeas in infants from an abdominal breathing signal, where an apnoea is a pause in breathing during sleep. Apnoea detection is performed by analysing breathing signals recorded during sleep studies. An abdominal breathing signal recorded by the BabyLog polysomnographic system is used for this research. A reference set of apnoeas is formed by three human experts identifying apnoeas five seconds and longer within ten overnight recordings of breathing. There was a 10% disagreement on the identification of events. Based on this reference set, the pe
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Vyskočilová, Martina. "Zpracování a klasifikace signálů ve spánkové medicíně." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2013. http://www.nusl.cz/ntk/nusl-220013.

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This work examines sleep apnea syndrome, sleep physiology and self control of respiration during sleep. There is a review of respiration disorders during sleep and methods of monitoring sleep apnea syndrome. In another part the data of monitoration are processed and method of flow, saturation and snoring signal events detection is described, program algorithm is described and results are presented.
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Tessema, Tizita Gedeon. "Detecting Obstructive Sleep Apnea in an Adult Primary Care Population." ScholarWorks, 2019. https://scholarworks.waldenu.edu/dissertations/6867.

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Obstructive sleep apnea (OSA) is a sleep-related disorder that pauses or decreases air flow during sleep as a result of an obstructed upper airway. About 25 million people in the United States are affected by OSA. OSA has low identification and referral rates, especially in primary care facilities as indicated by the lack of patients' sleep histories. Screening tools such as questionnaires ensure an effective detection of OSA. The practice-focused question examined whether implementing the Epworth sleepiness scale (ESS) in an outpatient primary care setting would increase the number of referra
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Corbishley, Phil. "Ultra low power circuits for a miniature apnoea detection device." Thesis, Imperial College London, 2007. http://hdl.handle.net/10044/1/8467.

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15

Gederi, Elnaz. "Video and audio analysis for the detection of obstructive sleep apnoea." Thesis, University of Oxford, 2017. http://ora.ox.ac.uk/objects/uuid:73387396-d1ba-4a22-9e7a-e84e0c951cfc.

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Obstructive sleep apnoea (OSA) is a common sleep disorder characterised by serious sleep fragmentation due to repeated breathing pauses (OSA events) followed by brief awakenings. OSA is under-diagnosed with many consequences that may be life threatening. The standard screening test, polysomnography (PSG), requires an overnight stay in a clinic and the attachment of several on-body sensors which may be uncomfortable for some patients. Large-scale screening for OSA is limited to the availability of equipment and sleep specialists. The manual review of hours of PSG recordings is also cumbersome a
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16

Navarro, Xavier. "Analysis of cerebral and respiratory activity in neonatal intensive care units for the assessment of maturation and infection in the early premature infant." Phd thesis, Université Rennes 1, 2013. http://tel.archives-ouvertes.fr/tel-00979727.

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This Ph.D. dissertation processes and analyzes signals from the neonatal intensive care units (NICUs) for the study of maturity, systemic infection (sepsis) and the influence of immunization in the premature newborn. A special attention is payed to the electroencephalography and the breathing signal. The former is often contaminated by several sources of noise, thus methods based on the signals decomposition and optimal noise cancellation, adapted to the characteristics of the immature EEG, were proposed and evaluated objectively on real and simulated signals. By means of the EEG and delta bur
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17

Bros, Julie. "Prédiction des facteurs psychosociaux de moindre observance et intervention psycho-éducative auprès des patients atteints du Syndrome d’Apnées Obstructives du Sommeil." Thesis, Université Grenoble Alpes (ComUE), 2019. http://www.theses.fr/2019GREAH015.

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Contexte : Le Syndrome d'Apnées Obstructives du Sommeil (SAOS) est maladie chronique dont le traitement de référence est le traitement par Pression Positive Continue (PPC). Cependant, certains patients ont des difficultés à devenir et/ou à rester observants.Objectif: Identifier précisément ces difficultés afin de prédire et de prévenir les risques de moindre observance au traitement par PPC.Méthodes : Une première étude observationnelle et longitudinale a été menée auprès de 204 patients afin d’établir des profils d’utilisation et d’identifier les facteurs de moindre observance. Au cours de tr
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18

Pinho, André Miguel da Silva. "Classification Models for Sleep Apnea Detection." Master's thesis, 2019. http://hdl.handle.net/10400.6/9998.

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A dissertação incide na selecção de características, importância das mesmas num modelo de classificação e diferentes tipos de classificação para uma melhor detecção de apneia de sono, recorrendo apenas a um electrocardiograma (ECG) e comparando a precisão dos diferentes modelos. Recorrendo ao uso da base de dados Physionet Apnea-ECG, um filtro Savitsky Golay (sgolay) foi aplicado aos registos para limpar o sinal e depois obter o complexo QRS de forma a obter o Heart Rate Variability (HRV) e o ECG-Derived Respi¬ration (EDR). As características extraídas destes dois métodos foram usadas para tre
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Chang, Wan-hua, and 張文華. "Obstructive Sleep Apnea Syndrome Detection Using Snoring Characteristics." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/87428861096276842419.

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碩士<br>逢甲大學<br>通訊工程所<br>95<br>Based on the investigation of Population Health Sciences & Biostatistics and Medical Informatics Dept. Univ. of Wisconsin, there are about 9% autumnal males and 4% autumnal females affected by SAS(Sleep Apnea Syndrome). In Japan’s investigation, there are about 1% of total populations affected by SAS. The case in Taiwan, it’s almost 0.4 million people. Because, the condition of SAS usually happen in sleep, the patients hard to aware. Hence, sometimes SAS be noticed by patients’ family or doctors. In the common case, when doctor diagnosing the “sleep disturbance” al
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Chen, Hsuan-Chun, and 陳玄峻. "Sleep Apnea Syndrome Detection Basedon Multiple Physiological Signals." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/s2spga.

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碩士<br>國立臺中科技大學<br>資訊管理系碩士班<br>104<br>The pressures of modern working life have caused deterioration in the sleep quality of people. Among sleep disorders, sleep apnea affects our everyday life the most. It not only disturbs physiological regulatory functions, but also often leads to poor focus and lack of efficiency at work. It may even lead to drowsiness during the working day, resulting in irreversible tragedy caused by inattention. This study focused mainly on the early detection of sleep apnea and assisting patients in early prevention, to avoid worsening of their condition. Polysomnogram
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Afonso, Valtino X. "Quantitative measures of respiratory sinus arrhythmia for apnea detection." 1993. http://catalog.hathitrust.org/api/volumes/oclc/32492998.html.

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Thesis (M.S.)--University of Wisconsin--Madison, 1993.<br>Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 14-15).
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Chen, Song-Lin, and 陳嵩霖. "Detection of Obstructive Sleep Apnea Using Nasal Airflow Signal." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/7v73nv.

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碩士<br>國立臺北科技大學<br>電機工程系研究所<br>102<br>Nowadays many elder people suffer from sleep disorders, especially the Sleep Apnea Syndrome (SAS). The SAS would adversely affect their cardiovascular systems and their mind. Since 90% of SAS is Obstructive Sleep Apnea (OSA), the detection and treatment of OSA has drawn the interest of medical and academic communities. The professional diagnosis of sleep disorders is to use Polysomnography (PSG) which involves overnight recordings of several physiological signals in sleep laboratories. These recorded signals are then analyzed by the sleep specialist for fin
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Shih, Ping-Ta, and 史秉達. "A Sleep Apnea Detection System Based on EEG Frequency Variation." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/74019267061966734909.

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碩士<br>輔仁大學<br>資訊工程學系<br>97<br>Obstructive sleep apnea syndrome is the most common respiratory disorder for human being. Many novel diagnosis and treatment methods are proposed continuously. Electroencephalogram analysis also becomes one of most important item for the diagnosis of obstructive sleep apnea syndrome. This thesis proposes a sleep apnea detection system based on the variation of electroencephalogram frequency. The system uses a band-pass filter to filtering out the components of very low and higher frequency from electroencephalogram. The system also uses the baseline correctio
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Liu, Iou-Shen, and 劉祐伸. "Detection of Sleep Apnea and Hypopnea Syndrome Using Electroencephalography Signal." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/q64c3k.

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碩士<br>國立臺北科技大學<br>電機工程系<br>106<br>Clinical research has shown that Sleep Apnea Syndrome (SAS) is a significant risk factor for many diseases. If it is not detected early and treated carefully thereafter, it will obviously affect daily life and cause cardiovascular disease. At present, there are approximately 85 % of SAS patients are of Obstructive Sleep Apnea (OSA). People who are suspected having sleep apnea must take Polysomnography (PSG) experiments in the sleep center at night. The sleep technologist and specialist will evaluate the Apnea and Hypopnea Index (AHI) for testing whether they h
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Montazeripouragha, Amanallah. "Acoustical analysis of respiratory sounds for detection of obstructive sleep apnea." 2012. http://hdl.handle.net/1993/5194.

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Obstructive Sleep Apnea (OSA) is a common respiratory disorder during sleep. Apnea is cessation of airflow to the lungs, which lasts for at least 10 seconds accompanied by more than 4% drop of the blood's Oxygen saturation. Polysomnography during the entire night is the Gold Standard diagnostic method of OSA. It's high cost and inconvenience for patients persuaded researchers to seek alternative OSA detection methods. This thesis proposes a technique for assessment of OSA during wakefulness. We recorded tracheal breath sounds of 17 non-apneic individuals and 35 people with various degrees
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Lin, Yin-Yan, and 林音延. "A Sleep Apnea Detection Algorithm Using Thoracic and Abdominal Movement Signals." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/29761072080337454988.

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碩士<br>國立清華大學<br>電機工程學系<br>103<br>Sleep apnea syndrome (SAS) is a prevalent sleep disorder well-known nowadays. People with SAS cease breathing intermittently in sleeping and an episode without breathing is called a sleep apnea event. SAS often deteriorates life quality by frequent nocturnal awakenings, morning headache, excessive daytime sleepiness, and attention deficiency. Unfortunately, the suffering people are usually unconscious of it and diagnosis nowadays relies on expensive and labor-intensive Polysomnography (PSG). This thesis proposed a sleep apnea event detection algorithm which det
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han, Wang-hsiao, and 王筱涵. "A pulse oximetry based method for detection of Obstructive Sleep Apnea." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/72404572898563574944.

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碩士<br>國立中山大學<br>機械與機電工程學系研究所<br>94<br>SAS has became an increasingly important public-health problem since 1970. It can adversely affect neurocognitive, cardiovascular, respiratory diseases and can also cause behavior disorder. Moreover, up to 90% of these cases are obstructive sleep apnea (OSA). Presently, Polysomnography is considered as the gold standard for diagnosing sleep apnea syndrome (SAS). However, Polysomnography-based sleep studies are expensive and time-consuming because they require overnight evaluation in sleep laboratories with dedicated systems and attending personnel. In t
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Yang, Chung-Chi, and 楊仲棋. "The Primitive Study Of Apnea Detection Based On A Wearable SpO2 Monitoring." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/su9m5s.

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碩士<br>元智大學<br>資訊管理學系<br>106<br>Obstructive sleep apnea (OSA) is most frequent sleep disordered breathing ,which is related to more cardiovascular risk and all cause mortality. Currently, apnea-hypopnea index (AHI) in-laboratory polysomnography (PSG) is the gold diagnostic standard. AHI is the sum of apneas plus hypopneas per hour of sleep. However, PSG have limited in time-consuming,costly procedure, well-trained technicians, manual scoring of recordings which is lack of convenient and economical. A real-time health monitoring system (referred to as SpO2 & Sleep Guard) based on a pulse oximetr
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Lin, Shang-Yi, and 林尚誼. "Detection of Sleep Apnea and Hypopnea Syndrome Using Arterial Oxygen Saturation Signal." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/v3ux6p.

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碩士<br>國立臺北科技大學<br>電機工程研究所<br>103<br>Sleep Apnea and Hypopnea Syndrome (SAHS) is a common sleep disorder characterized by repetitive cessation of breathing during sleep time. Currently Polysomnography (PSG) is considered as the standard means for SAHS diagnosis. However, PSG requires SAHS patients to spend one night in a sleep laboratory with professional technicians and doctors. The time-consuming and labor-intensive processing can be quite exhausting. An efficient and fast evaluation of SAHS based on arterial oxygen saturation signal is proposed in this thesis for the purpose of releasing the
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WANG, NENG-HSUAN, and 王能軒. "Detection of Sleep Apnea using Deep Learning Algorithm based on Electroencephalogram Signal." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/5nc383.

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碩士<br>輔仁大學<br>資訊工程學系碩士班<br>107<br>Sleep apnea is one type of sleep disorders. Among them, obstructive sleep apnea is the most common one. Clinically, for diagnosing obstructive sleep apnea (OSA) it usually relies on a variety of physiological signals, such as Electroencephalography (EEG), Electrocardiography and Electrooculography, for the Polysomnographic technician to perform evaluations for the diagnoses of sleep apnea. Therefore, a system for detecting sleep apnea based on EEG signal is proposed in this thesis. The system consists of two modules, a signal preprocessor and a respiratory arr
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Zheng, Yu-Xuan, and 鄭宇軒. "Sleep Apnea Detection Algorithm using EEG and Oximetry based on Ensemble Learning Model." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/66291000965483738888.

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碩士<br>國立中興大學<br>資訊科學與工程學系<br>105<br>The gold standard for diagnosis of sleep apnea is a formal sleep study established by the polysomnography(PSG). However the high cost and the complex steps of PSG makes a diagnosis of sleep apnea become evenmore difficult. Not to mention the shortage of devices and medical human resources. In this thesis, we propose a sleep apnea detection algorithm based on ensemble machine learning model. By using only Electroencephalography(EEG) and Oximetry, we can significantly reduce the difficulty of diagnosis and the effort of medical persons. The experimental res
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Kang, Kun-Tai, and 康焜泰. "Detection for pediatric obstructive sleep apnea syndrome: Role of objective and subjective measures." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/53463910845935537693.

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碩士<br>國立臺灣大學<br>流行病學與預防醫學研究所<br>102<br>Background: Obstructive sleep apnea syndrome (OSAS) is an upper airway disorder. Over-night polysomnography is the “gold standard” for the diagnosis of pediatric OSAS. Information from objective and subjective measures for children with OSAS helps clinicians in decision making. Purpose: To assess diagnostic abilities of objective measures, subjective measures, and combined objective and subjective measures in detecting pediatric obstructive sleep apnea syndrome, and to compare performance difference and clinical utilities between objective measures, subje
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Tee, Jarwin-Jim Ang, and 鄭嘉輝. "Time-Domain Heart Rate Variability Analysis as a Tool for Sleep Apnea Detection." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/04701869442905345489.

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碩士<br>中原大學<br>生物醫學工程研究所<br>101<br>Obstructive Sleep Apnea (OSA) is a syndrome in which there is a repeated event of a partial or complete obstruction of the upper airway during sleep, resulting in intermittent hypoxia and transient repetitive arousals from sleep. The characteristic heart rate pattern, known as the cyclic variation of heart rate (CVHR), that is known to accompany OSA episodes had been demonstrated in earlier studies to be an effective tool in the detection of OSA due to the high correlation between the CVHR index (CVHR per hour) and the apnea-hypopnea index. Moreover, Time- do
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MA, YU-ZHI, and 馬鈺智. "Application of automatic detection and prediction of sleep apnea events based on deep learning." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/235b3q.

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碩士<br>國立中正大學<br>電機工程研究所<br>107<br>In this study, we proposed the detection and estimation of sleep apnea events based on deep learning. By replacing breathing air flow, ribcage and abdomen movements and other signals with ECG, the study of non-invasive signal detection events can be achieved to reduce the discomfort of patients being measured. In addition, this study uses the PyQt framework to construct corresponding applications so that the trained model can be truly applied in daily life. This study can be divided into five parts, the first part of the introduction of sleep apnea classifica
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Chia-WeiHu and 胡家瑋. "Development of a Blood Oxygen Saturation and Cost Sensitive based Sleep Apnea Events Detection Algorithm." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/hjgz25.

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碩士<br>國立成功大學<br>電機工程學系碩博士班<br>101<br>This thesis presents a sleep apnea detection algorithm based on blood oxygen saturation signal and cost-sensitive learning. The proposed algorithm consists of a feature generation process from oxygen saturation signal, a feature selection process based on correlation-based feature selection, a MetaCost learning and a Bagging classification. The MetaCost learning is utilized because the sleep apnea events are imbalanced data sets in nocturnal sleep data sets. Using MetaCost learning can prevent low-sensitivity results in classification. Bagging is a machine
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Tzu-PingKao and 高子平. "Development of Obstructive Sleep Apnea Event Detection Algorithms Based on Heart Rate Variability and ECG Morphology Features." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/w6r4b4.

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碩士<br>國立成功大學<br>電機工程學系<br>104<br>Sleep medicine has become a salient issue in health and medical industry in the past decade. This thesis proposes two electroencephalography (ECG) signal analysis algorithms for obstructive sleep apnea (OSA) detection. The first algorithm is an ECG feature-based AdaBoost Bootstrap k-dimension tree k-nearest neighbor algorithm for OSA events recognition. The proposed method processes single-lead ECG recordings to generate heart rate variability, ECG-derived respiratory signals, and cardiopulmonary coupling features for detecting the occurrence of sleep apnea, an
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Lin, Yu-Zhe, and 林裕哲. "Detection and Prediction of Obstructive Sleep Apnea Based on Traditional Machine Learning and Recent Deep Learning Architectures." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/f6kfmz.

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碩士<br>國立中正大學<br>電機工程研究所<br>106<br>In this thesis, we proposed the identification and prediction methods of obstructive sleep apnea (OSA), using traditional machine learning and recent deep learning approaches. The human’s physiological signal Electrocardiogram (ECG) was used to identify and predict the occurrence of OSA. The differences of using different architectures were compared. This study is composed of three parts, the first part is the traditional machine learning (ML) identification. The architecture can be divided into signal processing, feature extraction, feature normalization and
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Chang, Hung-Chi, and 張紘齊. "A Neural Network System for Detection of Sleep Apnea Syndrome Through Tri-axial Accelerometer and Oxygen Saturation." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/r286ds.

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碩士<br>國立清華大學<br>電機工程學系<br>107<br>Sleep Apnea-Hypopnea Syndrome (SAHS) is a respiratory chronic disease that harms body health and worsens sleep quality of patients. The disease causes complete or partial cessation of breathing while sleeping, which are known as Apnea and Hypopnea event. On clinic, it abrupt awakenings accompanied by choking which cause fluctuation of blood pressure and heart rate. Furthermore, SAHS leads to severe disease such as hypertension and cardiovascular failure. Polysomnography (PSG) is the gold standard for diagnosing SAHS. However, PSG is limited environment, uncomfo
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39

Jia-XuDai and 戴嘉旭. "A home prescreening system based on sleep questionnaires and smartwatches with physiological signal measurement for sleep apnea detection." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/aa6y38.

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碩士<br>國立成功大學<br>電機工程學系<br>107<br>This thesis aims to develop a home prescreening system based on a sleep questionnaire system and physiological signals of smartwatches for sleep apnea detection. The sleep questionnaire system is implemented by an application program (APP) running in portable devices, such as smartphones or pads. The APP contains five sleep-related questionnaires used for clinical evaluation, while the smartwatch contains a photoplethysmography (PPG) sensor, a blood oxygen saturation (SpO2) sensor and physiological signal analysis algorithms. Two types of home prescreening syst
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Fan, Shu-Han, and 范書涵. "Algorithm Implementation of the Real-time Detection of Arrhythmia and Obstruction Sleep Apnea for the Cardiac Monitoring System." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/23768632053344010891.

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41

Yadollahi, Azadeh. "Respiratory sound analysis for flow estimation during wakefulness and sleep, and its applications for sleep apnea detection and monitoring." 2011. http://hdl.handle.net/1993/4590.

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Tracheal respiratory sounds analysis has been investigated as a non-invasive method to estimate respiratory flow and upper airway obstruction. However, the flow-sound relationship is highly variable among subjects which makes it challenging to estimate flow in general applications. Therefore, a robust model for acoustical flow estimation in a large group of individuals did not exist before. On the other hand, a major application of acoustical flow estimation is to detect flow limitations in patients with obstructive sleep apnea (OSA) during sleep. However, previously the flow--sound relationsh
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Yi-WenWang and 王意雯. "Development of an AI-based Sleep Apnea Detection Algorithm based on a Time-Frequency Spectrogram of an ECG Signal." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/kf5apn.

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碩士<br>國立成功大學<br>生物醫學工程學系<br>106<br>This thesis proposes a sleep apnea detection algorithm based on time-frequency transformation spectrogram of ECG signal combined with artificial intelligence algorithm. The methods proposed in this thesis mainly include signal pre-processing, ECG time-frequency transformation, and a bag of feature model-based feature transformation, AI-based classification, cross-validation procedures, etc. In the signal pre-processing, this thesis will perform zero-mean conversion on the electrocardiogram; then in the ECG time-frequency transformation, this thesis generates
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I-JenWen and 溫苡任. "Development of a Sleep Apnea Detection Algorithm based on the Features of Blood Oxygen Saturation and Time-frequency Analysis of Electrocardiography." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/75f3b5.

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han, la tzu, and 藍子涵. "ECG Based Obstructive Sleep Apnoea Detection Algorithm for Homecare." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/57695033046612872676.

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碩士<br>亞洲大學<br>電腦與通訊學系碩士班<br>95<br>Sleep disorder is one of the major diseases in modern society. The way to diagnose sleep disorder needs patients’ biomedical signals during sleep, and there are three levels according to the complexities of sleep recording measurement. The highest class, Level I, usually was set up in the hospital or professional lab; Level II measures the same signal patterns but at patients’ home. Level II are more approaching the patients real sleep situation but without the immediate monitoring by the expert. This project is going to set up Homecare based sleep monitoring
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Chen, Yu-Chou, and 陳禹州. "Flow Rate Based Detection Method for Apneas And Hypopneas." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/s222np.

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碩士<br>國立中山大學<br>機械與機電工程學系研究所<br>95<br>SAS has become an increasingly important public-health problem in recent years. It can adversely affect neurocognitive, cardiovascular, respiratory diseases and can also cause behavior disorder. Since up to 90% of these cases are obstructive sleep apnea (OSA), therefore, the study of how to diagnose, detect and treat OSA is becoming a significant issue, academically and medically. Polysomnography (PSG) can monitor the OSA with relatively fewer invasive techniques. However, PSG-based sleep studies are expansive and time-consuming because they require overn
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Huang, Ren-tsung, and 黃仁聰. "Detecting Apnea and Hypopnea Events by using Peaks of Flow Rate Signals." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/y9wqd8.

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碩士<br>國立中山大學<br>機械與機電工程學系研究所<br>96<br>This study uses flow rate and blood oxygen saturation signals to detect apnea and hypopnea events. The detection process consist two phases, by using the peaks of flow rate signals to determine respiratory cycles, the first phase uses seven flow rate feature to distinguish normal and abnormal respiratory events. To reduce the false detection rate, by appending two additional blood oxygen saturation variables into the feature set, the second phase tries to filter out some falsely detected events made in the first phase. Experimental results show that the pr
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Wang, Yuan-Hung, and 王元宏. "Electrocardiogram Signal for the Detection of Obstructive Sleep Apnoea Via Artificial Neural Networks." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/81885535557197225449.

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碩士<br>國立中山大學<br>機械與機電工程學系研究所<br>92<br>SAS has become an increasingly important public-health problem in recent years. It can adversely affect neurocognitive, cardiovascular, respiratory diseases and can also cause behavior disorder. Moreover, up to 90% of these cases are obstructive sleep apnea (OSA). Therefore, the study of how to diagnose, detect and treat OSA is becoming a significant issue, both academically and medically. Polysomnography can monitor the OSA with relatively fewer invasive techniques. However, polysomnography-based sleep studies are expensive and time-consuming because th
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48

(10724028), Jason David Ummel. "NONINVASIVE MEASUREMENT OF HEARTRATE, RESPIRATORY RATE, AND BLOOD OXYGENATION THROUGH WEARABLE DEVICES." Thesis, 2021.

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<p>The last two decades have shown a boom in the field of wearable sensing technology. Particularly in the consumer industry, growing trends towards personalized health have pushed new devices to report many vital signs, with a demand for high accuracy and reliability. The most common technique used to gather these vitals is photoplethysmography or PPG. PPG devices are ideal for wearable applications as they are simple, power-efficient, and can be implemented on almost any area of the body. Traditionally PPGs were utilized for capturing just heart rate, however, recent advancements in hardware
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