• 대한의용생체공학회:의공학회지
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• 제34권2호
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• pp.97-103
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• 2013

This paper proposes a new algorithm for sleep apnea detection based on stroke volume. It is very important to detect sleep apnea since it is a common and serious sleep-disordered breathing (SDB). In the previous studies, methods for sleep apnea detection using heart rate variability, airflow and blood oxygen saturation, tracheal sound have been proposed, but a method using stroke volume has not been studied. The proposed algorithm consists of detection of characteristic points in continuous blood pressure signal, estimation of stroke volume and detection of sleep apnea. To evaluate the performance of algorithm, the MIT-BIH Polysomnographic Database provided by Phsio- Net was used. As a result, the sensitivity of 85.99%, the specificity of 72.69%, and the accuracy of 84.34%, on the average were obtained. The proposed method showed comparable or higher performance compared with previous methods.

• 한국컴퓨터정보학회논문지
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• 제22권11호
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• pp.17-23
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• 2017

In this paper, we implemented a respiration measurement system consisting of piezoelectric sensor, respiration signal processing device, and a viewer on a notebook. We tried an experiment for measuring respiration and detecting sleep apnea syndrome when a subject lay on a bed. We applied the respiration measurement algorithm to sensor data obtained from four subjects. In order to get a good graph shape, data manipulation methods such as moving averages and maximum values were applied. The window size for moving average was chosen as N=70, and the threshold value for each subject was customized. In this case, the proposed system showed 96.0% accuracy. When the maximum value among 90 data was applied instead of moving average, our system achieved 95.1% accuracy. In an experiment for detecting sleep apnea syndrome, the system showed that sleep apnea occurred correctly and calculated the average interval of sleep apnea. While infants or the elderly as well as patients with sleep apnea syndrome are lying down on a bed, our results are also expected to be able to cope with some accidental emergency situation by observing their respiration and detecting sleep apnea.

• 한국인터넷방송통신학회논문지
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• 제23권2호
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• pp.119-129
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• 2023

수면 무호흡증은 고혈압, 뇌졸중, 심근경색, 우울증 및 인지기능 장애 등 다양한 2차 질환을 일으키며 심혈관 및 뇌혈관 질환의 발생 원인이 되기에 수면 무호흡의 조기 발견 및 지속적인 관리가 절실히 필요하다. 본 연구에서는 수면 중 호흡을 모니터링하기 위해 목의 기관 부위에서 호흡에 의한 미세한 진동을 검출할 수 있는 PVDF 필름 진동 센서를 이용하여 정상호흡과 수면 무호흡을 판단하는 웨어러블 디바이스를 개발하였다. 검출된 호흡음 데이터를 기반으로 호흡수, 무호흡 등의 변수들을 추출하였고 잡음 제거 알고리즘을 수립하여 잡음 신호가 있을 시에도 영향을 최소화하는 방법을 적용하였다. 또한 변동 문턱치 알고리즘을 수립하여 불규칙적인 호흡 패턴에서도 분석이 가능함을 확인하였다. 그 결과 분당 호흡수의 정확도는 98.7%이고 무호흡 횟수와 무호흡 지속 시간에 대한 개발기기와 수면다원검사의 결과를 비교한 결과 무호흡 횟수 측정 정확도는 92.6%, 무호흡 지속 시간의 정확도는 94.0%임을 확인하였다. 본 연구의 결과는 일상생활 중 가정에서 간편하고 정확하게 수면 정보를 모니터링하고 치료 경과를 확인할 수 있는 웨어러블 디바이스의 제품화로 이어져 수면장애의 관리에 큰 도움이 될 것이다.

• 한국전자파학회논문지
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• 제28권10호
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• pp.802-809
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• 2017

본 논문에서는 IR-UWB 레이다 신호를 이용하여 무호흡 검출과 호흡수를 측정할 수 있는 방법을 제안한다. 제안한 방법에서는 무호흡 검출과 호흡수 측정을 동시에 지원하기 위해서 레이다 신호의 크기, 도래시간 및 선택된 주파수 대역에서의 전력 정보를 이용한다. 하드웨어 실험을 통해서 제안한 방법을 사용하여 정확한 호흡수 측정이 가능함을 보인다. 또한, 제안한 방법을 사용하여 무호흡과 호흡의 선택비가 최소 50 dB 이상이 됨을 보인다.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2022년도 제66차 하계학술대회논문집 30권2호
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• pp.57-58
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• 2022

Sleep apnea (SA) is a common chronic sleep disorder that disrupts breathing during sleep. Clinically, the standard for diagnosing SA involves nocturnal polysomnography (PSG). However, this requires expert human intervention and considerable time, which limits the availability of SA diagnoses in public health sectors. Therefore, ECG-based methods for SA detection have been proposed to automate the PSG procedure and reduce its discomfort. We propose a preprocessing method to convert the one-dimensional time series of ECG into two-dimensional images using the Gramian Angular Field (GAF) algorithm, extract temporal features, and use a two-dimensional convolutional neural network for classification. The results of this study demonstrated that the proposed method can perform SA detection with specificity, sensitivity, accuracy, and area under the curve (AUC) of 88.89%, 81.50%, 86.11%, and 0.85, respectively. Our experimental results show that SA is successfully classified by extracting preprocessing transforms with temporal features.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1997년도 추계학술대회
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• pp.464-467
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• 1997

In this study, ECG was recorded during sleep patients with obstructive sleep apnea. We detecte(heart rate variability) signal from the ECG wa QRS detection algorithm. And we observed HRV by the power spectrum density using autoregr modeling. The experimental results were analysis sleep stage 1, sleep stage 2, sleep stage 3, sleep s sleep stage REM. In experimental result, the PSD with obstructive sleep apnea patients was distributed low frequency band except sleep step 4. These effect means that the sympathetic nervous system affected the sleep stage 1, 2, REM and the parasympathetic nervous system affected the sleep stage 3, 4 with obstructive sleep apnea patients.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 V
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• pp.2879-2882
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• 2003

Obstructive Sleep Apnea(OSA) is a representative symptom of sleep disorder which is caused by airway obstruction. OSA is usually diagnosed through the laboratory based Polysomnography(PSG) which is uncomfortable and expensive. In this paper, the detection method for OSA events, using ECG, has been developed. The proposed method uses the ECG data sets provided from Physionet. The features for OSA events detection are the average and standard deviation of 1 minute R-R interval, power spectrum of R-R interval and S-pulse amplitude from data sets. These features are applied to the input of Neural Network. To evaluate the method, we used the another ECG data sets. And we achieved sensitivity of 89.66％, specificity of 95.25％. So, we can know that the features proposed in this paper are important to detect OSA.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• 제30권2호
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• pp.150-156
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• 2004

The etiology of the obstructive sleep apnea includes the various factors such as anatomical abnormality in upper airway, craniofacial structure, obesity and personal habit. To establish reasonable treatment plan, multi-department approach is should be emphasized because the treatment modality is depend on the result of analysis for degree & site of obstruction and various behavioral factors. In Sleep Clinic in Keimyung University Medical Center, the standard of care for sleep apnea patient was established according to the Standard of practice committee of Americal Sleep Disorders Association. After one year experience of comprehensive approach for sleep apnea we could achieve following recommendation for the treatment. 1) The multi-department examination and diagnosis could prevent unnessesary treatment because the treatment plan could be established under comprehensive discussion. 2) Determination of the site of obstruction is important for treatment planning. However, no single determinant could be found. We expect multi-department approach can reduce the mistake in detection of obstruction. 3) Further evaluation of treatmet outcome should be succeeded to establish Korean standard of care for sleep apnea treatment.

• 수면정신생리
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• 제3권2호
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• pp.65-76
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• 1996

Natural sleep pattern and its physiology in childhood are much different from those in adulthood. Several aspects of clinical evaluation for sleepiness in childhood are more difficult than in adulthood. These difficulties are due to several factors. First, excessive sleepiness in childhood do not always develop functional impairments. Second, objective test such as MSLT may not be reliable since it is hard to be certain that the child understand instructions. Third, sleepiness in children is often obscured by irritability. paradoxical hyperactivity, or behavioral disturbances. Anseguently, careful clinical evaluation is needed for the sleepy children. Usual causes of sleepiness in children are the disorders that induce insufficient sleep such as sleep apnea syndrome, schedule disorder, underlying medical and psychiatric disorder, and so forth. After excluding such factors, we can diagnose the hypersomnic disorders such as narcolepsy, Kleine-Levin syndrome, and idiopathic central nervous system hypersomnia. Among the variety of those causes of sleepiness, I reviewed the clinical difference of narcolepsy and obstructive sleep apnea syndrome in childhood compared with in adulthood. Recognition of the childhood narcolepsy is difficult because even severely sleepy children often do not develop pathognomic cataplexy and associated REM phenomena until much later. Since childhood narcolepsy give srise to many psychological, academical problem. Practicers should be concerned about these aspects. Childhood obstructive sleep apnea syndrome is different from adult obstructive sleep apnea syndrome too. Several aspects such as pathophysiology. clinical feature, diagnostic criteria, complication, management, and prognosis differ from those in the adult syndrome. An important feature of childhood obstructive sleep apnea syndrome is the variety of severe complications such as behavioral disorders, cognitive impairment, cardiovascular symptoms, developmental delay, and ever death. Fortunately, surgical interventions like adenotosillectomy or UPPP are more effective for Childhood OSA than adult form. CPAP is a "safe, effective, and well-tolerated" treatment modality too. So if early detection and proper management of childhood OSA were done, the severe complication would be prevented or ever cured.

• 한국산업정보학회논문지
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• 제11권3호
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• pp.90-95
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• 2006

수면 무호흡증 환자를 진단하는 수면다원검사는 여러 가지 생체 신호를 함께 측정하므로 피검사자의 행동을 제약하며 비용이 많이 드는 단점이 있다. 본 논문에서는 피검사자의 심전도를 ZigBee 무선통신으로 컴퓨터 시스템에 전달하여 검사하는 방식을 제안하였다. 이 방식은 환자의 자유도를 높였을 뿐 만 아니라 수면 무호흡 검사 장소의 제약성, 시간의 한계를 극복하여 저렴한 비용으로 검사가 가능하다.