추정된 일회심박출량을 이용한 수면 무호흡 검출
Sleep Apnea Detection using Estimated Stroke Volume
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초록
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.
Abstract
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.
참고문헌 (33)
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