Abstract—Patients suspected of suffering sleep apnea and hy- popnea syndrome (SAHS) have to undergo sleep studies such as expensive polysomnographies to be diagnosed. Healthcare profes- sionals are constantly looking for ways to improve the ease of di- agnosis and comfort for this kind of patients as well as ...

This local analysis allows the detection of anomalous situations as soon as they are generated. The classifier has been implemented taking into consideration the restricted resources of mobile devices.

Abstract— Patients suspected of suffering Sleep Apnea and. Hypopnea Syndrome (SAHS) have to undergo sleep studies such as expensive polysomnographies to be diagnosed. Healthcare professionals are constantly looking for ways to improve the ease of diagnosis and comfort for this kind of patients as well as.

Jul 1, 2010 · This local analysis allows the detection of anomalous situations as soon as they are generated. The classifier has been implemented taking into consideration the restricted resources of mobile devices.

The aim of this paper is to show a very accurate classifier that is able of identifying the presence of sleep apneas from blood oxygen saturation signal fragments taken from pulsioximetry systems (SpO2 & HRV) implemented on smart phone in real time.

May 31, 2024 · This study proposes a single convolutional neural network architecture that can automatically extract spatial features and detect apnea from both electrocardiogram (ECG) and blood-oxygen saturation (SpO2) signals. Using segments of 10s, the network classified apnea with an accuracy of 94.2% and 96% for ...

Patients suspected of suffering sleep apnea and hypopnea syndrome (SAHS) have to undergo sleep studies such as expensive polysomnographies to be diagnosed. Healthcare professionals are constantly looking for ways to improve the ease of diagnosis and comfort for this kind of patients as well as reducing both the ...

This paper focuses on the real-time monitoring and detection of SAHS based on the arterial oxygen saturation signal measured by pulse oximetry (SpO2). We develop a more comprehensive feature set and a more appropriate annotation criterion, if compared to the existing approaches in the literature.

This paper investigates real-time sleep apnea and hypopnea syndrome detection based on electrocardiograph and saturation of peripheral oxygen signals, individually and in combination and proposes classifier combination to further enhance the classification performance by harnessing the complementary ...

As it can be seen in the table, the proposed model AIPCVwGMM maintains a high ability to detect different apnea types regardless disease severity in the test patients. MSA events are very rare in mild patients which caused low and skewed detection rates for these patients. Also, the final row in Table 6 was left empty ...