The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Obstructive Sleep Apnea (OSA) is one of the main sleep disorders, but only 10% of the cases are diagnosed. Moreover, there is a lack of tools for long-term monitoring of OSA, since current systems are too bulky and intrusive to be used continuously. In this context, recent studies have shown that it is possible to detect it automatically based on single-lead ECG recordings. This approach can be used...
We tried to improve the sleep assessment method from the accelerations (ACC) and RR interval variations (RRIV) thar were measured with newly developed small and light-weight wearable ECG and ACC measuring devices (M-BIT). We performed the simultaneous measurement of M-BIT and polygraph, and verified the validity of our ACC-based sleep/awake identification method, and studied the relationships among...
We have developed a sleep measuring system which can measure any subject at any pace. This system is consisted with wearable (size: 40×39×8mm, weight: 14g) acceleration and ECG measuring device and data analyzing software which able to output times in bed, sleep duration, NREM sleep proportion, sleep posture distribution and changing times, measures of autonomic system's activity, frequency of respiration...
This work applies time-varying parametric power spectral density analysis to ECG and derived signals in order to discover the frequency components related to obstructive sleep apnoea. Heart rate variability signals were derived from the original ECG signals using R-R wave intervals. The power spectral densities were calculated using a parametric method across the heart rate variability frequency bands...
Detection of obstructive sleep apnea can be performed through heart rate variability analysis, since fluctuations of oxygen saturation in blood cause variations in the heart rate. Such variations in heart rate can be assessed by means of time-frequency analysis implemented with time-frequency distributions belonging to Cohen's class. In this work, dynamic features are extracted from time frequency...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.