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- W2289608815 abstract "We used our computer program enabling detection of sleep apnea using long-time one-channel ECG signal recordings. It allows the calculations of commonly accepted six heart rate variability (HRV) parameters in time domain. We also introduced additional 34 indices which were created as a combination of selected or all basic six indices of HRV. For testing we used 70 sample recordings from the Physionet database containing single ECG signals 7 to 10 hours long. The analysis was performed on samples lasting 10000 seconds. The efficiency of the software was evaluated using the Receiver Operating Characteristic (ROC) method. For basic 6 HRV indices we found that the highest accuracy of discrimination was achieved for standard deviation of successive differences (88.5%). The area under the ROC curve was 0.89. The sensitivity and specifity were 96% and 70%, respectively. For one of the newly proposed indices which was average sum of square of all six base indices the accuracy was at the level of 90%. The area under the ROC curve was 0.85. The sensitivity and specifity were 98% and 70%, respectively." @default.
- W2289608815 created "2016-06-24" @default.
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- W2289608815 date "2015-09-01" @default.
- W2289608815 modified "2023-09-27" @default.
- W2289608815 title "New indices for sleep apnea detection from long-time ECG recordings" @default.
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- W2289608815 doi "https://doi.org/10.1109/cic.2015.7411085" @default.
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