… support system using electrocardiograph (ECG) is required. In this paper, we propose an
approach using residual network to detect apnea based on RR intervals (intervals between R-…

… This article introduced a new approach of sleep apnea recognition based on a multiscale …
Wang, “A RR interval based automated apnea detection approach using residual network,” …

… In this study we show that it is possible to detect sleep apnea through RR interval analysis.
The following list … The RR intervals were extracted from ECG signals via automated QRS …

… of the pooling layers, transforming the plain network to a residual network. The final layers
include a … Automatic detection of obstructive sleep apnea using wavelet transform and entropy-…

… uses the RR interval signals and R peak signals derived from the ECG signals as input. Then,
a multi-scale residual network … an SA detection method based on sparse auto-encoder and …

… Over the past decade, automatic detection of OSA from ECG … domain features from the
ECG's RR interval (RRI) and ECG-… , which makes the deep residual network easy to optimize. …

… a novel approach to detect sleep apnea using both HBI and EDR signals. The approach …
The goal of this work is to propose an automated technique for sleep apnea detection using …

… higher performance in detecting sleep apnea. The objective … an automated algorithm for the
detection of sleep apnea using … based feature extraction has been used for the detection of …

… [14] proposed an automated classification of normal and OSA subjects using TFR … RR interval
signal and R-peak signal derived from the ECG signal as input, and use a residual network …

… Combining the RR Intervals (… automatic SLA detection system based on a distinct Restricted
Boltzmann Machine's (RBM) feature-learning method and Fine-tuned Deep Belief Network (…