A Body Area Network-Based Detection of Sleep Apnea
نویسندگان
چکیده
Presented in this paper are the analysis and the results of our body area network (BAN) for the detection and classification of obstructive sleep apnea. Our algorithm is based on a low-order Daubechies D4 and D6 hybrid filter. Feature extractions are taken from the QT intervals of the Electrocardiography (ECG) waveform. These features include a QT-ECG-derived respiratory rate (QT-EDR) and the instantaneous heart rate. A determination of the existence of sleep apnea is based on the variability of these features.
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