METHOD, MACHINE-LEARNING MODEL, DETECTING DEVICE, HOME SLEEP APNEA TEST DEVICE, COMPUTER PROGRAM PRODUCT, ANE COMPUTER-READABLE STORAGE MEDIUM

There is provided a method for detecting sleep disordered breathing (SDB-) events. The method comprises receiving an arousal signal representative of an occurrence of an autonomic arousal; receiving an SDB-signal representative of an occurrence of an SDB-event; and generating a confirmation signal representing confirming that the SDB-signal is representative of the occurrence of the SDB-event based on the arousal signal. Further there is provided a detecting device for detecting SDB-events. The detecting device comprises a sensor system; and a processing unit connected to the sensor system. The sensor system is configured to generate an arousal signal and is configured to generate an SDB-signal. The arousal signal is representative of an occurrence of an autonomic arousal. The SDB-signal is representative of an occurrence of an SDB-event. The processing unit is configured to perform the method for detecting sleep disordered breathing events.