A new algorithm for detecting spiking events from ballistocardiographic data recorded with an EMFi sheet achieved an 80% true positive rate and a 19% false positive rate.
An automated algorithm can detect spiking events from EMFi sheet BCG data with 80% sensitivity, aiding in the evaluation of respiratory disturbance during sleep without requiring recording-specific tuning.
In this paper we present a new method for detection of spiking events caused by the increased respiratory resistance (IRR) from ballistocardiographic (BCG) data recorded with EMFi sheet. Spiking is a phenomenon where BCG wave complexes increase in amplitude during IRR. In this study data from six patients with a total of 1503 visually scored spiking events were studied. The algorithm monitors amplitude levels of BCG complexes and detects large relative increases. In this work 10 different variations of the algorithm were compared in order to find the best variation, which can cope with different recordings. The best variation of the algorithm was able to detect spiking events with 80% true positive and 19% false positive rates. The detection is not dependent on absolute waveform amplitudes and therefore does not require any recording-specific tuning prior to application. It is important to recognize spiking events in order to evaluate the severity of respiratory disturbance during sleep.
Alametsä et al. (Tue,) conducted a other in Increased respiratory resistance during sleep (n=6). Algorithm for detection of spiking events vs. Visual scoring was evaluated on True positive and false positive rates for detecting spiking events. A new algorithm for detecting spiking events from ballistocardiographic data recorded with an EMFi sheet achieved an 80% true positive rate and a 19% false positive rate.