Key result
The peak-detection method proposed by Sadek et al. achieved the highest average peak-detection rate of 94% and the lowest average false alarm rate of 0.0552 false alarms per second.
Why the study?
Multiple methods have been proposed for ballistocardiogram peak detection to identify individual cardiac cycles, but objective comparisons among them are lacking.
Which ballistocardiogram (BCG) peak detection method provides the best performance in identifying individual cardiac cycles?
Which ballistocardiogram (BCG) peak detection method provides the best performance in identifying individual cardiac cycles?
The Sadek et al. and Brüser et al. methods demonstrated superior performance for ballistocardiogram peak detection, offering high detection rates and low error margins.
Objective BCG peak-detection comparisons establish performance baselines; leaves open optimal method selection for clinical cardiac monitoring.
A number of research groups have proposed methods for ballistocardiogram (BCG) peak detection toward the identification of individual cardiac cycles. However, objective comparisons of these proposed methods are lacking. This paper, therefore, conducts a systematic and objective performance evaluation and comparison of several of these approaches. Five peak-detection methods (three replicated from the literature and two adapted from code provided by the methods' authors) are compared using data from 30 volunteers. A basic cross-correlation approach was also included as a sixth method. Two high-performing methods were identified: the method proposed by Sadek et al. and the method proposed by Brüser et al. The first achieved the highest average peak-detection rate of 94%, the lowest average false alarm rate of 0.0552 false alarms per second, and a relatively small mean absolute error between the real and detected peaks: 0.0175 seconds. The second method achieved the lowest mean absolute error of 0.0088 seconds between the real and detected peaks, an average peak-detection success rate of 89%, and 0.0766 false alarms per second. All metrics are averaged across participants.
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Suliman et al. (2019) studied Healthy volunteers (n=30). Sadek et al. peak detection method vs. Other peak detection methods (Lee, Lydon, Brüser, Alvarado, XCOR) was evaluated on Average peak-detection rate. The peak-detection method proposed by Sadek et al. achieved the highest average peak-detection rate of 94% and the lowest average false alarm rate of 0.0552 false alarms per second.
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