Key result
ECG-free seismocardiography algorithm achieves ~96% sensitivity for heartbeat detection in valvular heart disease.
Why the study?
SCG-based long-term monitoring would be less obtrusive and easier without simultaneous ECG, but few studies have addressed ECG-free heartbeat detection and have used complex approaches.
Does an ECG-free template matching algorithm accurately detect heartbeats in SCG signals in patients with valvular heart disease?
Observational (n=77)
Yes
Does an ECG-free template matching algorithm accurately detect heartbeats in SCG signals in patients with valvular heart disease?
A novel, low-computational template matching algorithm for ECG-free heartbeat detection in SCG signals demonstrates high sensitivity and accuracy, making it suitable for wearable devices.
May support wearable SCG monitoring in valvular disease; leaves open prospective validation before clinical adoption.
Cardiac monitoring can be performed by means of an accelerometer attached to a subject’s chest, which produces the Seismocardiography (SCG) signal. Detection of SCG heartbeats is commonly carried out by taking advantage of a simultaneous electrocardiogram (ECG). SCG-based long-term monitoring would certainly be less obtrusive and easier to implement without an ECG. Few studies have addressed this issue using a variety of complex approaches. This study proposes a novel approach to ECG-free heartbeat detection in SCG signals via template matching, based on normalized cross-correlation as heartbeats similarity measure. The algorithm was tested on the SCG signals acquired from 77 patients with valvular heart diseases, available from a public database. The performance of the proposed approach was assessed in terms of sensitivity and positive predictive value (PPV) of the heartbeat detection and accuracy of inter-beat intervals measurement. Sensitivity and PPV of 96% and 97%, respectively, were obtained by considering templates that included both systolic and diastolic complexes. Regression, correlation, and Bland–Altman analyses carried out on inter-beat intervals reported slope and intercept of 0.997 and 2.8 ms (R2 > 0.999), as well as non-significant bias and limits of agreement of ±7.8 ms. The results are comparable or superior to those achieved by far more complex algorithms, also based on artificial intelligence. The low computational burden of the proposed approach makes it suitable for direct implementation in wearable devices.
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Centracchio et al. (2023) conducted an observational in Valvular heart diseases (n=77). Template matching algorithm for SCG signals vs. ECG-based heartbeat detection was evaluated on Sensitivity and positive predictive value of heartbeat detection. An ECG-free template matching algorithm for seismocardiography signals achieved 96% sensitivity and 97% positive predictive value for heartbeat detection in patients with valvular heart diseases.
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