Key result
ECG-free SCG and GCG template matching estimates HRV indices with relative errors down to ~0.3%.
Why the study?
Heartbeat detection in cardio-mechanical signals usually requires a concurrent ECG lead, limiting standalone monitoring, while ECG-free detection is challenging due to complex signal morphology.
Does an ECG-free template matching heartbeat detection algorithm applied to Seismocardiography and Gyrocardiography signals provide accurate Heart Rate Variability indices compared to reference ECG in healthy subjects and patients with valvular heart disease?
Observational (n=129)
Does an ECG-free template matching heartbeat detection algorithm applied to Seismocardiography and Gyrocardiography signals provide accurate Heart Rate Variability indices compared to reference ECG in healthy subjects and patients with valvular heart disease?
This study provides initial evidence that standalone, ECG-free monitoring of heart rate variability via wearable seismocardiography and gyrocardiography sensors is feasible using normalized cross-correlation template matching, particularly in resting healthy subjects.
Answers are grounded in this paper and cite their sources.
May support wearable ECG-free HRV monitoring in healthy subjects at rest; leaves open validation in valvular disease.
Cardio-mechanical monitoring techniques, such as Seismocardiography (SCG) and Gyrocardiography (GCG), have received an ever-growing interest in recent years as potential alternatives to Electrocardiography (ECG) for heart rate monitoring. Wearable SCG and GCG devices based on lightweight accelerometers and gyroscopes are particularly appealing for continuous, long-term monitoring of heart rate and its variability (HRV). Heartbeat detection in cardio-mechanical signals is usually performed with the support of a concurrent ECG lead, which, however, limits their applicability in standalone cardio-mechanical monitoring applications. The complex and variable morphology of SCG and GCG signals makes the ECG-free heartbeat detection task quite challenging; therefore, only a few methods have been proposed. Very recently, a template matching method based on normalized cross-correlation (NCC) has been demonstrated to provide very accurate detection of heartbeats and estimation of inter-beat intervals in SCG and GCG signals of pathological subjects. In this study, the accuracy of HRV indices obtained with this template matching method is evaluated by comparison with ECG. Tests were performed on two public datasets of SCG and GCG signals from healthy and pathological subjects. Linear regression, correlation, and Bland-Altman analyses were carried out to evaluate the agreement of 24 HRV indices obtained from SCG and GCG signals with those obtained from ECG signals, simultaneously acquired from the same subjects. The results of this study show that the NCC-based template matching method allowed estimating HRV indices from SCG and GCG signals of healthy subjects with acceptable accuracy. On healthy subjects, the relative errors on time-domain indices ranged from 0.25% to 15%, on frequency-domain indices ranged from 10% to 20%, and on non-linear indices were within 8%. The estimates obtained on signals from pathological subjects were affected by larger errors. Overall, GCG provided slightly better performances as compared to SCG, both on healthy and pathological subjects. These findings provide, for the first time, clear evidence that monitoring HRV via SCG and GCG sensors without concurrent ECG is feasible with the NCC-based template matching method for heartbeat detection.
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Parlato et al. (2023) conducted an observational in Valvular heart diseases and healthy volunteers (n=129). ECG-free heartbeat detection in Seismocardiography (SCG) and Gyrocardiography (GCG) signals using normalized cross-correlation (NCC) template matching vs. Simultaneously acquired Electrocardiography (ECG) signals was evaluated on Agreement and relative errors of 24 time-domain, frequency-domain, and non-linear heart rate variability (HRV) indices extracted from SCG and GCG compared with ECG. ECG-free NCC template matching on SCG and GCG signals estimated HRV indices in healthy subjects with relative errors of 0.25%-15% (time-domain), 10%-20% (frequency-domain), and <=8% (non-linear).
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