Heart rate variability (HRV) is a physiological phenomenon of the variation of a cardiac interval (interbeat) over time that reflects the activity of the autonomic nervous system. HRV analysis is usually based on electrocardiograms (ECG signals) and has found many applications in the diagnosis of cardiac diseases, including valvular diseases. This analysis could also be performed on seismocardiograms (SCG signals) and gyrocardiograms (GCG signals) that provide information on cardiac cycles and the state of heart valves. In our study, we sought to evaluate the influence of valvular heart disease on the correlations between HRV indices obtained from electrocardiograms, seismocardiograms, and gyrocardiograms and to compare the HRV indices obtained from the three aforementioned cardiac signals. The results of HRV analysis in the time domain and frequency domain of the ECG, SCG, and GCG signals are within the standard deviation and have a strong linear correlation. This means that despite the influence of VHDs on the SCG and GCG waveforms, the HRV indices are valid. Clinical Relevance-Cardiac mechanical signals (seismocar-diograms and gyrocardiograms) can be applied to evaluate heart rate variability despite the influence of valvular diseases on the morphology of cardiac mechanical signals.