  Seismocardiography (SCG) is a non-invasive method that can be used for
cardiac activity monitoring. This paper presents a new electrocardiogram (ECG)
independent approach for estimating heart rate (HR) during low and high lung
volume (LLV and HLV, respectively) phases using SCG signals. In this study,
SCG, ECG, and respiratory flow rate (RFR) signals were measured simultaneously
in 7 healthy subjects. The lung volume information was calculated from the RFR
and was used to group the SCG events into low and high lung-volume groups. LLV
and HLV SCG events were then used to estimate the subjects HR as well as the HR
during LLV and HLV in 3 different postural positions, namely supine, 45 degree
heads-up, and sitting. The performance of the proposed algorithm was tested
against the standard ECG measurements. Results showed that the HR estimations
from the SCG and ECG signals were in a good agreement (bias of 0.08 bpm). All
subjects were found to have a higher HR during HLV (HR$_\text{HLV}$) compared
to LLV (HR$_\text{LLV}$) at all postural positions. The
HR$_\text{HLV}$/HR$_\text{LLV}$ ratio was 1.11$\pm$0.07, 1.08$\pm$0.05,
1.09$\pm$0.04, and 1.09$\pm$0.04 (mean$\pm$SD) for supine, 45 degree-first
trial, 45 degree-second trial, and sitting positions, respectively. This heart
rate variability may be due, at least in part, to the well-known respiratory
sinus arrhythmia. HR monitoring from SCG signals might be used in different
clinical applications including wearable cardiac monitoring systems.
