LAUSR

Introduction Seismocardiography (SCG) is a potential method for ambulatory assessment of heart failure (HF) status. New sensor and digital processing capabilities are expanding the possible utility of this approach. The SCG waveform, however, exhibits significant variability to which respiratory effects may be a major contributor. Hence, accounting for respiratory effects may improve SCG waveform interpretation, and support improved utility for HF assessment. Objective The objective of this study was to document SCG waveform respiratory variation and determine optimal criteria for minimizing its impact on signal variability. Methods Air flow and SCG were simultaneously measured in 20 healthy subjects. SCG waveforms were divided into two groups using three different criteria: Inspiration vs. expiration, low vs. high lung volume, and maximum intra-group similarity using Euclidean distance within and between groups. Results The separation between the two groups significantly improved when the maximum intra-group similarity criterion was implemented (p Conclusions Optimal decrease in signal variability was achieved using a maximum intra-group similarity method. Use of this may help increase robustness of SCG signal interpretation and their utility for HF monitoring.