A Clinical Method for Estimation of VO2max Using Seismocardiography

Area of Science:

• Cardiovascular Physiology
• Biomedical Engineering
• Exercise Science

Background:

• Cardiorespiratory fitness, often measured as maximal oxygen uptake (VO₂max), is a key health indicator.
• Current non-exercise methods for estimating VO₂max can lack accuracy.
• The seismocardiogram (SCG), a measure of cardiac vibrations, has potential for physiological assessment.

Purpose of the Study:

• To investigate the correlation between seismocardiogram (SCG) features and cardiorespiratory fitness (VO₂max).
• To develop and validate a non-exercise prediction model for VO₂max using SCG data and demographic information.

Main Methods:

• Healthy subjects underwent simultaneous seismocardiogram (SCG) and electrocardiogram (ECG) recordings at rest.
• Maximal oxygen uptake (VO₂max) was determined via a graded exercise test on a cycle ergometer.
• SCG amplitudes and timing intervals were extracted and integrated with age, sex, and BMI into a prediction model.

Main Results:

• A specific SCG amplitude (following aortic valve closure) strongly correlated with VO₂max (r=0.80, p<0.001).
• The combined SCG-based model achieved a high correlation with measured VO₂max (r=0.90, p<0.001).
• The model demonstrated superior performance compared to other non-exercise VO₂max prediction methods, even after cross-validation.

Conclusions:

• Seismocardiogram (SCG) signals contain valuable information for estimating cardiorespiratory fitness (VO₂max).
• The developed non-exercise SCG-based model offers a more accurate VO₂max estimation than current alternatives.
• While effective for baseline assessment, the model's utility in tracking VO₂max changes requires further investigation.