Objective: Electrocardiogram (ECG) has been regarded as a source of respiratory information with the main focus in the estimation of the respiratory rate. Although little research concerning the estimation of tidal volume (TV) has been conducted, there are several ECG-derived features that have been related with TV in the literature, such as ECG-derived respiration, heart rate variability, and respiratory rate. In this paper, we exploited these features for estimating TV using a linear model.
Methods: 25 young (33.4 ± 5.2 years) healthy male volunteers were recruited for performing a maximal (MaxT) and a submaximal (SubT) treadmill stress test, which were conducted on different days. Both tests were automatically segmented in stages attending to the heart rate. Afterwards, a subject-specific TV model was calibrated for each stage, employing features from MaxT, and the model was later used for estimating the TV in SubT.
Results: During exercise, the different proposed approaches led to relative fitting errors lower than 14% in most of the cases and 6% in some of them.
Conclusion: Low achieved fitting errors suggest that TV can be estimated from ECG during a treadmill stress test.
Significance: The results suggest that it is possible to estimate TV during exercise using only ECG-derived features.