Heart rate (HR) is a valuable and widespread measure for physical training programs, although its description of conditioning is limited to the cardiac response to exercise. More comprehensive measures of exercise adaptation include cardiac output (Q̇), stroke volume (SV) and oxygen uptake (V̇O2), but these physiological parameters can be measured only with cumbersome equipment installed in clinical settings. In this work, we explore the ability of pulse transit time (PTT) to represent a valuable pairing with HR for indirectly estimating Q̇, SV and V̇O2 non-invasively. PTT was measured as the time interval between the peak of the electrocardiographic (ECG) R-wave and the onset of the photoplethysmography (PPG) waveform at the periphery (i.e. fingertip) with a portable sensor. Fifteen healthy young subjects underwent a graded incremental cycling protocol after which HR and PTT were correlated with Q̇, SV and V̇O2 using linear mixed models. The addition of PTT significantly improved the modeling of Q̇, SV and V̇O2 at the individual level ([Formula: see text] for SV, 0.548 for Q̇, and 0.771 for V̇O2) compared to predictive models based solely on HR ([Formula: see text] for SV, 0.503 for Q̇, and 0.745 for V̇O2). While challenges in sensitivity and artifact rejection exist, combining PTT with HR holds potential for development of novel wearable sensors that provide exercise assessment largely superior to HR monitors.