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 ((Q) over dot), stroke volume (SV) and oxygen uptake ((V) over dotO(2)), 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 (Q) over dot, SV and (V) over dotO(2) 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 (Q) over dot, SV and (V) over dotO(2) using linear mixed models. The addition of PTT significantly improved the modeling of (Q) over dot, SV and (V) over dotO(2) at the individual level (R-1(2) = 0.419 for SV, 0.548 for (Q) over dot, and 0.771 for (V) over dotO(2)) compared to predictive models based solely on HR (R-1(2) = 0.379 for SV, 0.503 for (Q) over dot, and 0.745 for (V) over dotO(2)). 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.