Genetically encoded redox sensors, such as the Hyper and roGFP sensor families, are powerful tools for enumerating the real-time dynamics of hydrogen peroxide in cells. In typical experiments, a dynamic profile of sensor oxidation and reduction is obtained following an external hydrogen peroxide perturbation. Using these profiles to characterise the quantitative relationship between the hydrogen peroxide concentration and sensor outputs is challenging as non-linearity in sensor responses to hydrogen peroxide may not be evident. Further, it is unclear how different sensors could be compared. We tested whether these profiles could be characterised by the area under the curve (AUC), signal amplitude, signal time and signal duration parameters. In baker’s yeast, the Hyper7 AUC and amplitude showed a strong linear correlation (r>0.9) to a wide range of hydrogen peroxide concentrations (1-1000 μM). These responses were higher than roGFP2-Tsa2ΔCR parameters at hydrogen peroxide concentrations greater than 100 μM. By contrast, the roGFP2-Tsa2ΔCR AUC and amplitude plots presented distinct linear correlation equations for lower (<100 μM) and higher hydrogen peroxide (>100 μM) concentrations establishing that this sensor’s output is range specific. The signal time and duration for Hyper7 were lower than roGFP2-Tsa2ΔCR at higher hydrogen peroxide concentrations (>100 μM), showing that its activation/deactivation cycle was faster. By contrast, in the fission yeast, the AUC and amplitude for Hyper7 and roGFP2-Tpx1.C169S both showed distinct linear correlations for lower (<50 μM) and higher (>50 μM) concentrations, and the signal time and duration were constant in this background. These results show that any purported correlation between hydrogen peroxide input and sensor output depends on the sensor, cell type and the hydrogen peroxide concentration range chosen. In summary, this method facilitates the characterisation signalling data generated by redox sensors.