To study acute emotional stress, a linear approach may not correspond to the non-deterministic variation due to aetiology of the stress phenomenon itself. Besides that, assuming a linear model such as classic heart rate variability analysis usually has high computational cost and high artefact dependency. A nonlinear approach based on Chaos theory using Higuchi fractal dimension (HFD) is presented to define a measurement methodology for acute emotional stress. HFD was computed for a set of electrophysiological signals recorded during relax and stress states of an ad hoc experiment. Results show that for most of the signals HFD is able to differentiate among relax and stress states. This approach applied to electrocardiogram signals is not affected by the sample rate and does not need pre-process filtering. Photo-plethysmography data is only significant in the highest stress state. So, it can be used to evaluate stress levels higher than those had in this experiment.