Pinto, João RibeiroCardoso, Jaime S.Brömme, ArslanBusch, ChristophDantcheva, AntitzaRaja, KiranRathgeb, ChristianUhl, Andreas2020-09-162020-09-162020978-3-88579-700-5https://dl.gi.de/handle/20.500.12116/34321The literature seems to indicate that the QRS complex is the most important component of the electrocardiogram (ECG) for biometrics. To verify this claim, we use interpretability tools to explain how a convolutional neural network uses ECG signals to identify people, using on-theperson (PTB) and off-the-person (UofTDB) signals. While the QRS complex appears indeed to be a key feature on ECG biometrics, especially with cleaner signals, results indicate that, for larger populations in off-the-person settings, the QRS shares relevance with other heartbeat components, which it is essential to locate. These insights indicate that avoiding excessive focus on the QRS complex, using decision explanations during training, could be useful for model regularisation.enBiometricsElectrocardiogramExplainabilityIdentificationInterpretabilityText/Conference Paper1617-5468