In recent years we have witnessed the growth of a number of multimedia, health, cognitive learning, gaming user applications which include monitoring and processing of the users’ physiological signals, also termed biosignals or vital signs. The acquisition of the biosignals should be non-invasive and should not affect the activities and arousal of the user to achieve relevant results. Developments in mobile devices, e.g. smartphones, tablet PCs, etc. and electrode design have enabled unobtrusive acquisition and processing of biosignals, especially for mobile and non-clinical applications. The paper reviews recently developed non-clinical applications that exploit biosignal information. The paper analyses challenges for digital signal processing that arise from data acquisition from the mobile user are presented with focus on the electrocardiogram (ECG). Influence of the analysed challenges is demonstrated on a selected QRS detection algorithm by using signals from the MIT-BIH Noise stress test database (
). Results confirm that algorithms for processing signals of mobile users need a more thorough preprocessing procedure as opposed to simple band-pass filtering.