Muñoz, John EdisonGouveia, Elvio RubioCameirão, Mónica S.Bermúdez i Badia, Sergi2018-12-132018-12-132017http://hdl.handle.net/10400.13/2201The exponential increase of wearable health-tracking technologies offers new possibilities but also poses new challenges in signal processing to enable fitness monitoring through multimodal physiological recordings. Although there are several software tools used for postprocessing in physiological computing applications, limitations in the analysis, incorporating signals from multiple sources, integrating contextual information and providing information visualization tools prevent a widespread use of this technology. To address these issues, we introduce PhysioLab, a multimodal processing Matlab tool for the data analysis of Electromyography (EMG), Electrocardiography (ECG) and Electrodermal Activity (EDA). The software is intendedtofacilitatetheprocessingandcomprehensionofmultimodalphysiologicaldatawiththe aim of assessing fitness in several domains. A unique feature of PhysioLab is that is informed by normative data grouped by age and sex, allowing contextualization of data based on users’ demographics. Besides signal processing, PhysioLab includes a novel approach to multivariableengCardiorespiratory fitness assessmentElderly population.Faculdade de Ciências Sociaisjournal article10.1007/s11042-017-5069-z