Oliveira, AlexandraAguiar, JoyceSilva, ElianaFaria, Brígida MónicaGonçalves, HelenaTeófilo, LuísGonçalves, JoaquimCarvalho, VictorCardoso, Henrique LopesReis, Luís PauloFaria, Brigida MonicaOliveira, Alexandra2025-10-282025-10-282020-05-18Oliveira, A., Aguiar, J., Silva, E., Faria, B. M., Gonçalves, H., Teófilo, L., Gonçalves, J., Carvalho, V., Cardoso, H. L., & Reis, L. P. (2020). Assessing daily activities using a PPG Sensor embedded in a Wristband-Type Activity Tracker. Em Á. Rocha, H. Adeli, L. P. Reis, S. Costanzo, I. Orovic, & F. Moreira (Eds.), Trends and Innovations in Information Systems and Technologies (WorldCIST 2020) (Vol. 3, pp. 108–119). Springer International Publishing. https://doi.org/10.1007/978-3-030-45697-9_11978-3-030-45697-9http://hdl.handle.net/10400.22/30685Due to the technological evolution on wearable devices, biosignals, such as inter-cardiac beat interval (RR) time series, are being captured in a noncontrolled environment. These RR signals, derived from photoplethysmography (PPG), enable health status assessment in a more continuous, non-invasive, nonobstructive way, and fully integrated into the individual’s daily activity. However PPG is vulnerable to motion artefacts, which can affect the accuracy of the estimated neurophysiological markers. This paper introduces a method for motion artefact characterization in terms of location and relative variation parameters obtained in different common daily activities. The approach takes into consideration interindividual variability. Data was analyzed throughout related-samples Friedman’s test, followed by pairwise comparison with Wilcoxon signed-rank tests with a Bonferroni correction. Results showed that movement, involving only arms, presents more variability in terms of the two analyzed parameters.engPPG signalsDaily lifeHuman activity detectionSensory instrumentationPhotoplethysmographyMotion artifactsHeart rateSensor-based applicationsconference paper10.1007/978-3-030-45697-9_11