Vieira-Marques, PedroTeixeira, João FonsecaValente, JoséPinho, BernardoGuedes, RuiAlmeida, RuteJácome, CristinaPereira, AnaJacinto, TiagoAmaral, RitaGonçalves, IvâniaSousa, Ana SáCouto, MarianaMagalhães, ManuelBordalo, DianaSilva, Luís NogueiraFonseca, J. Almeida2021-01-052021-01-052020-08Vieira-Marques, P., Teixeira, J. F., Valente, J., Pinho, B., Guedes, R., Almeida, R., Jácome, C., Pereira, A., Jacinto, T., Amaral, R., Gonçalves, I., Sá Sousa, A., Couto, M., Pereira, M., Magalhães, M., Bordalo, D., Nogueira Silva, L., & Almeida Fonseca, J. (2020). Combined Image-Based Approach for Monitoring the Adherence to Inhaled Medications. Em J. Henriques, N. Neves, & P. de Carvalho (Eds.), XV Mediterranean Conference on Medical and Biological Engineering and Computing – MEDICON 2019 (pp. 1399–1404). Springer International Publishing. https://doi.org/10.1007/978-3-030-31635-8_171http://hdl.handle.net/10400.22/16658The adherence to inhaled controller medications is of critical importance to achieve good clinical results in patients with chronic respiratory diseases. To objectively verify the adherence, a detection tool was previously developed and integrated in the mobile application InspirerMundi, based on image processing methods. In this work, a new approach for enhanced adherence verification was developed. In a first phase template matching is employed to confirm the inhaler positioning and to locate the dose counter. In a second phase Google ML Kit framework is used for the detection of each numerical dose in the dose counter. The proposed approach was validated through a new detection tool pilot implementation, using a set of images collected by patients using the application in their daily life. Performance of each of the two phases was evaluated for a set of commonly used inhaler devices. Promising results were achieved showing the potential of mobile embedded sensors without the need for external devices.engMedication adherenceSmart deviceImageconference object10.1007/978-3-030-31635-8_171