Mireia Calvo González

After graduating in 2011 as a telecommunications engineer at Universitat Politècnica de Catalunya, with an internship at the Illinois Institute of Technology in Chicago (USA), she obtained in 2014 a MSc in Biomedical Engineering from both Universitat de Barcelona and Universitat Politència de Catalunya. During her studies, she worked as an eHealth researcher at Barcelona Digital Technology Center, and then as a research engineer at Hospital Clínic de Barcelona. In 2017, she obtained a European PhD in Signal processing from Université de Rennes 1 (France), and in Biomedical Engineering from Universitat Politècnica de Catalunya, thanks to postgraduate grants from Obra Social La Caixa (Spain), and from Fédération Hospitalo-Universitaire de Technologies pour la Santé (France). Then, she holded a postdoctoral position at Université de Rennes 1, in partnership with Cairdac, a company specialized in medical devices.

Group: Biomedical signal processing and interpretation
Supervisor: Raimon Jané
Project: Characterization of chronic respiratory diseases through the development and validation of novel signal-processing and model-based approaches for personalized medicine

Chronic respiratory diseases (CRDs) such as chronic obstructive pulmonary disease (COPD) and sleep apnea syndrome (SAS) affect millions of people nowadays. Indeed, more than 3 million people die each year from COPD, an estimated 6% of all deaths worldwide, making this disease the fourth leading cause of global death.
The main objective of the proposed project is to provide new tools for personalized medicine, based on advanced signal-processing and model-based approaches, for the characterization of CRDs. The development and evaluation of these approaches could provide new insights into the underlying mechanisms regulating the cardiorespiratory system under physiological and pathological conditions, improving physiopathology and prognosis interpretation, with a potential future impact on diagnosis, prevention and therapeutic strategies. More specifically, the study of the cardiorespiratory system interactions with other physiological systems involved in CRDs will allow: i) in the short-term, a better characterization of the physiology involved in respiration, ii) in the mid-term, a better understanding of the physiopathology and prognosis of different respiratory diseases, and iii) in the long-term, the proposal and validation of novel strategies for the prevention, diagnosis and treatment of CRDs.
The proposed methodology is based on a knowledge-based approach combining novel signal-processing and model-based techniques, integrating clinical data of different nature (ECG, EEG, respiration, acceleration, etc.), acquired from different human and animal populations, under conditions of health, COPD and SAS. This research proposes a novel interdisciplinary approach that would be a step forward towards the understanding of respiratory diseases, with a potential future impact on the design of personalized therapies.