QUMPHY Software package

At the core of this project stands the development of measures to quantify the uncertainties associated with machine learning (ML) algorithms applied to medical problems, in particular the analysis and processing of photoplethysmography (PPG) signals. To achieve this the following tasks will be addressed: (i) benchmark datasets will be generated using publicly available in vivo, in vitro and synthetic data (ii) different ML models and uncertainty quantification (UQ) methods will be used to analyse the processing of the PPG signals and specify the associated uncertainty and (iii) a good practice guide with accompanying software repository showcasing the used models, methods and benchmarks will be developed and made publicly available.