AI Denmark: Monitoring and tracking of disease progression in Oedema patients using sensor data

Based on sensor data (C measure and activity measure) and manual measurements obtained by medical professionals, we analysed the association between the different measurements to estimate the actual disease progression in Oedema patients.

We suggested several experiments to estimate the effects of the various sources of error. Another important result was the discovery that activity data was a strong predictor of the sensor measurements, and the relationship could be modelled effectively using a simple time series model.