Recognition of activities of daily living (ADL) is an essential component of assisted living
systems based on actigraphy. This task can nowadays be performed by machine learning
models which are able to automatically extract and learn relevant features but, most of time,
need to be trained with large amounts of data collected on several users. In this paper, we
propose an approach to learn personalized ADL recognition models from few raw data
based on a specific type of neural network called matching network. The interest of this few …