Modelling and Characterization of ELF MF Exposure of Children with Machine Learning Techniques

The paper describes a novel approach based on Machine Learning (ML) to characterize the exposure of children to extremely low frequency magnetic field (ELF-MF, 40-800Hz). Unsupervised cluster analysis is applied on MF registrations from a cohort 977 children during 24h. The aim is to better characterize children exposure with respect to daily activities, subject location, environmental conditions.