In the BDAS project one of the goals is to create a new solution for monitoring bone healing to complement current techniques. Data have been collected in clinical trials from infants treated for Craniosynostosis by a craniotomic surgery. The data are collected with a biomedical sensor based in microwave technology. This sensor could be able to sense changes in the composition of the different tissues in the upper hemisphere of the head, by noticing a difference in the propagation of the microwaves, as the bone injury from the craniectomy heals over time. In this thesis I analyze the validity of a proposed analytical model for the biosensor and extend the clinical data analysis in BDAS project. The validity of the model is analyzed by comparing its outcomes to available measurements from phantoms mimicking living tissues and to numerical simulations. In the data analysis two hypotheses are formulated and tested regarding the location of the measurement points with respect to a positioning grid and the healing over time too. By deriving a set of parameters for each collected dataset in the clinical trials, a distinct pattern was found which shows visible changes over the course of the healing process with this technique.