Automatic modeling based on cultural programming for osseointegration diagnosis

The problem of modeling equivalent circuits for interpreting Electrical Impedance Spectroscopy (EIS) data in monitoring osseointegration level of metallic implants in bone is faced by means of an evolutionary programming approach based on cultural algorithms. With respect to stateof-the-art gene expression programming, the information on search advance acquired by most promising individuals during the evolution is shared with the entire population of potential solutions and stored also for next generations. Experimental results of the application such cultural programming-based analytical modeling to in-vitro EIS measurements of bone in-growth around metallic implants during prosthesis osseointegration are presented.