The research paper titled “Comparison of Data Compression Methods for Implanted Real-Time Peripheral Nervous System” co-authored by Antonio Coviello, Anna Bersani, Fabiana Del Bono, Paolo Motto Ros, Danilo Demarchi, Umberto Spagnolini, and Maurizio Magarini, has been awarded as Best Poster at 2023 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE 2023).

The paper focuses on real-time data compression of electro neurographic (ENG) signals measured by a sensor placed around a nerve in the peripheral system. The measured ENG signal is sent from the sensor to an external computer that classifies it. The goal of the classification is to extract the information about the motor/sensory stimulus that would have been generated by the signal itself if it had arrived at its destination. The compression method proposed in the Best Poster Award-winning work has the merit of achieving a reduction in bit rate per second without compromising the accuracy of the classification, thus reducing the impact on power consumption.

The award represents an important recognition of the work the Department of Electronics, Information and Bioengineering is doing toward the development of a fully implantable peripheral nerve interface in the ongoing collaboration between Politecnico di Milano and Politecnico di Torino that started thanks to Alta Scuola Politecnica.