91ÌÒÉ«

Current Project (2023-)

91ÌÒÉ« Team: Natalia Martínez, Berkay Özbek, Jiaqi Ge, Chloé Bernardoni, Adrien Rapeaux, Timothy Constandinou (PI) 

Project Partners: ESL at EPFL (Juan Sapriza,  David Mallasén, Davide Schiavone, David Atienza Alonso), Andrew Jackson (Newcastle University), Mint Neurotechnologies Ltd (Andrea Mifsud, Dorian Haci, Jonathan Casey, Ian Williams, Peilong Feng), William Muirhead (Queen Square and Francis Crick Institute). 

Background 

 By interfacing electronic devices with the nervous system, implantable neural interfaces can sense the brain activity in real time with targeted precision and high spatial resolution for applications such as neuromonitoring in epilepsy or Brain-Computer Interfaces (BCIs) to control robotic prosthetics or communication software.  

Some of the current challenges in implantable neural interfaces involve the development of minimally invasive, robust, power-efficient and safe devices. In addition to these technical challenges, widespread availability to these technologies is still limited. This is mainly due to economic factors, restrictions in regulations, capacity and scalability. One of the causes underlying this issue is the invasive and complex nature of the surgical interventions required to implant the devices, resulting in prolonged operation, hospitalisation and recovery times. 

Our approach 

ENGINI2 builds on the ENGINI project to develop a new generation of distributed neural interfaces that are low-power, wireless, and designed with clinical translation in mind. The project aims to address the main challenges that currently limit the scalability of implantable neural technologies, including power delivery, neural signal acquisition and processing, and mm-scale packaging. 

The project develops miniaturised implantable devices capable of sensing neural activity across both dense local regions and wider brain areas. To support this, ENGINI2 combines energy-efficient on-chip processing, as well as analogue and mixed-signal circuits that enable high-dynamic range sensing within stringent power constraints and under the presence of stimulation artifacts. 

Because distributed implants require reliable wireless operation, ENGINI2 also focuses on new strategies for wireless power transfer and implant autonomy. This work supports the long-term operation of multiple miniature implants while reducing the need for bulky hardware or wired connections. The project considers how these systems can communicate as part of a scalable network of implants. 

Beyond electronics design, ENGINI2 focuses on modular chip integration, and flexible probe connections designed to reduce tissue damage and improve long-term performance. By combining low-power electronics, wireless operation, advanced packaging, and system-level design, ENGINI2 seeks to support progress toward next-generation neural implants for diagnostic and rehabilitative applications.