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Dr Tim Constandinou

Millimetre-scale implantable brain machine interfaces

Being able to control devices with our thoughts is a concept that has for long captured the imagination. Neural Interfaces or Brain Machine Interfaces (BMIs) are devices that aim to do precisely this. There is currently great interest and efforts in the community in this field, but also significant challenges. This talk will present the state-of-the-art, identify the key challenges and report our recent efforts to addressing these - developing millimetre-scale implantable devices. Next generation devices will be distributed like the brain itself. It is currently estimated that if we could record electrical activity simultaneously from between 1,000 and 10,000 neurons, this would enable useful prosthetic control (e.g. of a prosthetic arm). However, rather than relying on a single, highly complex implant and trying to integrate more and more channels in this high density interface (the current paradigm) an emerging trend, and topic of this special session, is to develop a simpler, smaller, safer, and well-engineered primitive, and deploy multiple such devices. It is essential these are each compact, autonomous, calibration-free, and completely wireless. It is envisaged that each device will be mm-scale, and be capable of monitoring fewer sites, but also perform real-time signal processing. This processing will achieve data reduction to wirelessly communicate only useful information, rather than raw data, which can most often be just noise and of no use. Making these underlyingdevices "simpler" will overcome many of the common challenges that are associated with scaling of neural interfaces, for example, wires breaking, biocompatibility of the packaging, thermal dissipation and yield. By distributing tens to hundreds of these in a "network" of neural interfaces, many of the desirable features of distributed networks come into play; for example, redundancy and robustness to single component failure. Such devices will communicate the neural "control signals” to an external prosthetic device. These can then, for example, be used for: an amputee to control a robotic prosthesis; a paraplegic to control a mobility aid; or an individual with locked-in syndrome to communicate with the outside world.

Biography: Timothy Constandinou received the B.Eng. and Ph.D. degrees in electronic engineering from Imperial College London, in 2001 and 2005, respectively. He is currently a Reader of Neural Microsystems within the Circuits and Systems Group, Department of Electrical and Electronic Engineering at Imperial College London and also the Deputy Director of the Centre for Bio-Inspired Technology. His current research interests include neural microsystems, neural prosthetics, brain machine interfaces, implantable devices, and low-power microelectronics. He leads the Next Generation Neural Interfaces research group at Imperial. The group utilises integrated circuit and microsystem technologies to create advanced neural interfaces that enable new scientific and prosthetic applications. He is a senior member of the IEEE, fellow of the IET, a chartered engineer, and member of the IoP. Within the IEEE, he serves on several committees/panels, regularly contributing to conference organization,technical activities, and governance. He currently serves on the IEEE Circuits & Systems Society (CASS) Board of Governors for the term 2017-19, is associate editor of IEEE Transactions on Biomedical Circuits & Systems (TBioCAS), chairs the IEEE CASS Sensory Systems Technical Committee, and serves on the IEEE BRAIN Initiative Steering Committee and IEEE CASS BioCAS Technical Committee. He was the technical program Co-Chair of the 2010, 2011 and 2018 IEEE BioCAS conferences, General Chair of the BrainCAS 2016 and NeuroCAS 2018 workshops, Special Session Co-Chair of the 2017 IEEE ISCAS Conference, and Demonstrations Co-Chair of the 2017 BioCAS Conference.