This event will be hosted on Zoom. You can access the webinar on the day by visiting https://zoom.us/join and using the following details:
- Zoom ID: 940 2477 9451
- Zoom passcode: 895881
Future neuroprostheses will be tightly coupled with the user in such a way that the resulting system will replace and restore impaired upper-limb functions. This is because they will be controlled by the same neural signals as their natural counterparts.
A key component of these neuroprostheses is a brain-machine interface (BMI). This enables users to interact with computers and robots through the voluntary modulation of their brain activity. Central to the BMI is its capability to distinguish different patterns of brain activity in real time, such as an intention or mental task. But, this is challenging due to the limited information carried by brain signals we can measure, no matter the recording modality.
So how is it possible to operate complex brain-controlled robots over long periods of time? In this talk, I will argue that efficient brain-machine interaction, as the execution of voluntary movements, requires the integration of several parts of the CNS and the external actuators. I will put forward principles to design neuroprostheses and illustrate these through working prototypes of brain-controlled robots and applications for disabled and able-bodied people alike.
Professor José del R Millán holds the Carol Cockrell Curran Chair in the Department of Electrical and Computer Engineering at The University of Texas at Austin. He is also a professor in the Department of Neurology of the Dell Medical School. Before joining UT Austin, he was a research scientist at the Joint Research Centre of the European Commission in Ispra, Italy, and a senior researcher at the Idiap Research Institute in Martigny, Switzerland.
Most recently, he held the Defitech Foundation Chair in Brain-Machine Interface at the École Polytechnique Fédérale de Lausanne in Switzerland. There he helped establish the Center for Neuroprosthetics. Professor Millán has made big contributions to the field of brain-machine interfaces, and especially EEG signals. Most of his achievements revolve around the design of brain-controlled robots. He has received several recognitions for these seminal and pioneering achievements, notably the IEEE-SMC Norbert Wiener Award, elevation to IEEE Fellow and IAMBE Fellow.
As well as his work on the fundamentals of BMI and design of neuroprosthetics, Millán is prioritising the translation of BMI to end-users who live with motor and cognitive disabilities. He is also designing BMI technology to offer new interaction modalities for healthy persons.