Imperial College London > Talks@ee.imperial > Featured talks > Semi- and non-invasive brain-machine interfaces in humans - Part 1

Semi- and non-invasive brain-machine interfaces in humans - Part 1

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A brain-machine interface (BMI) allows subjects to control external devices (e.g. a prosthesis or a computer) directly by their brain activity without participation of the spinal cord or the peripheral motor system. Such BMIs aim to restore lost behavioral functionality, e.g. movement and communication abilities, of paralyzed patients.

Our BMI approach is to transfer neuronal activity controlling movements of a natural effector (e.g. arm or hand) for equivalent controls of an external effector. This direct motor BMI approach has the advantages of being intuitive and precise, and requiring only a small amount of training. Until recently this approach was successfully implemented only with spiking activity measured using intracortical microelectrodes. We are developing direct motor BMIs using non- and semi-invasive recording techniques as EEG /MEG and ECoG (field potentials measured directly from the surface of the human brain). I will show that different parameters of natural hand/arm movements (e.g. movement direction, velocity and grasp) can be accurately predicted from theses signals and used for real-time control of external actuators. Moreover, I will demonstrate the stability of the neuronal control signals used in our approach.

ABOUT THE SPEAKER Dr Mehring is a Senior Lecturer with both the Departments of Bioengineering and Electrical & Electronic Engineering, and is an Honorary Senior Lecturer at the Institute of Neurology, UCL , and Principal Investigator, Bernstein Centre, Albert-Ludwigs-University Freiburg.

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