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From Brain Science to Intelligent Machines

A BCI Operated Hand Exoskeleton based Neurorehabilitation System for Movement Restoration in Paralysis

This project is funded by UK India Education and Research Initiative (UKIERI) phase-II and the Department of Science and Technology (DST) Government of India under the DST-UKIERI Thematic Partnership program (DST-2013-14/126). This international collaborative project has three main components brain-computer interface (BCI), exoskeleton, and rehabilitation which are being undertaken under respective leaders Professor Girijesh Prasad of Neural Systems and Neuro-technology Research Team, Professor Ashish Dutta of Indian Institute of Technology Kanpur (IITK) India, and Professor Suzanne McDonough of Institute of Nursing and Health Research under the co-ordination  of the PI Professor Prasad. Main project objectives are as follows:

  • Develop a lightweight three-finger exoskeleton with embedded sensors, capable of replicating human motion for physical practice. It will be controlled by users’ EMG and EEG signals in assist-as-needed mode;
  • Develop a novel brain-computer interface (BCI) that facilitates EMG and EEG for controlling the exoskeleton and provides  visual neurofeedback to ensure focused physical and MI practices;
  • Conduct pilot trials to evaluate the effectiveness of the exoskeleton along with BCI in movement restoration

Functional Brain Mapping

The first functional brain mapping facility on the island of Ireland is to be established at the University of Ulster‘s Magee campus.

Enterprise Minister Arlene Foster announced a £5.3 million investment package for the advanced research project when she spoke at the Intelligent Systems Summit 2013 in June.

The facility will be the only brain imaging system anywhere in Ireland and only one of only a few in the UK to use the recently developed brain imaging modality, Magneto encephalography (MEG), to measure brain activity.


This project will create a self-learning robotic ecology, called RUBICON (for Robotic UBIquitous COgnitive Network), consisting of a network of sensors, effectors and mobile robot devices.

Enabling robots to seamlessly operate as part of these ecologies is an important challenge for robotics R&D, in order to support applications such as ambient assisted living, security, etc.

Current approaches heavily rely on models of the environment and on human configuration and supervision and lack the ability to smoothly adapt to evolving situations.


VISUALISE is an EU-funded project to create a refined understanding of retinal function in natural visual environments by examining the unique role that non-standard retinal ganglion cells play in dynamic visual processes.

VISUALISE will combine the efforts of physiologists, computational neuroscientists, neuromorphic electronic engineers, and roboticists, to build novel theoretical and hardware models of biological retinal ganglion cell types for dynamic vision applications such as robotic navigation or pursuit.


Biological neural systems are powerful, robust and highly adaptive computational entities that outperform conventional computers in almost all aspects of sensory-motor integration. Despite dramatic progress in information technology, there is a big performance discrepancy between artificial computational systems and brains in seemingly simple orientation and navigation tasks. In fact, no system exists that can faithfully reproduce the rich behavioural repertoire of the tiny worm Caenorhabditis elegans which features one of the simplest nervous systems in nature made of 302 neurons and about 8000 connections.