Brain-machine interfaces allow a person's brain to communicate directly with an external device by reading neural signals and translating them into actions. Scientists hope this will allow people with paralysis to control things like motorized wheelchairs or prosthetic limbs using only their thoughts. The BrainGate system is an example of this technology, using a 100 electrode array implanted on the motor cortex to read neural signals and control an external device. Artificial neural networks can model biological neurons and synapses to process and interpret neural signals. Non-invasive methods like EEG have lower resolution than invasive methods like ECoG but avoid surgery. Significant progress has been made in using brain-machine interfaces to restore motor function and develop assistive technologies.

1. BRAIN - MACHINE INTERFACE PRESENTED BY:-TUHIN DAS

2. What is Brain-Machine Interface?It is a collaboration in which a brain accepts and controls a mechanical device as a natural part of its representation of the bodyBy reading signals from an array of neurons and using computer chips and programs to translate the signals into action, scientists hope it will be possible for a person suffering from paralysis to control a motorized wheelchair or a prosthetic limb by just thinking about it

3. Concept of brain gateThe BrainGate system is a neuromotor prosthetic device consisting of an array of one hundred silicon microelectrodes, each of which is 1mm long and thinner than a human hair. The electrodes are arranged less than half a millimetre apart on the array, which is attached to a 13cm-long cable ribbon cable connecting it to a computer

4. Biological inspirationDendritesSoma (cell body)Axon

5. Biological inspirationdendritesaxonsynapsesThe information transmission happens at the synapses.

6. Artificial neuronsNeurons work by processing information. They receive and provide information in form of spikes.x1x2x3…xn-1xnw1Outputw2Inputsyw3...wn-1wnThe McCullogh-Pitts model

7. Artificial neuronsNonlinear generalization of the McCullogh-Pitts neuron:y is the neuron’s output, x is the vector of inputs, and w is the vector of synaptic weights.Examples:sigmoidal neuronGaussian neuron

8. Neural network mathematicsNeural network: input / output transformationW is the matrix of all weight vectors.

9. Cortical neural signal extraction: non-invasive vs. invasive recordingEEG Rhythms β and μ, P300, Slow cortical potential (SCP)Sampling rate 200-1000Hz, # of channels, from 1 or 2 to 128 or 256 ElectrodesBioactive, allowing growth of nerve, or bio-inactive multiple mircowires or multichannel electrode arraysSuperficial motor areas or deep brain structuresPrimary motor, parietal, premotor, frontoparietal, basal ganglia

10. HOMONCULUS: The littleguy

11. Cortical neural signal extraction: ECoGrestingimagining saying the word ‘move’(d) Imagery is associated with decrease in µ (8–12 Hz) and β (18–26 Hz) bands.A brain–computer interface using electrocorticographic signals in humans*Leuthardt et al 2004 J. Neural Eng. 1 63-71

12. CONTROLLING OF MACHINE :- BY HUMAN BRAIN

13. The Brain-Controlled VehicleSignal Processing Algorithms/Command ExtractionNeural InterfaceNeural SignalsDirectional controlControl CommandVehicle State SignalEnvironmental FeedbackVehicleSensors

14. ApplicationIt can help to restore any loss of senses 1.sense of vision2.sense of hearing3.sense of movementcreation of human robotsCreation of detective rats

15. Biggest rewardOn 7th november 2009 toyota launched it’s wheel chair that works on thoughtIt has a reaction time of 123 milliseconds

16. THANK YOU…..