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1 Decoding Neural Activity from an Intracortical Implant in Humans with Tetraplegia Chad E. Bouton Battelle Health and Life Sciences Division.

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Presentation on theme: "1 Decoding Neural Activity from an Intracortical Implant in Humans with Tetraplegia Chad E. Bouton Battelle Health and Life Sciences Division."— Presentation transcript:

1 1 Decoding Neural Activity from an Intracortical Implant in Humans with Tetraplegia Chad E. Bouton Battelle Health and Life Sciences Division

2 2 Background Cyberkinetics (founded in 2001) developed a Brain-Computer Interface (BCI) system called BrainGate At the core of the system was the Utah Electrode Array (brain implant) Implanted in the Primary Motor Cortex (M1), hand/arm area Purpose was to allow severely disabled individuals to communicate, use their PC’s, and even control a wheelchair by decoding their thoughts

3 3 Elbow Extension Background Battelle developed user training methods and Neural Decoding Algorithms Processed signals from the electrode array (96 channels) Goal: isolate and predict arm/hand movements the patient is thinking about Time Domain Signals from Electrode Array Neural Decoding Shoulder Abduction Wrist Flexion

4 4 Patients 54 year old female stroke victim (“SCI 3”), quadriplegic and unable to speak 36 year old male, diagnosed with ALS, quadriplegic and unable to speak Conducted an intended motion survey to look at neural modulation (change in neuronal firing patterns) for various visually cued movements –Shoulder Flexion and Extension –Shoulder Abduction and Adduction –Elbow Flexion and Extension –Wrist Flexion and Hyperextension –Wrist Radial and Ulnar Deviation –Wrist Pronation and Supination –Hand Open and Close

5 5 Initial Motion Survey with SCI3 Zero Units (Neurons) Exhibited Differing Firing Patterns Flexion/extension mixed (dark/med blue) (Axes are unit-less and represent the first three principal components from a principal components / eigenvector analysis.)

6 6 Thought-Driven Cursor Previous decoding methods (from non-human primate work) –Position based (assumed neural patterns correlated to position in space) –Early demonstration in a human subject: BG SCI P003 - Center Out wmvBG SCI P003 - Center Out wmv Marginally stable results - proprioceptive feedback is disrupted in a disabled user Introduced user training methods - used motion demonstration (mirror neuron activation) and ‘coaching’ periods Moved away from position-based decoding and utilized model-based approaches along with support vector machine methods Results for Battelle decoding algorithm - stabilized cursor motion by isolating 6 intended motions: rest, four wrist motions, and close hand: –SCI P Great - excellent motion and diagonal.movSCI P Great - excellent motion and diagonal.mov

7 7 Increasing Degrees-of-Freedom -12 Motions (6 DOF) Recognized by Algorithm

8 8 Adaptive Algorithm Subject ALS1 exhibited decreased and inconsistent performance Incorporated performance feedback during training (“dots/masses on springs”) Adapted decoding algorithm after each training block Demonstration: ALS1_4DOF_matlab_screen.wmv ALS1_4DOF_matlab_screen.wmv

9 9 Communicating to Others Locked-in syndrome 5 imagined movements to move and ‘click’ cursor over virtual keyboard: Aug_Communications_Wonderful_high_quality.wmv Aug_Communications_Wonderful_high_quality.wmv

10 10 Wheelchair Control Mobility extremely important and can be difficult/impossible for certain patients with existing interfaces As aired on 60 Minutes (Nov. 2, 2008), Cathy Hutchinson became the world’s first person to control a wheelchair with a brain implant (using the Battelle training and decoding methods) –Stroke Patient - Controlling Wheelchair.wmvStroke Patient - Controlling Wheelchair.wmv

11 11 Acknowledgements Cyberkinetics, Inc. Dr. John Donoghue Dr. Leigh Hochberg Mike Fritz Almut Branner Abe Caplan Ammar Shaikhouni Oystein Johnsen (Eagle)


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