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EE 290P Project Proposal: Next-Generation Decoding Algorithms for BMI Systems

EE 290P Project Proposal: Next-Generation Decoding Algorithms for BMI Systems. Siddharth Dangi Suraj Gowda Paul Johnson. Preliminary work: Adaptive Kalman Filter. Dynamics of model. Variables. Kinematic state at time t. Firing rates at time t. Gaussian noise variables. State matrix.

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EE 290P Project Proposal: Next-Generation Decoding Algorithms for BMI Systems

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  1. EE 290P Project Proposal:Next-Generation Decoding Algorithms for BMI Systems Siddharth Dangi SurajGowda Paul Johnson

  2. Preliminary work:Adaptive Kalman Filter • Dynamics of model • Variables Kinematic state at time t Firing rates at time t Gaussian noise variables State matrix Observation matrix

  3. Preliminary work:Adaptive Kalman Filter • Observation matrix “C” y estimated as: • Want to be able to adjust C over time • Why? • Implanted electrodes will shift, leading to changes in statistics of recorded signals

  4. Preliminary work:Adaptive Kalman Filter • Current paradigm: • Collect data offline, get initial estimate of C • Collect data online, re-estimate C • Repeat step 2 • Issues • Requires storing/retrieving data in large matrices • Repeating step 2 many times for optimal estimate • How to just “tweak” C?

  5. Preliminary work:Adaptive Kalman Filter • Idea: update C w/ stochastic gradient descent • Gradient descent: • Stochastic version:

  6. Preliminary work:Adaptive Kalman Filter • Initial results

  7. Benchmarking • Two relevant performance measures • Training time • Percentage of successful trials • We will tackle the measures independently • Faster training time for closed-loop reaching. • More accurate results for arbitrary reaches

  8. Intelligent Decoder Training • Hypothesis: linear combinations of neural firing rates are suboptimal decoding

  9. Mixture Kalman Filtering

  10. Neural State Space Modeling • Preliminary work: firing rates signals can be treated as state space trajectories (behavior-driven) • Find state space model showing only behavior • Correlate control trajectories for different limbs

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