Lahiru N. Wimalasena

Spinal interneuron population dynamics underlying flexible pattern generation

The paper uses artificial intelligence to analyze spinal interneuron activity and muscle output in cats, revealing how state space trajectories capture timing and magnitude variations in muscle activation across steps.

Stabilizing brain-computer interfaces through alignment of latent dynamics

This paper introduces NoMAD, a method that stabilizes brain-computer interfaces by aligning latent dynamics, achieving stable decoding without supervised recalibration over long periods.

Estimating muscle activation from EMG using deep learning-based dynamical systems models

This paper uses a deep learning model to estimate muscle activation from EMG signals, showing improved performance over traditional methods in predicting joint kinematics and force.