Peter Bradley Shull

This paper uses self-supervised learning to improve accuracy and reduce data requirements for estimating ground reaction forces from IMU data.

This paper demonstrates that synthetic EMG signals generated via adversarial style transfer can effectively attack biometric identification models, achieving high success rates in confusing and manipulating them.