Fabio Rizzoglio

High-density surface EMG grid enables non-invasive characterization of intrinsic hand muscles activity

This paper introduces a high-density surface EMG grid for non-invasive recording of intrinsic hand muscle activity, showing it closely matches intramuscular EMG with improved spatial selectivity.

Muscle-driven hand simulations emphasize the critical role of the extensor mechanism

The paper uses biomechanical simulations to study hand motion, finding that extensor muscle path modifications improve accuracy in tracking interphalangeal joints during American Sign Language gestures.

Consistent EMG encoding during reach and grasp by neurons in motor cortex

The paper shows that motor cortex neurons encode movement through a consistent muscle-based principle, explaining both reaching and grasping behaviors without distinct control strategies.

Unsupervised, piecewise linear decoding enables an accurate prediction of muscle activity in a multi-task brain computer interface

This paper develops an unsupervised piecewise linear decoder for multi-task brain-computer interfaces, showing it outperforms global decoders in EMG prediction.

A Generalist Intracortical Motor Decoder

The paper trains an autoregressive Transformer on neural spiking data to decode motor behavior, showing broad utility across tasks but highlighting limitations in scaling.

Few-shot Algorithms for Consistent Neural Decoding (FALCON) Benchmark

The paper introduces FALCON, a benchmark suite for evaluating robustness of iBCI decoders using standardized datasets and evaluation metrics.

Monkey-to-human transfer of brain computer interface decoders

This paper transfers brain-computer interface decoders from monkeys to humans, showing that motor-related neural representations are consistent across species and reducing the need for extensive data.

Using adversarial networks to extend brain computer interface decoding accuracy over time

This paper improves brain-computer interface decoding accuracy over time using Cycle-GAN and ADAN methods, outperforming linear methods with minimal data requirements.