✳flâneur — a map of the web's best reading

High-performance brain-to-text communication via imagined handwriting | bioRxiv

biorxiv.org · 10,893 words · saved by 1 readers

Brain-computer interfaces (BCIs) can restore communication to people who have lost the ability to move or speak. To date, a major focus of BCI research has been on restoring gross motor skills, such as reaching and grasping[1][1]–[5][2] or point-and-click typing with a 2D computer cursor[6][3],[7][4]. However, rapid sequences of highly dexterous behaviors, such as handwriting or touch typing, might enable faster communication rates. Here, we demonstrate an intracortical BCI that can decode imagined handwriting movements from neural activity in motor cortex and translate it to text in real-time, using a novel recurrent neural network decoding approach. With this BCI, our study participant (whose hand was paralyzed) achieved typing speeds that exceed those of any other BCI yet reported: 90 characters per minute at >99% accuracy with a general-purpose autocorrect. These speeds are comparable to able-bodied smartphone typing speeds in our participant’s age group (115 characters per minute)[8][5] and significantly close the gap between BCI-enabled typing and able-bodied typing rates. Finally, new theoretical considerations explain why temporally complex movements, such as handwriting, may be fundamentally easier to decode than point-to-point movements. Our results open a new approach for BCIs and demonstrate the feasibility of accurately decoding rapid, dexterous movements years after paralysis. ### Competing Interest Statement The MGH Translational Research Center has a clinical research support agreement with Neuralink, Paradromics, and Synchron, for which L.R.H. provides consultative input. JMH is a consultant for Neuralink Corp and Proteus Biomedical, and serves on the Medical Advisory Board of Enspire DBS. KVS consults for Neuralink Corp. and CTRL-Labs Inc. (part of Facebook Reality Labs) and is on the scientific advisory boards of MIND-X Inc., Inscopix Inc., and Heal Inc. All other authors have no competing interests. [1]: #ref-1 [2]: #ref-5 [3]: #ref-6 [4]: #ref-7 [5]: #ref-8

High-performance brain-to-text communication via imagined handwriting | bioRxiv Skip to main content New Results High-performance brain-to-text communication via imagined handwriting View ORCID Profile Francis R. Willett , View ORCID Profile Donald T. Avansino , View ORCID Profile Leigh R. Hochberg , View ORCID Profile Jaimie M. Henderson , View ORCID Profile Krishna V. Shenoy doi: https://doi.org/10.1101/2020.07.01.183384 Francis R. Willett 1 Howard Hughes Medical Institute at Stanford University , Stanford, CA, USA 2 Department of Neurosurgery, Stanford University , Stanford, CA, USA 3 Depar

Explore this link on the map →

related reading