A novel method for achieving high accuracy typing on a virtual keyboard using an intracortical Brain Computer Interface.

A novel method for achieving high accuracy typing on a virtual keyboard using an intracortical Brain Computer Interface

Overview

From texting on a device to pressing buttons on appliances, finger motions are utilized to communicate and interact with devices in almost all aspects of life. Individuals with severe motor impairment, however, often lack complete control of their hands and/or fingers, causing these “simple” tasks to be impossible. Commercial speech-to-text products and eye tracking devices can be used to facilitate communication in these populations. However, there are still individuals that cannot utilize these technologies, like those suffering from advanced cases of Amyotrophic Lateral Sclerosis (ALS). In these cases, brain computer interfaces (BCIs) can be leveraged to improve assistive communication and interaction. BCIs are systems that provide communication between human beings and machines by directly engaging a person’s nervous system, essentially bypassing damaged neural pathways to allow an individual to directly control assistive devices with their thoughts. Yet, current BCI systems are often slow and imprecise when individuals try to communicate and/or select elements from groups. The disclosed technology provides a solution for fast, accurate communication for individuals using a BCI through the development of a virtual keyboard. Through this novel method, a fluent and efficient means of text-based communication for individuals with severe motor or communication impairments is established. 

Market Opportunity

The global BCI market is estimated at >$2 billion, having life-changing applications for patients with motor impairment (i.e. from stroke or spinal cord injury), communication disabilities and prosthetic limbs. Although current BCI systems utilize speech-to-text and eye tracking algorithms, these methods can be slow and inaccurate. More importantly, individuals with severe motor impairment and/or degenerative diseases cannot utilize these technologies as in many cases speech is impossible and/or the ability to use eye tracking technology degrades over time. In this way, the disclosed technology addresses a major gap in current BCI systems, with the potential to expand in applications involving the creation of inputs for chat based, text-to-speech and word processing. 

Innovation and Meaningful Advantages

The proposed technology is a virtual keyboard integrated with BCI systems. The virtual keyboard contains multiple rows, with each row holding 10 keys of characters (letters and numbers). Each of the 10 keys per row maps to a different finger or thumb. Users will be able to access keys by imagining pressing each finger and different rows by an additional hand or finger gesture (i.e. wrist up). In this way, the disclosed technology will provide assistive communication for individuals with severe motor impairment, overcoming current issues by providing high accuracy, fast and fluent selection of elements. 

Collaboration Opportunity: We are interested in exploring research collaborations and licensing opportunities 

References

  • US Utility Application 18/947,556 
  • S. E. Lütschg Espinosa, T. Hosman, C. Nicolas, S. Allcroft, N. Herrick, L. R. Hochberg, C. E. Vargas-Irwin, J. D. Simeral. Toward assistive communication using a discrete ten-digit single hemisphere intracortical brain computer interface. Society for Neuroscience Conference 2023. 

 

Principal Investigator

Leigh Hochberg, PhD 

Professor of Engineering, Professor of Brain Science

Brown University

Leigh_Hochberg@brown.edu 

https://vivo.brown.edu/display/lhochber

Contact

Melissa Simon, PhD

Director of Business Development

Brown Technology Innovations 

melissa_j_simon@brown.edu

Brown Tech ID 3371J

Patent Information:
For Information, Contact:
Brown Technology Innovations
350 Eddy Street - Box 1949
Providence, RI 02903
tech-innovations@brown.edu
401-863-7499
Inventors:
Leigh Hochberg
John Simeral
Stefan Lütschg Espinosa
Carlos Vargas-Irwin
Natalie Herrick
David Rosler
Thomas Hosman
Keywords:
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