Brain-Computer Interaction and Silent Speech Recognition on Decentralized Messaging Applications

Abstract

Peer-to-peer communication has increasingly gained prevalence in people’s daily lives, with its widespread adoption being catalysed by technological advances. Although there have been strides for the inclusion of disabled individuals to ease communication between peers, people who suffer hand/arm impairments have scarce support in regular mainstream applications to efficiently communicate privately with other individuals. Additionally, as centralized systems have come into scrutiny regarding privacy and security, development of alternative, decentralized solutions has increased, a movement pioneered by Bitcoin that culminated on the blockchain technology and its variants. Within the inclusivity paradigm, this paper aims to showcase an alternative on human-computer interaction with support for the aforementioned individuals, through the use of an electroencephalography headset and electromyography surface electrodes, for application navigation and text input purposes respectively. Users of the application are inserted in a decentralized system that is designed for secure communication and exchange of data between peers that are both resilient to tampering attacks and central points of failure, with no long-term restrictions regarding scalability prospects. Therefore, being composed of a silent speech and brain-computer interface, users can communicate with other peers, regardless of disability status, with no physical contact with the device. Users utilize a specific user interface design that supports such interaction, doing so securely on a decentralized network that is based on a distributed hash table for better lookup, insert and deletion of data performance. This project is still in early stages of development, having successfully been developed a functional prototype on a closed, testing environment.