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Author Spotlight: Enhancing Neurorehabilitation Through EEG, Motor Imagery, and Virtual Reality

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Brain-Computer Interface (BCI) Control of a Virtual Assistant in a Smartphone to Manage Messaging Applications.

Francisco Velasco-Álvarez¹, Álvaro Fernández-Rodríguez¹, Francisco-Javier Vizcaíno-Martín¹

¹Departamento de Tecnología Electrónica, Universidad de Málaga, 29071 Málaga, Spain.

Sensors (Basel, Switzerland)

|June 2, 2021

Summary

This summary is machine-generated.

This study introduces a brain-computer interface (BCI) system enabling smartphone messaging for individuals with motor disabilities. The BCI uses brain signals for communication control, offering a viable assistive technology solution.

Keywords:

P300 Telegram WhatsApp assistive technology brain–computer interface (BCI)e-mail messaging applications short message service (SMS)

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Area of Science:

Neuroscience
Assistive Technology
Human-Computer Interaction

Background:

Motor disabilities significantly impair communication, leading to negative psychological consequences for patients.
Existing assistive technologies may not fully restore communication capabilities for severely affected individuals.
Brain-computer interfaces (BCI) offer a potential solution by bypassing the need for muscular control.

Purpose of the Study:

To present a novel BCI system designed for controlling mainstream smartphone messaging applications.
To enable communication restoration for individuals with severe motor impairments.
To evaluate the system's viability and performance in practical communication tasks.

Main Methods:

The BCI system utilizes the P300 row-column paradigm (RCP) for user command selection and character spelling.
It integrates with a smartphone's virtual assistant to interpret synthesized voice commands for controlling messaging apps (WhatsApp, Telegram, email, SMS).
The system was tested with 15 healthy volunteers performing communication tasks.

Main Results:

Most participants successfully accomplished communication tasks, including sending free-text emails.
The system demonstrated effective control over multiple messaging applications.
Online performance metrics and subjective feedback indicated the system's viability.

Conclusions:

The developed BCI system shows promise for restoring communication skills in severely motor-disabled individuals.
The integration of BCI with smartphone virtual assistants offers a practical approach to assistive communication.
Further research and development can enhance the capabilities and accessibility of BCI technology.