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Design of Smart Assistant Integrated Brain Computer Interface for Environmental Control by PALS
Conference paper   Peer reviewed

Design of Smart Assistant Integrated Brain Computer Interface for Environmental Control by PALS

Mohammad Sahal, Yashodha Ravichandran, Grace Feldman, Terry D Heiman-Patterson and Hasan Ayaz
Muscle & Nerve, v 66(S2), pp S33-S33
01 Nov 2022

Abstract

Clinical Neurology Life Sciences & Biomedicine Neurosciences Neurosciences & Neurology Science & Technology
Background: Brain computer interface (BCI) has emerged as an alternate communication and control option for people with neuro-muscular impairments, including Amyotrophic Lateral Sclerosis (ALS) [1]. P300 BCIs are the most common type that rely on oddball paradigm-based event related potentials that do not require training. P300 BCIs can be utilized for spelling, cursor movement, wheelchair/virtual navigation, and neuro-prostheses control [2][3]. In this project, we aimed to expand our earlier work [4] in developing Augmented Reality (AR) integrated P300 BCI to enable people with ALS (PALS) to select predefined environmental control commands. Methods: The P300 BCI system has x64 embedded single-board computer and runs OpenVibe for signal processing, stimuli, and command selection. A wireless battery-operated Bluetooth-enabled 8-channel dry-electrode EEG headset (Unicorn) is used for data collection. The system uses an AR head-mounted display for p300 stimulus presentation. The P300 matrix displays icons corresponding to commands that can be personalized by the user. Once the command is finalized, the BCI system uses gTTS, a text-to-speech library, to convert the command to an audio file which triggers the smart-assistant and relays the command to smart assistant verbally. Results: The proposed system has been implemented as a proof of concept and tested in the lab. It has shown potential with initial testing allowing environmental and entertainment control in lab settings. Further systematic testing will be done with PALS in their homes for real-world applications. Discussion: Integration of text-to-speech in a mobile P300 BCI interface advances assistive technology to improve the quality of life of PALS. The overall system is smart assistant brand agnostic. The wake word can be changed so this BCI may operate different smart assistants such as Amazon Alexa, Apple Siri, Google Assistant etc.

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