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Enhancing Communication for People in Late-Stage ALS Using an fNIRS-Based BCI System

Seyyed Bahram Borgheai, John McLinden, Alyssa Hillary Zisk, Sarah Ismail Hosni, Roohollah Jafari Deligani, Mohammadreza Abtahi, Kunal Mankodiya, Yalda Shahriari

2020IEEE Transactions on Neural Systems and Rehabilitation Engineering76 citationsDOIOpen Access PDF

Abstract

OBJECTIVE: Brain-computer interface (BCI) based communication remains a challenge for people with later-stage amyotrophic lateral sclerosis (ALS) who lose all voluntary muscle control. Although recent studies have demonstrated the feasibility of functional near-infrared spectroscopy (fNIRS) to successfully control BCIs primarily for healthy cohorts, these systems are yet inefficient for people with severe motor disabilities like ALS. In this study, we developed a new fNIRS-based BCI system in concert with a single-trial Visuo-Mental (VM) paradigm to investigate the feasibility of enhanced communication for ALS patients, particularly those in the later stages of the disease. METHODS: In the first part of the study, we recorded data from six ALS patients using our proposed protocol (fNIRS-VM) and compared the results with the conventional electroencephalography (EEG)-based multi-trial P3Speller (P3S). In the second part, we recorded longitudinal data from one patient in the late locked-in state (LIS) who had fully lost eye-gaze control. Using statistical parametric mapping (SPM) and correlation analysis, the optimal channels and hemodynamic features were selected and used in linear discriminant analysis (LDA). RESULTS: Over all the subjects, we obtained an average accuracy of 81.3%±5.7% within comparatively short times (< 4 sec) in the fNIRS-VM protocol relative to an average accuracy of 74.0%±8.9% in the P3S, though not competitive in patients with no substantial visual problems. Our longitudinal analysis showed substantially superior accuracy using the proposed fNIRS-VM protocol (73.2%±2.0%) over the P3S (61.8%±1.5%). SIGNIFICANCE: Our findings indicate the potential efficacy of our proposed system for communication and control for late-stage ALS patients.

Topics & Concepts

Brain–computer interfaceComputer scienceStage (stratigraphy)Human–computer interactionPsychologyElectroencephalographyNeuroscienceGeologyPaleontologyEEG and Brain-Computer InterfacesOptical Imaging and Spectroscopy TechniquesGaze Tracking and Assistive Technology
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