<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Borgheai, Seyyed Bahram</style></author><author><style face="normal" font="default" size="100%">McLinden, John</style></author><author><style face="normal" font="default" size="100%">Zisk, Alyssa Hillary</style></author><author><style face="normal" font="default" size="100%">Hosni, Sarah Ismail</style></author><author><style face="normal" font="default" size="100%">Deligani, Roohollah Jafari</style></author><author><style face="normal" font="default" size="100%">Abtahi, Mohammadreza</style></author><author><style face="normal" font="default" size="100%">Mankodiya, Kunal</style></author><author><style face="normal" font="default" size="100%">Shahriari, Yalda</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Enhancing Communication for People in Late-Stage ALS Using an fNIRS-Based BCI System.</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE Trans Neural Syst Rehabil Eng</style></secondary-title><alt-title><style face="normal" font="default" size="100%">IEEE Trans Neural Syst Rehabil Eng</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amyotrophic Lateral Sclerosis</style></keyword><keyword><style  face="normal" font="default" size="100%">brain-computer interfaces</style></keyword><keyword><style  face="normal" font="default" size="100%">Communication</style></keyword><keyword><style  face="normal" font="default" size="100%">Electroencephalography</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Spectroscopy, Near-Infrared</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">05/2020</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">28</style></volume><pages><style face="normal" font="default" size="100%">1198-1207</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;OBJECTIVE: &lt;/b&gt;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.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;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).&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;Over all the subjects, we obtained an average accuracy of 81.3%±5.7% within comparatively short times (&lt; 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%).&lt;/p&gt;&lt;p&gt;&lt;b&gt;SIGNIFICANCE: &lt;/b&gt;Our findings indicate the potential efficacy of our proposed system for communication and control for late-stage ALS patients.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue></record></records></xml>