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.

In recent years, technologies used for augmentative and alternative communication (AAC) have seen increasing development and availability. As a result, more and more autistic people are using AAC. With the increased use of AAC by autistic people, research on autism and AAC has also increased. However, the vast majority of this research focuses on nonspeaking autistic children. AAC use by autistic adults and by speaking autistic people has received limited academic attention. Speaking autistic adults often use AAC and many have publicly shared information about their strategies and experiences. In this article, we provide an overview of the speech differences autistic adults choose to support through AAC, including varying difficulties with speech depending on environment and content. We also discuss the technologies and strategies adopted by autistic adults, including free or low-cost tools that are not specific to AAC, mobile technologies, and signed languages or gestures. We explore barriers to AAC use, including a lack of awareness of relevant options, misconceptions about who AAC supports are for, and the cost of dedicated AAC applications or devices. We then provide suggestions for autistic adults, people supporting autistic adults, and researchers. Overall communication—rather than speech—should be prioritized. Mainstream communication technologies can support communication for autistic adults and a variety of tools can support communication across contexts. Further research into the use and effectiveness of AAC for autistic adults is needed, as is research on barriers to AAC use. Lay Summary What is augmentative and alternative communication? Augmentative and alternative communication (AAC) describes the ways people communicate without, or in addition to, speech. What do we know about AAC for autistic adults who can speak? Research on AAC and autism has focused on nonspeaking children. However, autistic adults who use AAC sometimes tell each other about AAC. This community knowledge includes reasons AAC is important, useful AAC strategies, and barriers to AAC use. This article talks about autistic community knowledge about AAC and then makes suggestions. Why is AAC important for autistic adults who can speak? Autistic adults, including those who talk, may not always be able to meet all their communication needs with speech alone. Autistic people who use speech may experience intermittent, unreliable, and/or insufficient speech. What AAC strategies do speaking autistic adults use? The three main ways that autistic adults report on using AAC include: (1) Free or low-cost tools that are not specific to AAC (e.g., online chat rooms, text messaging applications, or handwriting). (2) Mobile applications designed for communication support. (3) Signed languages such as American Sign Language. What are some common barriers to AAC use for speaking autistic adults? Several barriers may prevent AAC use. These include the following: Knowledge of AAC options Attitudes about who AAC is useful for Beliefs that the use of AAC should be decreased if a person can speak Cost of AAC devices and applications. What are our recommendations to autistic adults who might use AAC and their supporters? Support autistics in defining their own communication needs, regardless of speech. Evaluate communication goals and match them with system features when making decisions about AAC. Prioritize all communication, not just speech. Explore a variety of options to support communication. Explore low- and no-cost options to support communication. What are some research questions that still need to be answered? What communication strategies do autistic adults see as effective? What AAC strategies are being used, in what environments, and by whom? What prevents effective AAC use? How can AAC specialists and autistic adults best collaborate to promote and evaluate AAC use? How can communication supports be designed to better meet the needs of autistic adults?

This is a literature review paper covering state-of-the-art sleep technologies to measure sleep and clinical sleep disorders. This paper addresses an interdisciplinary audience from a variety of subdomains in engineering and medicine. We reviewed 120 scientific papers, 15 commercial mobile apps, and 4 commercial devices. We selected the papers from scientific publishers including Institute of Electrical and Electronics Engineers (IEEE), Nature, Association for Computing Machinery (ACM), Proceedings of Machine Learning Research, Journal of Informatics in Health and Biomedicine, Plos One, PubMed, and Elsevier and Nature digital libraries. We used Google Scholar with keywords including “sleep monitoring”, “sleep monitoring technologies”, “non-contact sleep monitoring”, “mobile apps for sleep monitoring”, “AI in sleep technologies”, and “automated sleep staging.” The manuscript reviews sleep technologies, including sleep lab technologies such as polysomnography and consumer sleep technologies categorized as ambient room sensors, wearable sensors, bed sensors, mobile apps, and artificial intelligence. We primarily focused on validation and comparison studies of the reviewed technologies. The manuscript also provides an overview of several clinical datasets for sleep staging and taxonomizes the different learning methods. Finally, the manuscript offers our insights and recommendations about the application of the reviewed sleep technologies.

Objective: Amyotrophic lateral sclerosis (ALS) is a complex neurodegenerative disease that causes the progressive loss of voluntary muscle control. Recent studies have reported conflicting results on alterations in resting-state functional brain networks in ALS by adopting unimodal techniques that measure either electrophysiological or vascular-hemodynamic neural functions. However, no study to date has explored simultaneous electrical and vascular-hemodynamic changes in the resting-state brain in ALS. Using complementary multimodal electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) recording and analysis techniques, we explored the underlying multidimensional neural contributions to altered oscillations and functional connectivity in people with ALS. Methods: 10 ALS patients and 9 age-matched controls underwent multimodal EEG-fNIRS recording in the resting state. Resting-state functional connectivity (RSFC) and power spectra of both modalities in both groups were analyzed and compared statistically. Results: Increased fronto-parietal EEG connectivity in the alpha and beta bands and increased interhemispheric and right intra-hemispheric fNIRS connectivity in the frontal and prefrontal regions were observed in ALS. Frontal, central, and temporal theta and alpha EEG power decreased in ALS, as did parietal and occipital alpha EEG power, while frontal and parietal hemodynamic spectral power increased in ALS. Significance: These results suggest that electro-vascular disruption in neuronal networks extends to the extra-motor regions in ALS patients, which can ultimately introduce novel neural markers of ALS that can be exploited further as diagnostic and prognostic tools.