Nationwide survey of 780 Japanese patients with amyotrophic lateral sclerosis: their status and expectations from brain–machine interfaces

Kageyama, Yu; He, Xin; Shimokawa, Toshio; Sawada, Jinichi; Yanagisawa, Takufumi; Morris, Shayne; Sakura, Osamu; Kishima, Haruhiko; Mochizuki, Hideki; Yoshimine, Toshiki; Hirata, Masayuki

doi:10.1007/s00415-020-09903-3

Cited by 13 publications

(4 citation statements)

References 35 publications

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“…Despite the positive reports about eye-gaze devices, an important subset of people with late-stage ALS have difficulty using this technology [3][4][5] and about 10-17% of PALS cannot communicate at all [5,6]. The problems that impair or prevent the use of eye-gaze devices include difficulty maintaining stable head position [4], pupil dilation due to Baclofen use [61], and progressive oculomotor impairment and eye-gaze fatigue [4,5].…”

Section: Communication In Alsmentioning

confidence: 99%

“…A central theme in the management of ALS is helping individuals address the loss of the ability to communicate verbally or in writing, related to the progressive motor impairment and the use of tracheostomy invasive ventilation (TIV). Conventional assistive communication technologies rely on some level of residual and intentional muscle movement for control and thus do not represent an adequate solution for all people with ALS (PALS) in all disease stages and all circumstances [3][4][5][6]. Brain-computer interface (BCI) technology is a novel, muscle-independent method to control computers and communication software, using brain signals.…”

Section: Introductionmentioning

confidence: 99%

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Towards clinical application of implantable brain–computer interfaces for people with late-stage ALS: medical and ethical considerations

et al. 2022

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Individuals with amyotrophic lateral sclerosis (ALS) frequently develop speech and communication problems in the course of their disease. Currently available augmentative and alternative communication technologies do not present a solution for many people with advanced ALS, because these devices depend on residual and reliable motor activity. Brain–computer interfaces (BCIs) use neural signals for computer control and may allow people with late-stage ALS to communicate even when conventional technology falls short. Recent years have witnessed fast progression in the development and validation of implanted BCIs, which place neural signal recording electrodes in or on the cortex. Eventual widespread clinical application of implanted BCIs as an assistive communication technology for people with ALS will have significant consequences for their daily life, as well as for the clinical management of the disease, among others because of the potential interaction between the BCI and other procedures people with ALS undergo, such as tracheostomy. This article aims to facilitate responsible real-world implementation of implanted BCIs. We review the state of the art of research on implanted BCIs for communication, as well as the medical and ethical implications of the clinical application of this technology. We conclude that the contribution of all BCI stakeholders, including clinicians of the various ALS-related disciplines, will be needed to develop procedures for, and shape the process of, the responsible clinical application of implanted BCIs.

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Section: Communication In Alsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Towards clinical application of implantable brain–computer interfaces for people with late-stage ALS: medical and ethical considerations

et al. 2022

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“…16 LIS is typically linked to events that cause pontine damage (eg, stroke or injury), but also demyelinating and neurogenerative diseases (eg, ALS, central pontine myelinolysis) may lead to this condition. [17][18][19][20][21] A communication-BCI may provide a solution for the substantial portion of people with LIS for whom conventional, muscle-controlled, assistive communication technology, such as eye-gaze devices, falls short, [22][23][24][25] because of difficulties keeping the head still, 23 pupil dilation 26 or other side effects of medication, progressive oculomotor impairment, 24 and/or eye gaze fatigue. 23 The interindividual variability in user preference regarding the various practical and functional characteristics of communication-BCIs that are based on non-invasive and implanted electrodes, [27][28][29] underline the importance of the continued development and validation of both approaches.…”

Section: Target Population Of Implanted Communication-bcismentioning

confidence: 99%

Methodological Recommendations for Studies on the Daily Life Implementation of Implantable Communication-Brain–Computer Interfaces for Individuals With Locked-in Syndrome

Vansteensel

Branco

Leinders

et al. 2022

Neurorehabil Neural Repair

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Implantable brain–computer interfaces (BCIs) promise to be a viable means to restore communication in individuals with locked-in syndrome (LIS). In 2016, we presented the world-first fully implantable BCI system that uses subdural electrocorticography electrodes to record brain signals and a subcutaneous amplifier to transmit the signals to the outside world, and that enabled an individual with LIS to communicate via a tablet computer by selecting icons in spelling software. For future clinical implementation of implantable communication-BCIs, however, much work is still needed, for example, to validate these systems in daily life settings with more participants, and to improve the speed of communication. We believe the design and execution of future studies on these and other topics may benefit from the experience we have gained. Therefore, based on relevant literature and our own experiences, we here provide an overview of procedures, as well as recommendations, for recruitment, screening, inclusion, imaging, hospital admission, implantation, training, and support of participants with LIS, for studies on daily life implementation of implantable communication-BCIs. With this article, we not only aim to inform the BCI community about important topics of concern, but also hope to contribute to improved methodological standardization of implantable BCI research.

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“…Recently, a combination of deep learning and natural language processing (NLP) significantly improved the speed and accuracy of text generated using the iEEG of paralyzed patients [6,7]. The practical speed and accuracy of the communication make invasive BCIs indispensable to patients despite the risks inherent to the invasive nature of the procedures [8].…”

Section: Introductionmentioning

confidence: 99%

Text and image generation from intracranial electroencephalography using an embedding space for text and images

Ikegawa,

Fukuma,

Sugano

et al. 2024

J. Neural Eng.

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Objective:Invasive brain-computer interfaces (BCIs) are promising communication devices for severely paralyzed patients. Recent advances in intracranial electroencephalography (iEEG) coupled with natural language processing have enhanced communication speed and accuracy. It should be noted that such a speech BCI uses signals from the motor cortex. However, BCIs based on motor cortical activities may experience signal deterioration in users with motor cortical degenerative diseases such as amyotrophic lateral sclerosis (ALS). An alternative approach to using iEEG of the motor cortex is necessary to support patients with such conditions.Approach:In this study, a multimodal embedding of text and images was used to decode visual semantic information from iEEG signals of the visual cortex to generate text and images. We used contrastive language-image pretraining (CLIP) embedding to represent images presented to 17 patients implanted with electrodes in the occipital and temporal cortexes. A CLIP image vector was inferred from the high-γ power of the iEEG signals recorded while viewing the images.Main results:Text was generated by CLIPCAP from the inferred CLIP vector with better-than-chance accuracy. Then, an image was created from the generated text using StableDiffusion with significant accuracy.Significance:The text and images generated from iEEG through the CLIP embedding vector can be used for improved communication.

show abstract

Nationwide survey of 780 Japanese patients with amyotrophic lateral sclerosis: their status and expectations from brain–machine interfaces

Cited by 13 publications

References 35 publications

Towards clinical application of implantable brain–computer interfaces for people with late-stage ALS: medical and ethical considerations

Towards clinical application of implantable brain–computer interfaces for people with late-stage ALS: medical and ethical considerations

Methodological Recommendations for Studies on the Daily Life Implementation of Implantable Communication-Brain–Computer Interfaces for Individuals With Locked-in Syndrome

Text and image generation from intracranial electroencephalography using an embedding space for text and images

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