Independent home use of a brain-computer interface by people with amyotrophic lateral sclerosis

Concerns in the Blurred Divisions between Medical and Consumer Neurotechnology

Neurotechnology has traditionally been central to the diagnosis and treatment of neurological disorders. While these devices have initially been utilized in clinical and research settings, recent advancements in neurotechnology have yielded devices that are more portable, user-friendly, and less expensive. These improvements allow laypeople to monitor their brain waves and interface their brains with external devices. Such improvements have led to the rise of wearable neurotechnology that is marketed to the consumer. While many of the consumer devices are marketed for innocuous applications, such as use in video games, there is potential for them to be repurposed for medical use. How do we manage neurotechnologies that skirt the line between medical and consumer applications and what can be done to ensure consumer safety? Here, we characterize neurotechnology based on medical and consumer applications and summarize currently marketed uses of consumer-grade wearable headsets. We lay out concerns that may arise due to the similar claims associated with both medical and consumer devices, the possibility of consumer devices being repurposed for medical uses, and the potential for medical uses of neurotechnology to influence commercial markets related to employment and self-enhancement.

EEG power spectral density in locked-in and completely locked-in state patients: a longitudinal study

Persons with their eye closed and without any means of communication is said to be in a completely locked-in state (CLIS) while when they could still open their eyes actively or passively and have some means of communication are said to be in locked-in state (LIS). Two patients in CLIS without any means of communication, and one patient in the transition from LIS to CLIS with means of communication, who have Amyotrophic Lateral Sclerosis were followed at a regular interval for more than 1 year. During each visit, resting-state EEG was recorded before the brain-computer interface (BCI) based communication sessions. The resting-state EEG of the patients was analyzed to elucidate the evolution of their EEG spectrum over time with the disease's progression to provide future BCI-research with the relevant information to classify changes in EEG evolution. Comparison of power spectral density (PSD) of these patients revealed a significant difference in the PSD's of patients in CLIS without any means of communication and the patient in the transition from LIS to CLIS with means of communication. The EEG of patients without any means of communication is devoid of alpha, beta, and higher frequencies than the patient in transition who still had means of communication. The results show that the change in the EEG frequency spectrum may serve as an indicator of the communication ability of such patients.

High-performance brain-to-text communication via handwriting

Brain-computer interfaces (BCIs) can restore communication to people who have lost the ability to move or speak. So far, a major focus of BCI research has been on restoring gross motor skills, such as reaching and grasping^1-5 or point-and-click typing with a computer cursor^6,7. However, rapid sequences of highly dexterous behaviours, such as handwriting or touch typing, might enable faster rates of communication. Here we developed an intracortical BCI that decodes attempted handwriting movements from neural activity in the motor cortex and translates it to text in real time, using a recurrent neural network decoding approach. With this BCI, our study participant, whose hand was paralysed from spinal cord injury, achieved typing speeds of 90 characters per minute with 94.1% raw accuracy online, and greater than 99% accuracy offline with a general-purpose autocorrect. To our knowledge, these typing speeds exceed those reported for any other BCI, and are comparable to typical smartphone typing speeds of individuals in the age group of our participant (115 characters per minute)⁸. Finally, theoretical considerations explain why temporally complex movements, such as handwriting, may be fundamentally easier to decode than point-to-point movements. Our results open a new approach for BCIs and demonstrate the feasibility of accurately decoding rapid, dexterous movements years after paralysis.

Invariability of EEG error-related potentials during continuous feedback protocols elicited by erroneous actions at predicted or unpredicted states

Objective.When humans perceive an erroneous action, an EEG error-related potential (ErrP) is elicited as a neural response. ErrPs have been largely investigated in discrete feedback protocols, where actions are executed at discrete steps, to enable seamless brain-computer interaction. However, there are only a few studies that investigate ErrPs in continuous feedback protocols. The objective of the present study is to better understand the differences between two types of ErrPs elicited during continuous feedback protocols, where errors may occur either at predicted or unpredicted states. We hypothesize that ErrPs of the unpredicted state is associated with longer latency as it requires higher cognitive workload to evaluate actions compared to the predicted states.Approach.Participants monitored the trajectory of an autonomous cursor that occasionally made erroneous actions on its way to the target in two conditions, namely, predicted or unpredicted states. After characterizing the ErrP waveform elicited by erroneous actions in the two conditions, we performed single-trial decoding of ErrPs in both synchronous (i.e. time-locked to the onset of the erroneous action) and asynchronous manner. Furthermore, we explored the possibility to transfer decoders built with data of one of the conditions to the other condition.Main results.As hypothesized, erroneous actions at unpredicted states gave rise to ErrPs with higher latency than erroneous actions at predicted states, a correlate of higher cognitive effort in the former condition. Moreover, ErrP decoders trained in a given condition successfully transferred to the other condition with a slight loss of classification performance. This was the case for synchronous as well as asynchronous ErrP decoding, showing the invariability of ErrPs across conditions.Significance.These results advance the characterization of ErrPs during continuous feedback protocols, enlarging the potential use of ErrPs during natural operation of brain-controlled devices as it is not necessary to have different decoders for each kind of erroneous conditions.

Habituation of P300 in the Use of P300-based Brain-Computer Interface Spellers: Individuals With Amyotrophic Lateral Sclerosis Versus Age-Matched Controls

The P300-based brain-computer interface speller can provide motor independent communication to individuals with amyotrophic lateral sclerosis (ALS), a progressive neurodegenerative disorder that affects the motor system. P300 amplitude stability is critical for operation of the P300 speller. The P300 has good long-term stability, but to our knowledge, short-term habituation in the P300 speller has not been studied. In the current study, 15 participants: 8 ALS patients and 7 age-matched healthy volunteers (HVs), used 2 versions of P300 spellers, Face speller and Flash speller, each for 30 minutes. The ALS group performed as well as the HVs in both spellers and HVs did better with the Face speller than Flash speller while the ALS group performed equally well in both spellers. Neither intra-run P300 habituation nor inter-run P300 habituation was found. The P300 speller could be a reliable communication device for individuals with ALS.

Neurotechnology ethics and relational agency

Novel neurotechnologies, like deep brain stimulation and brain-computer interface, offer great hope for treating, curing, and preventing disease, but raise important questions about effects these devices may have on human identity, authenticity, and autonomy. After briefly assessing recent narrative work in these areas, we show that agency is a phenomenon key to all three goods and highlight the ways in which neural devices can help to draw attention to the relational nature of our agency. Drawing on insights from disability theory, we argue that neural devices provide a kind of agential assistance, similar to that provided by caregivers, family, and others. As such, users and devices participate in a kind of co-agency. We conclude by suggesting the need for developing relational agency-competencies-skills for reflecting on the influence of devices on agency, for adapting to novel circumstances ushered in by devices, and for incorporating the feedback of loved ones and others about device effects on agency.

Neuroprosthetics in systems neuroscience and medicine

The impaired brain is often difficult to restore, owing to our limited knowledge of the complex nervous system. Accumulating knowledge in systems neuroscience, combined with the development of innovative technologies, may enable brain restoration in patients with nervous system disorders that are currently untreatable. The Neuroprosthetics in Systems Neuroscience and Medicine Collection provides a platform for interdisciplinary research in neuroprosthetics.

Plug-and-play control of a brain-computer interface through neural map stabilization

Brain-computer interfaces (BCIs) enable control of assistive devices in individuals with severe motor impairments. A limitation of BCIs that has hindered real-world adoption is poor long-term reliability and lengthy daily recalibration times. To develop methods that allow stable performance without recalibration, we used a 128-channel chronic electrocorticography (ECoG) implant in a paralyzed individual, which allowed stable monitoring of signals. We show that long-term closed-loop decoder adaptation, in which decoder weights are carried across sessions over multiple days, results in consolidation of a neural map and 'plug-and-play' control. In contrast, daily reinitialization led to degradation of performance with variable relearning. Consolidation also allowed the addition of control features over days, that is, long-term stacking of dimensions. Our results offer an approach for reliable, stable BCI control by leveraging the stability of ECoG interfaces and neural plasticity.

Brain-Computer Interfaces for Communication: Preferences of Individuals With Locked-in Syndrome

BACKGROUND

Brain-computer interfaces (BCIs) have been proposed as an assistive technology (AT) allowing people with locked-in syndrome (LIS) to use neural signals to communicate. To design a communication BCI (cBCI) that is fully accepted by the users, their opinion should be taken into consideration during the research and development process.

OBJECTIVE

We assessed the preferences of prospective cBCI users regarding (1) the applications they would like to control with a cBCI, (2) the mental strategies they would prefer to use to control the cBCI, and (3) when during their clinical trajectory they would like to be informed about AT and cBCIs. Furthermore, we investigated if individuals diagnosed with progressive and sudden onset (SO) disorders differ in their opinion.

METHODS

We interviewed 28 Dutch individuals with LIS during a 3-hour home visit using multiple-choice, ranking, and open questions. During the interview, participants were informed about BCIs and the possible mental strategies.

RESULTS

Participants rated (in)direct forms of communication, computer use, and environmental control as the most desired cBCI applications. In addition, active cBCI control strategies were preferred over reactive strategies. Furthermore, individuals with progressive and SO disorders preferred to be informed about AT and cBCIs at the moment they would need it.

CONCLUSIONS

We show that individuals diagnosed with progressive and SO disorders preferred, in general, the same applications, mental strategies, and time of information. By collecting the opinion of a large sample of individuals with LIS, this study provides valuable information to stakeholders in cBCI and other AT development.

On the way home: a BCI-FES hand therapy self-managed by sub-acute SCI participants and their caregivers: a usability study

BACKGROUND

Regaining hand function is the top priority for people with tetraplegia, however access to specialised therapy outwith clinics is limited. Here we present a system for hand therapy based on brain-computer interface (BCI) which uses a consumer grade electroencephalography (EEG) device combined with functional electrical stimulation (FES), and evaluate its usability among occupational therapists (OTs) and people with spinal cord injury (SCI) and their family members.

METHODS

Users: Eight people with sub-acute SCI (6 M, 2F, age 55.4 ± 15.6) and their caregivers (3 M, 5F, age 45.3 ± 14.3); four OTs (4F, age 42.3 ± 9.8). User Activity: Researchers trained OTs; OTs subsequently taught caregivers to set up the system for the people with SCI to perform hand therapy. Hand therapy consisted of attempted movement (AM) of one hand to lower the power of EEG sensory-motor rhythm in the 8-12 Hz band and thereby activate FES which induced wrist flexion and extension. Technology: Consumer grade wearable EEG, multichannel FES, custom made BCI application.

LOCATION

Research space within hospital. Evaluation: donning times, BCI accuracy, BCI and FES parameter repeatability, questionnaires, focus groups and interviews.

RESULTS

Effectiveness: The BCI accuracy was 70-90%. Efficiency: Median donning times decreased from 40.5 min for initial session to 27 min during last training session (N = 7), dropping to 14 min on the last self-managed session (N = 3). BCI and FES parameters were stable from session to session. Satisfaction: Mean satisfaction with the system among SCI users and caregivers was 3.68 ± 0.81 (max 5) as measured by QUEST questionnaire. Main facilitators for implementing BCI-FES technology were "seeing hand moving", "doing something useful for the loved ones", good level of computer literacy (people with SCI and caregivers), "active engagement in therapy" (OT), while main barriers were technical complexity of setup (all groups) and "lack of clinical evidence" (OT).

CONCLUSION

BCI-FES has potential to be used as at home hand therapy by people with SCI or stroke, provided it is easy to use and support is provided. Transfer of knowledge of operating BCI is possible from researchers to therapists to users and caregivers. Trial registration Registered with NHS GG&C on December 6th 2017; clinicaltrials.gov reference number NCT03257982, url: https://clinicaltrials.gov/ct2/show/NCT03257982 .

Closed-loop EEG study on visual recognition during driving

OBJECTIVE

In contrast to the classical visual BCI paradigms, which adhere to a rigid trial structure and restricted user behavior, EEG-based visual recognition decoding during our daily activities remains challenging. The objective of this study is to explore the feasibility of decoding the EEG signature of visual recognition in experimental conditions promoting our natural ocular behavior when interacting with our dynamic environment.

APPROACH

In our experiment, subjects visually search for a target object among suddenly appearing objects in the environment while driving a car-simulator. Given that subjects exhibit an unconstrained overt visual behavior, we based our study on eye fixation-related potentials (EFRP). We report on gaze behavior and single-trial EFRP decoding performance (fixations on visually similar target vs. non-target objects). In addition, we demonstrate the application of our approach in a closed-loop BCI setup.

MAIN RESULTS

To identify the target out of four symbol types along a road segment, the BCI system integrated decoding probabilities of multiple EFRP and achieved the average online accuracy of 0.37 ± 0.06 (12 subjects), statistically significantly above the chance level. Using the acquired data, we performed a comparative study of classification algorithms (discriminating target vs. non-target) and feature spaces in a simulated online scenario. The EEG approaches yielded similar moderate performances of at most 0.6 AUC, yet statistically significantly above the chance level. In addition, the gaze duration (dwell time) appears to be an additional informative feature in this context.

SIGNIFICANCE

These results show that visual recognition of sudden events can be decoded during active driving. Therefore, this study lays a foundation for assistive and recommender systems based on the driver's brain signals.

Nonspecific Visuospatial Imagery as a Novel Mental Task for Online EEG-Based BCI Control

Brain-computer interfaces (BCIs) can provide a means of communication to individuals with severe motor disorders, such as those presenting as locked-in. Many BCI paradigms rely on motor neural pathways, which are often impaired in these individuals. However, recent findings suggest that visuospatial function may remain intact. This study aimed to determine whether visuospatial imagery, a previously unexplored task, could be used to signify intent in an online electroencephalography (EEG)-based BCI. Eighteen typically developed participants imagined checkerboard arrow stimuli in four quadrants of the visual field in 5-s trials, while signals were collected using 16 dry electrodes over the visual cortex. In online blocks, participants received graded visual feedback based on their performance. An initial BCI pipeline (visuospatial imagery classifier I) attained a mean accuracy of [Formula: see text]% classifying rest against visuospatial imagery in online trials. This BCI pipeline was further improved using restriction to alpha band features (visuospatial imagery classifier II), resulting in a mean pseudo-online accuracy of [Formula: see text]%. Accuracies exceeded the threshold for practical BCIs in 12 participants. This study supports the use of visuospatial imagery as a real-time, binary EEG-BCI control paradigm.

TeleBCI: remote user training, monitoring, and communication with an evoked-potential brain-computer interface

Brain-computer interfaces (BCIs) are a movement-independent form of augmentative and alternative communication (AAC) for individuals with amyotrophic lateral sclerosis (ALS). The rare utilization of such devices in the homes of patients stems from a number of factors, one of which is the complexity of providing training and support for users. This paper describes the teleBCI interface used to train the patient and facilitator in the operation of a virtual keyboard using an evoked potential BCI. Fifteen patients with motor neuron disease and their communication partners were included in the study, participating from their homes while receiving remote support from the research team. Patient/caregiver teams completed 8 sessions each of P300 BCI training virtually with the researcher. As they participated in subsequent training sessions, participant teams required less help to complete physical, computer, and BCI-specific tasks associated with device use. A subset of users experienced improved performance over sessions, progressing to utilize the full functionality of the speller and communicate with a nurse partner over a telemedicine interface. Perceptions of device utility varied with accuracy of the BCI system. In the management of ALS, the integration of telemedicine provides new opportunities for care delivery, including how BCI-AAC are deployed and used.

New technologies and Amyotrophic Lateral Sclerosis - Which step forward rushed by the COVID-19 pandemic?

Amyotrophic Lateral Sclerosis (ALS) is a fast-progressive neurodegenerative disease leading to progressive physical immobility with usually normal or mild cognitive and/or behavioural involvement. Many patients are relatively young, instructed, sensitive to new technologies, and professionally active when developing the first symptoms. Older patients usually require more time, encouragement, reinforcement and a closer support but, nevertheless, selecting user-friendly devices, provided earlier in the course of the disease, and engaging motivated carers may overcome many technological barriers. ALS may be considered a model for neurodegenerative diseases to further develop and test new technologies. From multidisciplinary teleconsults to telemonitoring of the respiratory function, telemedicine has the potentiality to embrace other fields, including nutrition, physical mobility, and the interaction with the environment. Brain-computer interfaces and eye tracking expanded the field of augmentative and alternative communication in ALS but their potentialities go beyond communication, to cognition and robotics. Virtual reality and different forms of artificial intelligence present further interesting possibilities that deserve to be investigated. COVID-19 pandemic is an unprecedented opportunity to speed up the development and implementation of new technologies in clinical practice, improving the daily living of both ALS patients and carers. The present work reviews the current technologies for ALS patients already in place or being under evaluation with published publications, prompted by the COVID-19 pandemic.

"Re-identifying yourself": a qualitative study of veteran views on implantable BCI for mobility and communication in ALS

OBJECTIVES

Brain-computer interface (BCI) technology to assist with mobility and communication is an active area of research in amyotrophic lateral sclerosis (ALS). Implantable BCI offers promise for individuals with severe disease, such as locked-in syndrome, but also raises important ethical issues. We undertook in-depth qualitative interviews with ALS patients from a Veterans Administration hospital ALS multi-disciplinary clinic and explored their perspectives on issues of identity, privacy, enhancement, informed consent, and responsibility related to implantable BCI.

METHODS

Semi-structured interviews were conducted with sixteen (n = 16) individuals, and transcripts were analysed using a modified grounded theory approach.

RESULTS

Emergent themes included: (1) attitudes towards BCI were characterised by fear, hope, and hesitation about adoption of BCI technology; (2) analogies to other technologies were a useful tool in understanding and communicating opinions about ethical issues in BCI; (3) concerns about potentially socially stigmatising effects of BCI and the burden of adjustment to new therapeutic devices were important considerations to be weighed against the potential functional benefit of BCI use; (4) therapeutic decision-making in ALS often intimately involves loved ones; and (5) prospective decision-making about BCI was significantly affected by weighing the timing of the intervention with the progression of illness.

CONCLUSION

The interest in BCI and views on ethical issues raised by BCI is moderated by the experience of living with ALS. The findings from this study can help guide the development of implantable BCI technology for persons with ALS.Implications for rehabilitationLoved ones will play crucial roles in helping patients think through the possible benefits and burdens of getting a BCI device.Providers should consider how the ideal timing for getting an implantable BCI device will vary based on the priorities of persons with ALS and their disease stage.Concerns about social stigma, burden of adjustment, and the desire to maximise time left with loved ones may outweigh the potential functional benefits of BCI devices for some persons with ALS.

Indirect Control of an Autonomous Wheelchair Using SSVEP BCI

Having the capability to control a wheelchair using brain signals would be a major benefit to patients suffering from motor disabling diseases. However, one major challenge such systems are facing is the amount of input needed over time by the patient for control. Such a navigation control system results in a significant mental burden for the patient. The objective of this study is to develop a BCI system that requires a low number of inputs from a subject to operate. We propose an autonomous wheelchair that uses steady-state visual evoked potential based brain computer interfaces to achieve the objective. A dual mode system was implemented in this study to allow the autonomous wheelchair to work in both unknown and known environments. Robot operating system is used as the middleware in this study for the development of the algorithm to operate the wheelchair. The mental task for the subject using this wheelchair is reduced by relegating the responsibility of navigation control from the subject to the navigation software.

Human visual skills for brain-computer interface use: a tutorial

Background and objectives: Many brain-computer interfaces (BCIs) for people with severe disabilities present stimuli in the visual modality with little consideration of the visual skills required for successful use. The primary objective of this tutorial is to present researchers and clinical professionals with basic information about the visual skills needed for functional use of visual BCIs, and to offer modifications that would render BCI technology more accessible for persons with vision impairments.Methods: First, we provide a background on BCIs that rely on a visual interface. We then describe the visual skills required for BCI technologies that are used for augmentative and alternative communication (AAC), as well as common eye conditions or impairments that can impact the user's performance. We summarize screening tools that can be administered by the non-eye care professional in a research or clinical setting, as well as the role of the eye care professional. Finally, we explore potential BCI design modifications to compensate for identified functional impairments. Information was generated from literature review and the clinical experience of vision experts.Results and conclusions: This in-depth description culminates in foundational information about visual skills and functional visual impairments that affect the design and use of visual interfaces for BCI technologies. The visual interface is a critical component of successful BCI systems. We can determine a BCI system for potential users with visual impairments and design BCI visual interfaces based on sound anatomical and physiological visual clinical science.Implications for RehabilitationAs brain-computer interfaces (BCIs) become possible access methods for people with severe motor impairments, it is critical that clinicians have a basic knowledge of the visual skills necessary for use of visual BCI interfaces.Rehabilitation providers must have a knowledge of objectively gathering information regarding a potential BCI user's functional visual skills.Rehabilitation providers must understand how to modify BCI visual interfaces for the potential user with visual impairments.Rehabilitation scientists should understand the visual demands of BCIs as they develop and evaluate these new access methods.

Brain-computer interfaces for amyotrophic lateral sclerosis

A brain-computer interface (BCI) is a device that detects signals from the brain and transforms them into useful commands. Researchers have developed BCIs that utilize different kinds of brain signals. These different BCI systems have differing characteristics, such as the amount of training required and the degree to which they are or are not invasive. Much of the research on BCIs to date has involved healthy individuals and evaluation of classification algorithms. Some BCIs have been shown to have potential benefit for users with minimal muscular function as a result of amyotrophic lateral sclerosis. However, there are still several challenges that need to be successfully addressed before BCIs can be clinically useful.

Auditory Electrooculogram-based Communication System for ALS Patients in Transition from Locked-in to Complete Locked-in State

Patients in the transition from locked-in (i.e., a state of almost complete paralysis with voluntary eye movement control, eye blinks or twitches of face muscles, and preserved consciousness) to complete locked-in state (i.e., total paralysis including paralysis of eye-muscles and loss of gaze-fixation, combined with preserved consciousness) are left without any means of communication. An auditory communication system based on electrooculogram (EOG) was developed to enable such patients to communicate. Four amyotrophic lateral sclerosis patients in transition from locked-in state to completely locked-in state, with ALSFRS-R score of 0, unable to use eye trackers for communication, learned to use an auditory EOG-based communication system. The patients, with eye-movement amplitude between the range of ±200μV and ±40μV, were able to form complete sentences and communicate independently and freely, selecting letters from an auditory speller system. A follow-up of one year with one patient shows the feasibility of the proposed system in long-term use and the correlation between speller performance and eye-movement decay. The results of the auditory speller system have the potential to provide a means of communication to patient populations without gaze fixation ability and with low eye-movement amplitude range.

30+ years of P300 brain-computer interfaces

Brain-computer interfaces (BCIs) directly measure brain activity with no physical movement and translate the neural signals into messages. BCIs that employ the P300 event-related brain potential often have used the visual modality. The end user is presented with flashing stimuli that indicate selections for communication, control, or both. Counting each flash that corresponds to a specific target selection while ignoring other flashes will elicit P300s to only the target selection. P300 BCIs also have been implemented using auditory or tactile stimuli. P300 BCIs have been used with a variety of applications for severely disabled end users in their homes without frequent expert support. P300 BCI research and development has made substantial progress, but challenges remain before these tools can become practical devices for impaired patients and perhaps healthy people.

On Primitives in Motor Control

The concept of primitives has been used in motor control both as a theoretical construct and as a means of describing the results of experimental studies involving multiple moving elements. This concept is close to Bernstein’s notion of engrams and level of synergies. Performance primitives have been explored in spaces of peripheral variables but interpreted in terms of neural control primitives. Performance primitives reflect a variety of mechanisms ranging from body mechanics to spinal mechanisms and to supraspinal circuitry. This review suggests that primitives originate at the task level as preferred time functions of spatial referent coordinates or at mappings from higher level referent coordinates to lower level, frequently abundant, referent coordinate sets. Different patterns of performance primitives can emerge depending, in particular, on the external force field.

State-of-the-art non-invasive brain–computer interface for neural rehabilitation: A review

Brain–computer interface (BCI) is a novel communication method between brain and machine. It enables signals from the human brain to influence or control external devices. Currently, much research interest is focused on the BCI-based neural rehabilitation of patients with motor and cognitive diseases. Over the decades, BCI has become an alternative treatment for motor and cognitive rehabilitation. Previous studies demonstrated the usefulness of BCI intervention in restoring motor function and recovery of the damaged brain. Electroencephalogram (EEG)-based BCI intervention could cast light on the mechanisms underlying neuroplasticity during upper limb recovery by providing feedback to the damaged brain. BCI could act as a useful tool to aid patients with daily communication and basic movement in severe motor loss cases like amyotrophic lateral sclerosis (ALS). Furthermore, recent findings have reported the therapeutic efficacy of BCI in people suffering from other diseases with different levels of motor impairment such as spastic cerebral palsy, neuropathic pain, etc. Besides motor functional recovery, BCI also plays its role in improving the behavior of patients with cognitive diseases like attention-deficit/hyperactivity disorder (ADHD). The BCI-based neurofeedback training is focused on either reducing the ratio of theta and beta rhythm, or enabling the patients to regulate their own slow cortical potentials, and both have made progress in increasing attention and alertness. With summary of several clinical studies with strong evidence, we present cutting edge results from the clinical application of BCI in motor and cognitive diseases, including stroke, spinal cord injury, ALS, and ADHD.

Brain-computer interfaces: Definitions and principles

Throughout life, the central nervous system (CNS) interacts with the world and with the body by activating muscles and excreting hormones. In contrast, brain-computer interfaces (BCIs) quantify CNS activity and translate it into new artificial outputs that replace, restore, enhance, supplement, or improve the natural CNS outputs. BCIs thereby modify the interactions between the CNS and the environment. Unlike the natural CNS outputs that come from spinal and brainstem motoneurons, BCI outputs come from brain signals that represent activity in other CNS areas, such as the sensorimotor cortex. If BCIs are to be useful for important communication and control tasks in real life, the CNS must control these brain signals nearly as reliably and accurately as it controls spinal motoneurons. To do this, they might, for example, need to incorporate software that mimics the function of the subcortical and spinal mechanisms that participate in normal movement control. The realization of high reliability and accuracy is perhaps the most difficult and critical challenge now facing BCI research and development. The ongoing adaptive modifications that maintain effective natural CNS outputs take place primarily in the CNS. The adaptive modifications that maintain effective BCI outputs can also take place in the BCI. This means that the BCI operation depends on the effective collaboration of two adaptive controllers, the CNS and the BCI. Realization of this second adaptive controller, the BCI, and management of its interactions with concurrent adaptations in the CNS comprise another complex and critical challenge for BCI development. BCIs can use different kinds of brain signals recorded in different ways from different brain areas. Decisions about which signals recorded in which ways from which brain areas should be selected for which applications are empirical questions that can only be properly answered by experiments. BCIs, like other communication and control technologies, often face artifacts that contaminate or imitate their chosen signals. Noninvasive BCIs (e.g., EEG- or fNIRS-based) need to take special care to avoid interpreting nonbrain signals (e.g., cranial EMG) as brain signals. This typically requires comprehensive topographical and spectral evaluations. In theory, the outputs of BCIs can select a goal or control a process. In the future, the most effective BCIs will probably be those that combine goal selection and process control so as to distribute control between the BCI and the application in a fashion suited to the current action. Through such distribution, BCIs may most effectively imitate natural CNS operation. The primary measure of BCI development is the extent to which BCI systems benefit people with neuromuscular disorders. Thus, BCI clinical evaluation, validation, and dissemination is a key step. It is at the same time a complex and difficult process that depends on multidisciplinary collaboration and management of the demanding requirements of clinical studies. Twenty-five years ago, BCI research was an esoteric endeavor pursued in only a few isolated laboratories. It is now a steadily growing field that engages many hundreds of scientists, engineers, and clinicians throughout the world in an increasingly interconnected community that is addressing the key issues and pursuing the high potential of BCI technology.

Brain-computer interfaces for communication

Locked-in syndrome (LIS) is characterized by an inability to move or speak in the presence of intact cognition and can be caused by brainstem trauma or neuromuscular disease. Quality of life (QoL) in LIS is strongly impaired by the inability to communicate, which cannot always be remedied by traditional augmentative and alternative communication (AAC) solutions if residual muscle activity is insufficient to control the AAC device. Brain-computer interfaces (BCIs) may offer a solution by employing the person's neural signals instead of relying on muscle activity. Here, we review the latest communication BCI research using noninvasive signal acquisition approaches (electroencephalography, functional magnetic resonance imaging, functional near-infrared spectroscopy) and subdural and intracortical implanted electrodes, and we discuss current efforts to translate research knowledge into usable BCI-enabled communication solutions that aim to improve the QoL of individuals with LIS.

Self-health monitoring and wearable neurotechnologies

Brain-computer interfaces and wearable neurotechnologies are now used to measure real-time neural and physiologic signals from the human body and hold immense potential for advancements in medical diagnostics, prevention, and intervention. Given the future role that wearable neurotechnologies will likely serve in the health sector, a critical state-of-the-art assessment is necessary to gain a better understanding of their current strengths and limitations. In this chapter we present wearable electroencephalography systems that reflect groundbreaking innovations and improvements in real-time data collection and health monitoring. We focus on specifications reflecting technical advantages and disadvantages, discuss their use in fundamental and clinical research, their current applications, limitations, and future directions. While many methodological and ethical challenges remain, these systems host the potential to facilitate large-scale data collection far beyond the reach of traditional research laboratory settings.

Brain-computer interfaces and personhood: interdisciplinary deliberations on neural technology

OBJECTIVE

Scientists, engineers, and healthcare professionals are currently developing a variety of new devices under the category of brain-computer interfaces (BCIs). Current and future applications are both medical/assistive (e.g. for communication) and non-medical (e.g. for gaming). This array of possibilities has been met with both enthusiasm and ethical concern in various media, with no clear resolution of these conflicting sentiments.

APPROACH

To better understand how BCIs may either harm or help the user, and to investigate whether ethical guidance is required, a meeting entitled 'BCIs and Personhood: A Deliberative Workshop' was held in May 2018.

MAIN RESULTS

We argue that the hopes and fears associated with BCIs can be productively understood in terms of personhood, specifically the impact of BCIs on what it means to be a person and to be recognized as such by others.

SIGNIFICANCE

Our findings suggest that the development of neural technologies raises important questions about the concept of personhood and its role in society. Accordingly, we propose recommendations for BCI development and governance.

Behind the Scenes of Noninvasive Brain-Computer Interfaces: A Review of Electroencephalography Signals, How They Are Recorded, and Why They Matter

Purpose

Brain-computer interface (BCI) techniques may provide computer access for individuals with severe physical impairments. However, the relatively hidden nature of BCI control obscures how BCI systems work behind the scenes, making it difficult to understand how electroencephalography (EEG) records the BCI related brain signals, what brain signals are recorded by EEG, and why these signals are targeted for BCI control. Furthermore, in the field of speech-language-hearing, signals targeted for BCI application have been of primary interest to clinicians and researchers in the area of augmentative and alternative communication (AAC). However, signals utilized for BCI control reflect sensory, cognitive and motor processes, which are of interest to a range of related disciplines including speech science.

Method

This tutorial was developed by a multidisciplinary team emphasizing primary and secondary BCI-AAC related signals of interest to speech-language-hearing.

Results

An overview of BCI-AAC related signals are provided discussing 1) how BCI signals are recorded via EEG, 2) what signals are targeted for non-invasive BCI control, including the P300, sensorimotor rhythms, steady state evoked potentials, contingent negative variation, and the N400, and 3) why these signals are targeted. During tutorial creation, attention was given to help support EEG and BCI understanding for those without an engineering background.

Conclusion

Tutorials highlighting how BCI-AAC signals are elicited and recorded can help increase interest and familiarity with EEG and BCI techniques and provide a framework for understanding key principles behind BCI-AAC design and implementation.

An exploration of BCI performance variations in people with amyotrophic lateral sclerosis using longitudinal EEG data

OBJECTIVE

Brain-computer interface (BCI) technology enables people to use direct measures of brain activity for communication and control. The National Center for Adaptive Neurotechnologies and Helen Hayes Hospital are studying long-term independent home use of P300-based BCIs by people with amyotrophic lateral sclerosis (ALS). This BCI use takes place without technical oversight, and users can encounter substantial variation in their day-to-day BCI performance. The purpose of this study is to identify and evaluate features in the electroencephalogram (EEG) that correlate with successful BCI performance during home use with the goal of improving BCI for people with neuromuscular disorders.

APPROACH

Nine people with ALS used a P300-based BCI at home over several months for communication and computer control. Sessions from a routine calibration task were categorized as successful ([Formula: see text]70%) or unsuccessful (<70%) BCI performance. The correlation of temporal and spectral EEG features with BCI performance was then evaluated.

MAIN RESULTS

BCI performance was positively correlated with an increase in alpha-band (8-14 Hz) activity at locations PO8, P3, Pz, and P4; and beta-band (15-30 Hz) activity at occipital locations. In addition, performance was significantly positively correlated with a positive deflection in EEG amplitude around 220 ms at frontal mid-line locations (i.e. Fz and Cz). BCI performance was negatively correlated with delta-band (1-3 Hz) activity recorded from occipital locations.

SIGNIFICANCE

These results highlight the variability found in the EEG and describe EEG features that correlate with successful BCI performance during day-to-day use of a P300-based BCI by people with ALS. These results should inform studies focused on improved BCI reliability for people with neuromuscular disorders.

P300 Speller Performance Predictor Based on RSVP Multi-feature

Brain-computer interface (BCI) systems were developed so that people can control computers or machines through their brain activity without moving their limbs. The P300 speller is one of the BCI applications used most commonly, as is very simple and reliable and can achieve satisfactory performance. However, like other BCIs, the P300 speller still has room for improvements in terms of its practical use, for example, selecting the best compromise between spelling accuracy and information transfer rate (ITR; speed) so that the P300 speller can maintain high accuracy while increasing spelling speed. Therefore, seeking correlates of, and predicting, the P300 speller's performance is necessary to understand and improve the technique. In this work, we investigated the correlations between rapid serial visual presentation (RSVP) task features and the P300 speller's performance. Fifty-five subjects participated in the RSVP and conventional matrix P300 speller tasks and RSVP behavioral and electroencephalography (EEG) features were compared in the P300's speller performance. We found that several of the RSVP's event-related potential (ERP) and behavioral features were correlated with the P300 speller's offline binary classification accuracy. Using these features, we propose a simple multi-feature performance predictor (r = 0.53, p = 0.0001) that outperforms any single feature performance predictor, including that of the conventional RSVP T1% predictor (r = 0.28, p = 0.06). This result demonstrates that selective multi-features can predict BCI performance better than a single feature alone.

UMA-BCI Speller: An easily configurable P300 speller tool for end users

BACKGROUND AND OBJECTIVE

Some neurodegenerative conditions can severely limit patients' capability to communicate because of the loss of muscular control. Brain-computer interfaces may help in the restoration of communication with these patients, bypassing the muscular activity, so that brain signals can be directly interpreted by a computer. There are many studies regarding brain-controlled spellers; however, these systems do not usually leap out of the lab because of technical and economic requirements. As a consequence, the potential end users do not benefit from these scientific advances in their daily life. The objective of this paper is to present a novel brain-controlled speller designed to be used by patients due to its versatility and ease of use.

METHODS

The brain-computer interface research group of the University of Málaga (UMA-BCI) has developed a speller application based on the well-known P300 potential which can be easily installed, configured and used. The application supports the common P300 paradigms: the Row-Column Paradigm and the Rapid Serial Visual Presentation Paradigm. The inner core of the application is implemented with a widely used and studied platform, BCI2000, which ensures its reliability and allows other researchers to apply modifications at will in order to test new features. Ten naïve volunteers carried out exercises using the application and completed usability tests for evaluation purposes.

RESULTS

New subjects using the application managed to set up and use the proposed speller in less than an hour. The positive results of the evaluation through the usability tests support this application's ease of use.

CONCLUSIONS

A new brain-controlled spelling tool has been presented whose aim is to be used by severely paralyzed patients in their daily lives, as well as by researchers to test new spelling features.

Vigilance state fluctuations and performance using brain-computer interface for communication

The effect of fatigue and drowsiness on brain-computer interface (BCI) performance was evaluated. 20 healthy participants performed a standardized 11-minute calibration of a Rapid Serial Visual Presentation BCI system five times over two hours. For each calibration, BCI performance was evaluated using area under the receiver operating characteristic curve (AUC). Self-rated measures were obtained following each calibration including the Karolinska Sleepiness Scale and a standardized boredom scale. Physiological measures were obtained during each calibration including P300 amplitude, theta power, alpha power, median power frequency and eye-blink rate. There was a significant decrease in AUC over the five sessions. This was paralleled by increases in self-rated sleepiness and boredom and decreases in P300 amplitude. Alpha power, median power frequency, and eye-blink rate also increased but more modestly. AUC changes were only partly explained by changes in P300 amplitude. There was a decrease in BCI performance over time that related to increases in sleepiness and boredom. This worsened performance was only partly explained by decreases in P300 amplitude. Thus, drowsiness and boredom have a negative impact on BCI performance. Increased BCI performance may be possible by developing physiological measures to provide feedback to the user or to adapt the classifier to state.

Electroencephalography-based endogenous brain-computer interface for online communication with a completely locked-in patient

Background

Brain–computer interfaces (BCIs) have demonstrated the potential to provide paralyzed individuals with new means of communication, but an electroencephalography (EEG)-based endogenous BCI has never been successfully used for communication with a patient in a completely locked-in state (CLIS).

Methods

In this study, we investigated the possibility of using an EEG-based endogenous BCI paradigm for online binary communication by a patient in CLIS. A female patient in CLIS participated in this study. She had not communicated even with her family for more than one year with complete loss of motor function. Offline and online experiments were conducted to validate the feasibility of the proposed BCI system. In the offline experiment, we determined the best combination of mental tasks and the optimal classification strategy leading to the best performance. In the online experiment, we investigated whether our BCI system could be potentially used for real-time communication with the patient.

Results

An online classification accuracy of 87.5% was achieved when Riemannian geometry-based classification was applied to real-time EEG data recorded while the patient was performing one of two mental-imagery tasks for 5 s.

Conclusions

Our results suggest that an EEG-based endogenous BCI has the potential to be used for online communication with a patient in CLIS.

New and emerging access technologies for adults with complex communication needs and severe motor impairments: State of the science

Individuals with complex communication needs often use alternative access technologies to control their augmentative and alternative communication (AAC) devices, their computers, and mobile technologies. While a range of access devices is available, many challenges continue to exist, particularly for those with severe motor-control limitations. For some, access options may not be readily available or access itself may be inaccurate and frustrating. For others, access may be available but only under optimal conditions and support. There is an urgent need to develop new options for individuals with severe motor impairments and to leverage existing technology to improve efficiency, increase accuracy, and decrease fatigue of access. This paper describes person-centred research and development activities related to new and emerging access technologies, with a particular focus on adults with acquired neurological conditions.

Considering Augmentative and Alternative Communication Research for Brain-Computer Interface Practice

PURPOSE

Brain-computer interfaces (BCIs) aim to provide access to augmentative and alternative communication (AAC) devices via brain activity alone. However, while BCI technology is expanding in the laboratory setting there is minimal incorporation into clinical practice. Building upon established AAC research and clinical best practices may aid the clinical translation of BCI practice, allowing advancements in both fields to be fully leveraged.

METHOD

A multidisciplinary team developed considerations for how BCI products, practice, and policy may build upon existing AAC research, based upon published reports of existing AAC and BCI procedures.

OUTCOMES/BENEFITS

Within each consideration, a review of BCI research is provided, along with considerations regarding how BCI procedures may build upon existing AAC methods. The consistent use of clinical/research procedures across disciplines can help facilitate collaborative efforts, engaging a range-individuals within the AAC community in the transition of BCI into clinical practice.

Brain-computer interface use is a skill that user and system acquire together

A brain-computer interface (BCI) is a computer-based system that acquires, analyzes, and translates brain signals into output commands in real time. Perdikis and colleagues demonstrate superior performance in a Cybathlon BCI race using a system based on "three pillars": machine learning, user training, and application. These results highlight the fact that BCI use is a learned skill and not simply a matter of "mind reading."