Brain–computer interfaces in neurological rehabilitation

Daly, Janis J.; Wolpaw, Jonathan R.

doi:10.1016/s1474-4422(08)70223-0

Cited by 944 publications

(621 citation statements)

References 103 publications

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“…41,42,66,67 In addition, some researchers are exploring the use of BCIs in neurorehabilitation. 68 The hypothesis is that BCIs can augment current rehabilitation therapies by reinforcing and thereby increasing more effective use of impaired brain areas and connections. 69,70 Studies in stroke patients have shown that, with a motor relearning intervention, EEG features change in parallel with improvement in motor function 71 and that sensorimotor rehabilitation using BCI training and motor imagery may improve motor function after CNS injury.…”

Section: Device Outputmentioning

confidence: 99%

Brain-Computer Interfaces in Medicine

Shih

Krusienski

Wolpaw

2012

Mayo Clinic Proceedings

544

279

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Brain-computer interfaces (BCIs) acquire brain signals, analyze them, and translate them into commands that are relayed to output devices that carry out desired actions. BCIs do not use normal neuromuscular output pathways. The main goal of BCI is to replace or restore useful function to people disabled by neuromuscular disorders such as amyotrophic lateral sclerosis, cerebral palsy, stroke, or spinal cord injury. From initial demonstrations of electroencephalography-based spelling and single-neuron-based device control, researchers have gone on to use electroencephalographic, intracortical, electrocorticographic, and other brain signals for increasingly complex control of cursors, robotic arms, prostheses, wheelchairs, and other devices. Brain-computer interfaces may also prove useful for rehabilitation after stroke and for other disorders. In the future, they might augment the performance of surgeons or other medical professionals. Brain-computer interface technology is the focus of a rapidly growing research and development enterprise that is greatly exciting scientists, engineers, clinicians, and the public in general. Its future achievements will depend on advances in 3 crucial areas. Brain-computer interfaces need signal-acquisition hardware that is convenient, portable, safe, and able to function in all environments. Brain-computer interface systems need to be validated in long-term studies of real-world use by people with severe disabilities, and effective and viable models for their widespread dissemination must be implemented. Finally, the day-to-day and moment-to-moment reliability of BCI performance must be improved so that it approaches the reliability of natural muscle-based function. U ntil recently, the dream of being able to control one's environment through thoughts had been in the realm of science fiction. However, the advance of technology has brought a new reality: Today, humans can use the electrical signals from brain activity to interact with, influence, or change their environments. The emerging field of brain-computer interface (BCI) technology may allow individuals unable to speak and/or use their limbs to once again communicate or operate assistive devices for walking and manipulating objects. Brain-computer interface research is an area of high public awareness. Videos on YouTube as well as news reports in the lay media indicate intense curiosity and interest in a field that hopefully one day soon will dramatically improve the lives of many disabled persons affected by a number of different disease processes.This review seeks to provide the general medical community with an introduction to BCIs. We define BCI and then review some of the seminal discoveries in this rapidly emerging field, the brain signals used by BCIs, the essential components of a BCI system, current BCI systems, and the key issues now engaging researchers. Challenges are inherent in translating any new technology to practical and useful clinical applications, and BCIs are no exception. We discuss the potent...

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Section: Device Outputmentioning

confidence: 99%

Brain-Computer Interfaces in Medicine

Shih

Krusienski

Wolpaw

2012

Mayo Clinic Proceedings

544

279

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“…For this purpose, the PSD was previously computed using the nonparametric Welch method, which is suitable for the analysis of nonstationary signals [43]. Hamming window of 2 13 samples (32 seconds), along with a 90% overlap and FFT of 2 13 points was used. This epoch length is long enough to collect several signal periods of alpha or beta frequency bands taken into account the sampling rate of 256 Hz.…”

Section: Duration Of Each Session Was Approximately 90 Minutes Depenmentioning

confidence: 99%

“…These endogenous BCI systems depend on the user's ability to control the amplitude in a specific frequency band of the EEG recorded over a particular cortical area [45]. MI-BCI is based on the generation of event-related desynchronization (ERD) and event-related synchronization (ERS) in alpha (8)(9)(10)(11)(12)(13) and beta (13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) frequency bands of the EEG [20,33]. These events are related to sensorimotor rhythms (SMR).…”

Section: Introductionmentioning

confidence: 99%

“…Since EEG-alpha and EEG-beta band activity are associated with different cognitive and motor functions [3,15,20,31,32], BCIs have become not only a tool to assist people with disabilities, but also a way to rehabilitate or restore motor or cognitive functions. Brain plasticity can be restored into a more normal brain function by means of inducing brain activity [13]. In this regard, neurofeedback training (NFT) has been shown to be an appropriate way to control one's own brain activity [47].…”

Section: Introductionmentioning

confidence: 99%

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Neurofeedback training with a motor imagery-based BCI: neurocognitive improvements and EEG changes in the elderly

Gómez‐Pilar

Corralejo

Nicolás-Alonso

et al. 2016

Med Biol Eng Comput

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“…Specific signals are extracted and feedback is provided to the user, for example by on-screen activity or through a peripheral device [1]. BCI systems have been identified as having potential as an assistive technology as they make it possible to perform basic commands using thinking strategies alone and they are not reliant on voluntary muscular movement, making them suitable for people with severe communication difficulties [2][3][4] and in neurological rehabilitation [5] and enabling greater social inclusion [6]. While the effectiveness of these systems is recognised as varying widely, with user motivation being a key determinant of success [7], results have been sufficiently promising [8][9][10] to warrant further exploration with different groups of users.…”

Section: Introductionmentioning

confidence: 99%

BNCI systems as a potential assistive technology: ethical issues and participatory research in the BrainAble project

Carmichael

2013

Disability and Rehabilitation: Assistive Technology

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Purpose. This paper highlights aspects of the current state of research and thinking about ethical issues in relation to Brain Computer Interface (BCI) and Brain-Neuronal Computer Interfaces (BNCI) research through the experience of one particular project, BrainAble, which is exploring and developing the potential of these technologies to enable people with complex disabilities to control a computer. It describes how ethical practice has been developed both within the multidisciplinary research team and with participants.Results. The paper presents findings from the project in which participants shared their views of the project prototypes, of the potential of BCI/BNCI systems as an assistive technology, and of their other possible applications. This draws attention to the importance of ethical practice in projects where high expectations of technologies, and representations of 'ideal types' of disabled users may reinforce stereotypes or drown out participant 'voices'. Conclusions. Ethical frameworks for research and development in emergent areas such as BCI/BNCI systems should be based on broad notions of a 'duty of care' while being sufficiently flexible to allow researchers to adapt project procedures according to participant needs. They need to be frequently revisited, not only in the light of experience, but also to make sure that they reflect new research findings and ever more complex and powerful technologies. Implications for Rehabilitation• BCI/BNCI systems are not similar to existing switch-controlled or eye gaze systems. Users and those supporting them need to have their expectations carefully managed.• BCI/BNCI are emergent technologies and side effects of long term use are not well understood: this demands an ongoing concern to ensure duty of care and maintenance of a 'watching brief' regarding ethical issues.• Practitioners need to be particularly careful when introducing BCI/BNCI systems to be sensitive to the meanings that are attached to them and how they may convey prognosis.

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Brain–computer interfaces in neurological rehabilitation

Cited by 944 publications

References 103 publications

Brain-Computer Interfaces in Medicine

Brain-Computer Interfaces in Medicine

Neurofeedback training with a motor imagery-based BCI: neurocognitive improvements and EEG changes in the elderly

BNCI systems as a potential assistive technology: ethical issues and participatory research in the BrainAble project

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