‘Thought’ – control of functional electrical stimulation to restore hand grasp in a patient with tetraplegia

Pfurtscheller, Gert; Müller, Gernot; Pfurtscheller, Jörg; Gerner, Hans Jürgen; Rupp, Rüdiger

doi:10.1016/s0304-3940(03)00947-9

Cited by 476 publications

(279 citation statements)

References 13 publications

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“…Other BCI systems depend on brain activity recorded non-invasively from the surface of the scalp using electroencephalography (EEG). EEG-based BCIs can be operated by modulations of EEG rhythmic activity located over scalp sensorimotor areas that are induced by motor imagery tasks [11]; these modulations can be used to control a cursor on a computer screen [12] or a prosthetic device for limited hand movements [13] [14]. Thus, it has become conceivable to extend the communication between disabled individuals and the external environment from mere symbolic interaction (e.g.…”

Section: Introductionmentioning

confidence: 99%

Non-invasive brain–computer interface system: Towards its application as assistive technology

Cincotti

Mattia

Aloise

et al. 2008

Brain Research Bulletin

270

147

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The quality of life of people suffering from severe motor disabilities can benefit from the use of current assistive technology capable of ameliorating communication, house-environment management and mobility, according to the user's residual motor abilities. Brain Computer Interfaces (BCIs) are systems that can translate brain activity into signals that control external devices. Thus they can represent the only technology for severely paralyzed patients to increase or maintain their communication and control options.Here we report on a pilot study in which a system was implemented and validated to allow disabled persons to improve or recover their mobility (directly or by emulation) and communication within the surrounding environment. The system is based on a software controller that offers to the user a communication interface that is matched with the individual's residual motor abilities. Patients (n=14) with severe motor disabilities due to progressive neurodegenerative disorders were trained to use the system prototype under a rehabilitation program carried out in a house-like furnished space. All users utilized regular assistive control options (e.g., microswitches or head trackers). In addition, four subjects learned to operate the system by means of a non-invasive EEG-based BCI. This system was controlled by the subjects' voluntary modulations of EEG sensorimotor rhythms recorded on the scalp; this skill was learnt even though the subjects have not had control over their limbs for a long time.Correspondence should be addressed to: Febo Cincotti, PhD, Fondazione Santa Lucia, IRCCS, Via Ardeatina, 306, 00179, Rome, Italy, Phone: +39-06-51501466, Fax: +39-06-51501465, f.cincotti@hsantalucia.it. * These authors equally contributed to the paper Conflict of Interest Declaration: I had full access to all the data in the study and I take responsibility for the integrity of the data and the accuracy of the data analysis. I also state that all authors have read and approved submission of the manuscript; the manuscript contains original material that has not been published and has not being considered for publication elsewhere.Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. We conclude that such a prototype system, which integrates several different assistive technologies including a BCI system, can potentially facilitate the translation from pre-clinical demonstrations to a clinical useful BCI. NIH Public Access

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Section: Introductionmentioning

confidence: 99%

Non-invasive brain–computer interface system: Towards its application as assistive technology

Cincotti

Mattia

Aloise

et al. 2008

Brain Research Bulletin

270

147

View full text Add to dashboard Cite

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“…Pfurtscheller and his colleagues attached a FES device to the forearm of a tetraplegic patient [56]. The BMI control was driven by EEG beta rhythms which the subject produced by imagining his foot move.…”

Section: Functional Electrical Stimulationmentioning

confidence: 99%

“…EEG-based BMIs have achieved many important milestones, such as control of a robot [72], wheelchair navigation [65], and control of hand orthosis [56,73].…”

Section: Noninvasive Bmismentioning

confidence: 99%

Brain-machine interfaces: an overview

Lebedev¹

2014

Translational Neuroscience

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Brain-machine interfaces (BMIs) hold promise to treat neurological disabilities by linking intact brain circuitry to assistive devices, such as limb prostheses, wheelchairs, artificial sensors, and computers. BMIs have experienced very rapid development in recent years, facilitated by advances in neural recordings, computer technologies and robots. BMIs are commonly classified into three types: sensory, motor and bidirectional, which subserve motor, sensory and sensorimotor functions, respectively. Additionally, cognitive BMIs have emerged in the domain of higher brain functions. BMIs are also classified as noninvasive or invasive according to the degree of their interference with the biological tissue. Although noninvasive BMIs are safe and easy to implement, their information bandwidth is limited. Invasive BMIs hold promise to improve the bandwidth by utilizing multichannel recordings from ensembles of brain neurons. BMIs have a broad range of clinical goals, as well as the goal to enhance normal brain functions.

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“…Future work on these neural prosthetic devices is also focusing on decoding the intended motion trajectories from the cerebral motor cortex and using this signal to control the FES devices. Hybrid Neuro-prosthetics are being investigated and may lead to the development of a cognitive link through cerebral motor cortex to these neural prosthetic devices [61,65]. Recently, Muller-Putz [60] reported a case study where an implanted FES device Freehand system was connected with an electroencephalogram (EEG) based-Brain-Computer Interface (BCI).…”

Section: Future Scopementioning

confidence: 99%

Role of electrical stimulation for rehabilitation and regeneration after spinal cord injury: an overview

2008

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Structural discontinuity in the spinal cord after injury results in a disruption in the impulse conduction resulting in loss of various bodily functions depending upon the level of injury. This article presents a summary of the scientific research employing electrical stimulation as a means for anatomical or functional recovery for patients suffering from spinal cord injury. Electrical stimulation in the form of functional electrical stimulation (FES) can help facilitate and improve upper/lower limb mobility along with other body functions lost due to injury e.g. respiratory, sexual, bladder or bowel functions by applying a controlled electrical stimulus to generate contractions and functional movement in the paralysed muscles. The available rehabilitative techniques based on FES technology and various Food and Drug Administration, USA approved neuroprosthetic devices that are in use are discussed. The second part of the article summarises the experimental work done in the past 2 decades to study the effects of weakly applied direct current fields in promoting regeneration of neurites towards the cathode and the new emerging technique of oscillating field stimulation which has shown to promote bidirectional regeneration in the injured nerve fibres. The present article is not intended to be an exhaustive review but rather a summary aiming to highlight these two applications of electrical stimulation and the degree of anatomical/functional recovery associated with these in the field of spinal cord injury research.

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‘Thought’ – control of functional electrical stimulation to restore hand grasp in a patient with tetraplegia

Cited by 476 publications

References 13 publications

Non-invasive brain–computer interface system: Towards its application as assistive technology

Non-invasive brain–computer interface system: Towards its application as assistive technology

Brain-machine interfaces: an overview

Role of electrical stimulation for rehabilitation and regeneration after spinal cord injury: an overview

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