Brain Computer Interface Complete locked-in State Communication
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|ClinicalTrials.gov Identifier: NCT02980380|
Recruitment Status : Recruiting
First Posted : December 2, 2016
Last Update Posted : December 2, 2016
|Condition or disease||Intervention/treatment|
|Complete Locked-in State||Other: Non-invasive brain computer interface|
Amyotrophic lateral sclerosis is a progressive motor disease of unknown etiology resulting eventually in a complete paralysis of the motor system but affecting sensory or cognitive functions to a minor degree. There is no treatment available; patients have to decide to accept artificial respiration and feeding after the disease destroys respiratory and bulbar functions or to die of respiratory or related problems. If they opt for life and accept artificial respiration, the disease progresses until the patient loses control of the last muscular response, usually the eye muscles. If rudimentary voluntary control of at least one muscle is present the syndrome is called locked-in state (LIS); ultimately as the disease progresses most ALS patients lose the control of all muscles, the resulting condition is called completely locked-in state (CLIS). Patients in CLIS are unable to communicate with the external world because all assistive communication aids are based on some remaining motor control; hence there is a vital need for an assistive technology to help patients in CLIS to communicate needs and feelings to their family members/caregivers. Brain computer interface (BCI) represents a promising strategy to establish communication with paralyzed ALS patients, as it does not need muscle control. BCI research includes invasive (implantable electrodes on or in the neocortex) and noninvasive means (including electroencephalography (EEG), magnetoencephalography (MEG), functional magnetic resonance imaging (fMRI), and near-infrared spectroscopy (NIRS)) to record brain activity for conveying the user's intent to devices such as simple word-processing programs. Non-invasive methods have been utilized more frequently than invasive methods for people with disabilities (such as those with ALS).
For these conditions (LIS and CLIS) Brain-Computer-Interface were developed and tested extensively since the first publication of Birbaumer, 1999 of two LIS patients suffering from ALS. Patients select letters or words after learning self-regulation of the particular brain signal or by focusing their attention to the desired letter or a letter-matrix and the attention related brain potential selects the desired letter. While healthy people and ALS patients up to the LIS showed successful EEG-BCI control and communication, completely paralyzed ALS patients in CLIS did not learn sufficient EEG-based BCI control for brain communication. A single case report by Gallegos Ayala et al., 2014 for the first time described a CLIS patient with ALS achieving BCI-control and "yes" - "no" communication to simple questions with known positive answers or negative answers and some open questions over an extensive time period. NIRS was used to measure and classify cortical oxygenation and deoxygenation following the questions. The BCI methodology used in this report departed radically from the previous BCI-procedures: a more "reflexive" mode based on learning principles of classical conditioning to simple questions was used. This "reflexive" mode served to train the classifier separating "yes" and "no" brain answers silently imagined by the patient instead of neuroelectric recording (EEG), functional NIRS (fNIRS) was used.
Gallegos Ayala et al., 2014 was the first single case report of auditory BCI control by an ALS patient in CLIS and to this date no study has reported the successful "yes"- "no" communication in several ALS patient in CLIS. In order to replicate and generalize the results of Gallegos-Ayala et al., 2014 in the present study fNIRS based BCI will be employed for communication in ALS patients in CLIS. The hemodynamic change in the motor cortex of the CLIS patient will be recorded across many sessions spread over more than a year and will be used to train a classifier to predict the "yes" and "no" answering pattern of the CLIS patient.
|Study Type :||Observational|
|Estimated Enrollment :||15 participants|
|Official Title:||Brain Computer Interface Based Communication in the Completely Locked-In State|
|Study Start Date :||June 2014|
|Estimated Primary Completion Date :||December 2020|
Complete locked-in state patients
Amyotrophic lateral sclerosis patients in complete locked-in state who have no means of communication.
Other: Non-invasive brain computer interface
The hemodynamic change in the motor cortex of the CLIS patient will be recorded across many sessions spread over more than a year and will be used to train a classifier to predict the "yes" and "no" answering pattern of the CLIS patient
- Brain Computer Interface Based Communication in the Completely Locked-In State patients [ Time Frame: 2 years ]fNIRS based BCI will be employed for communication in ALS patients in CLIS. The hemodynamic change in the motor cortex of the CLIS patient will be recorded and will be used for communication.
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT02980380
|Contact: Ujwal Chaudhary, PhDemail@example.com|
|Contact: Niels Birbaumer, PhDfirstname.lastname@example.org|
|University of Tuebingen||Recruiting|
|Tubingen, Baden Wuerttemberg, Germany, 72076|
|Contact: Ujwal Chaudhary, PhD email@example.com|
|Contact: Niels Birbaumer, PhD firstname.lastname@example.org|
|Principal Investigator:||Niels Birbaumer, PhD||University Hospital Tuebingen|