BCI-Controlled Devices for Motor Disorders
Recruiting in Palo Alto (17 mi)
Age: 18+
Sex: Any
Travel: May be covered
Time Reimbursement: Varies
Trial Phase: Academic
Recruiting
Sponsor: University of Texas at Austin
No Placebo Group
Approved in 2 jurisdictions
Trial Summary
What is the purpose of this trial?Injuries affecting the central nervous system may disrupt the cortical pathways to muscles causing loss of motor control. Nevertheless, the brain still exhibits sensorimotor rhythms (SMRs) during movement intents or motor imagery (MI), which is the mental rehearsal of the kinesthetics of a movement without actually performing it. Brain-computer interfaces (BCIs) can decode SMRs to control assistive devices and promote functional recovery. Despite rapid advancements in non-invasive BCI systems based on EEG, two persistent challenges remain: First, the instability of SMR patterns due to the non-stationarity of neural signals, which may significantly degrade BCI performance over days and hamper the effectiveness of BCI-based rehabilitation. Second, differentiating MI patterns corresponding to fine hand movements of the same limb is still difficult due to the low spatial resolution of EEG. To address the first challenge, subjects usually learn to elicit reliable SMR and improve BCI control through longitudinal training, so a fundamental question is how to accelerate subject training building upon the SMR neurophysiology. In this study, the investigators hypothesize that conditioning the brain with transcutaneous electrical spinal stimulation, which reportedly induces cortical inhibition, would constrain the neural dynamics and promote focal and strong SMR modulations in subsequent MI-based BCI training sessions - leading to accelerated BCI training. To address the second challenge, the investigators hypothesize that neuromuscular electrical stimulation (NMES) applied contingent to the voluntary activation of the primary motor cortex through MI can help differentiate patterns of activity associated with different hand movements of the same limb by consistently recruiting the separate neural pathways associated with each of the movements within a closed-loop BCI setup. The investigators study the neuroplastic changes associated with training with the two stimulation modalities.
Will I have to stop taking my current medications?
The trial does not specify if you need to stop taking your current medications, but it excludes participants on heavy medication affecting the central nervous system. It's best to discuss your specific medications with the trial team.
How is the treatment of non-invasive BCI-controlled assistive devices different from other treatments for motor disorders?
Non-invasive BCI-controlled assistive devices are unique because they allow people with motor disorders to control external devices using their brain activity, without the need for surgery or invasive procedures. This treatment uses EEG (a method to record brain activity) to interpret mental commands, offering a nonintrusive and user-friendly alternative to traditional therapies that often rely on physical movement or invasive techniques.
2571112Is it safe to use non-invasive BCI-controlled assistive devices for motor disorders?
The research on non-invasive BCI-controlled assistive devices shows that they are generally safe for use in humans, including those with severe disabilities and neurological disorders. However, improvements are needed for daily life use, and there are concerns about the regulatory safeguards for these devices.
3461011What data supports the effectiveness of the treatment Non-invasive BCI-controlled Assistive Devices for motor disorders?
Research shows that non-invasive brain-computer interfaces (BCIs) can help people with severe disabilities control devices using their brain signals. Studies have found that these BCIs can provide movement control comparable to more invasive methods, suggesting they could be effective for people with motor disorders.
168913Eligibility Criteria
This trial is for people with certain motor disabilities (like stroke, spinal cord injury, or muscular diseases) and healthy individuals with normal vision. Participants must understand English and be able to consent. Those with serious illnesses, attention/cognitive issues preventing focus during sessions, heavy central nervous system medication, or conditions affecting EEG/EMG data collection can't join.Participant Groups
The study tests brain-computer interfaces (BCI) that read brain activity to control devices without movement. It focuses on whether neuromuscular electrical stimulation (NMES), when paired with motor imagery-based BCI, improves the differentiation of hand movement patterns in the same limb.
4Treatment groups
Experimental Treatment
Active Control
Group I: TESS BCI - Standard MI TaskExperimental Treatment2 Interventions
Transcutaneous Electrical Spinal Stimulation (TESS) is applied for 20 minutes prior to BCI training sessions. Following TESS, BCI training is performed with visual feedback contingent to motor imagery as detected by a closed-loop BCI.
Group II: NMES BCI - Difficult MI TaskExperimental Treatment1 Intervention
BCI training is performed with NMES instead of Visual feedback. NMES is delivered over the flexors/extensors of the forearm contingent to the imagination of same-hand wrist and fingers flexion versus extension as detected by a closed-loop BCI.
Group III: Visual BCI - Standard MI TaskActive Control1 Intervention
Conventional BCI training is performed with visual feedback contingent to the imagination of right versus left hand movements as detected by a closed-loop BCI.
Group IV: Visual BCI - Difficult MI TaskActive Control1 Intervention
Conventional BCI training is performed with visual feedback contingent to the imagination of same-hand wrist and fingers flexion versus extension as detected by a closed-loop BCI.
Non-invasive BCI-controlled Assistive Devices is already approved in United States, European Union for the following indications:
🇺🇸 Approved in United States as Non-invasive BCI-controlled Assistive Devices for:
- Rehabilitation for stroke survivors with chronic motor deficits
- Assistive technology for individuals with severe motor impairments
🇪🇺 Approved in European Union as Non-invasive BCI-controlled Assistive Devices for:
- Assistive technology for individuals with spinal cord injuries
- Rehabilitation for individuals with motor impairments
Find A Clinic Near You
Research locations nearbySelect from list below to view details:
The University of Texas at AustinAustin, TX
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Who is running the clinical trial?
University of Texas at AustinLead Sponsor
References
Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans. [2023]Brain-computer interfaces (BCIs) can provide communication and control to people who are totally paralyzed. BCIs can use noninvasive or invasive methods for recording the brain signals that convey the user's commands. Whereas noninvasive BCIs are already in use for simple applications, it has been widely assumed that only invasive BCIs, which use electrodes implanted in the brain, can provide multidimensional movement control of a robotic arm or a neuroprosthesis. We now show that a noninvasive BCI that uses scalp-recorded electroencephalographic activity and an adaptive algorithm can provide humans, including people with spinal cord injuries, with multidimensional point-to-point movement control that falls within the range of that reported with invasive methods in monkeys. In movement time, precision, and accuracy, the results are comparable to those with invasive BCIs. The adaptive algorithm used in this noninvasive BCI identifies and focuses on the electroencephalographic features that the person is best able to control and encourages further improvement in that control. The results suggest that people with severe motor disabilities could use brain signals to operate a robotic arm or a neuroprosthesis without needing to have electrodes implanted in their brains.
Physiological regulation of thinking: brain-computer interface (BCI) research. [2006]The discovery of event-related desynchronization (ERD) and event-related synchronization (ERS) by Pfurtscheller paved the way for the development of brain-computer interfaces (BCIs). BCIs allow control of computers or external devices with the regulation of brain activity only. Two different research traditions produced two different types of BCIs: invasive BCIs, realized with implanted electrodes in brain tissue and noninvasive BCIs using electrophysiological recordings in humans such as electroencephalography (EEG) and magnetoencephalography (MEG) and metabolic changes such as functional magnetic resonance imaging (fMRI) and near infrared spectroscopy (NIRS). Clinical applications were reserved with few exceptions for the noninvasive approach: communication with the completely paralyzed and locked-in syndrome with slow cortical potentials (SCPs), sensorimotor rhythms (SMRs), and P300 and restoration of movement and cortical reorganization in high spinal cord lesions and chronic stroke. It was demonstrated that noninvasive EEG-based BCIs allow brain-derived communication in paralyzed and locked-in patients. Movement restoration was achieved with noninvasive BCIs based on SMRs control in single cases with spinal cord lesions and chronic stroke. At present no firm conclusion about the clinical utility of BCI for the control of voluntary movement can be made. Invasive multielectrode BCIs in otherwise healthy animals allowed execution of reaching, grasping, and force variations from spike patterns and extracellular field potentials. Whether invasive approaches allow superior brain control of motor responses compared to noninvasive BCI with intelligent peripheral devices and electrical muscle stimulation and EMG feedback remains to be demonstrated. The newly developed fMRI-BCIs and NIRS-BCIs offer promise for the learned regulation of emotional disorders and also disorders of small children (in the case of NIRS).
A high performance sensorimotor beta rhythm-based brain-computer interface associated with human natural motor behavior. [2022]To explore the reliability of a high performance brain-computer interface (BCI) using non-invasive EEG signals associated with human natural motor behavior does not require extensive training. We propose a new BCI method, where users perform either sustaining or stopping a motor task with time locking to a predefined time window. Nine healthy volunteers, one stroke survivor with right-sided hemiparesis and one patient with amyotrophic lateral sclerosis (ALS) participated in this study. Subjects did not receive BCI training before participating in this study. We investigated tasks of both physical movement and motor imagery. The surface Laplacian derivation was used for enhancing EEG spatial resolution. A model-free threshold setting method was used for the classification of motor intentions. The performance of the proposed BCI was validated by an online sequential binary-cursor-control game for two-dimensional cursor movement. Event-related desynchronization and synchronization were observed when subjects sustained or stopped either motor execution or motor imagery. Feature analysis showed that EEG beta band activity over sensorimotor area provided the largest discrimination. With simple model-free classification of beta band EEG activity from a single electrode (with surface Laplacian derivation), the online classifications of the EEG activity with motor execution/motor imagery were: >90%/ approximately 80% for six healthy volunteers, >80%/ approximately 80% for the stroke patient and approximately 90%/ approximately 80% for the ALS patient. The EEG activities of the other three healthy volunteers were not classifiable. The sensorimotor beta rhythm of EEG associated with human natural motor behavior can be used for a reliable and high performance BCI for both healthy subjects and patients with neurological disorders.
Brain-Computer Interface devices: risks and Canadian regulations. [2008]Implantable Brain-Computer Interface (BCI) devices are currently in clinical trials in the U.S., and their introduction into the Canada could follow in the next few years. This article provides an overview of the research, developments, design issues, and risks in BCIs and an analysis of the adequacy of the regulatory framework in place for the approval of medical devices in Canada, emphasizing device investigational testing. The article concludes that until better safeguards are in place, to best protect potential research subjects, BCIs should not be approved for investigational testing in Canada.
[Training protocol evaluation of a brain-computer interface: mental tasks proposal]. [2015]A brain-computer interface (BCI) is based on the analysis of the electroencephalographic (EEG) signals recorded during certain mental activities, to control an external device. Main users are people with severe neuromuscular disorders, like amyotrophic lateral sclerosis. One of the most important problems to control a BCI is the need of providing suitable training, helping subjects to get some control of the EEG signals.
A brain-computer interface as input channel for a standard assistive technology software. [2017]Recently brain-computer interface (BCI) control was integrated into the commercial assistive technology product QualiWORLD (QualiLife Inc., Paradiso-Lugano, CH). Usability of the first prototype was evaluated in terms of effectiveness (accuracy), efficiency (information transfer rate and subjective workload/NASA Task Load Index) and user satisfaction (Quebec User Evaluation of Satisfaction with assistive Technology, QUEST 2.0) by four end-users with severe disabilities. Three assistive technology experts evaluated the device from a third person perspective. The results revealed high performance levels in communication and internet tasks. Users and assistive technology experts were quite satisfied with the device. However, none could imagine using the device in daily life without improvements. Main obstacles were the EEG-cap and low speed.
Brain-computer interfaces using capacitive measurement of visual or auditory steady-state responses. [2013]Brain-computer interface (BCI) technologies have been intensely studied to provide alternative communication tools entirely independent of neuromuscular activities. Current BCI technologies use electroencephalogram (EEG) acquisition methods that require unpleasant gel injections, impractical preparations and clean-up procedures. The next generation of BCI technologies requires practical, user-friendly, nonintrusive EEG platforms in order to facilitate the application of laboratory work in real-world settings.
recoveriX: a new BCI-based technology for persons with stroke. [2020]Brain-computer interface (BCI) systems have been used primarily to provide communication for persons with severe movement disabilities. This paper presents a new system that extends BCI technology to a new patient group: persons diagnosed with stroke. This system, called recoveriX, is designed to detect changes in motor imagery in real-time to help monitor compliance and provide closed-loop feedback during therapy. We describe recoveriX and present initial results from one patient.
Brain⁻Computer Interfaces for Human Augmentation. [2020]The field of brain⁻computer interfaces (BCIs) has grown rapidly in the last few decades, allowing the development of ever faster and more reliable assistive technologies for converting brain activity into control signals for external devices for people with severe disabilities [...].
Single-paradigm and hybrid brain computing interfaces and their use by disabled patients. [2020]Brain computer interfacing (BCI) has enjoyed increasing interest not only from research communities such as engineering and neuroscience but also from visionaries that predict it will change the way we will interact with technology. Since BCIs establish an alternative communication channel between the brain and the outside world, they have been hailed to provide solutions for patients suffering from severe motor- and/or communication disabilities such as fully paralyzed locked-in syndrome patients. However, despite single-case successes, which sometimes reach a broad audience, BCIs are actually not routinely used to support patients in their daily life activities. This review focusses on non-invasive BCIs, introduces the main paradigms and applications, and shows how the technology has improved over recent years. We identify patient groups that potentially can benefit from BCIs by referring to disability levels and etiology. We list the requirements, indicate how BCIs can tap into their spared competences, and discuss performance issues also in view of other assistive communication technologies. We discuss hybrid BCIs, a more recent development that combines paradigms and signals, possibly also of non-brain origin, to increase performance in terms of accuracy and/or communication speed, also as a way to counter the low performance with a given paradigm by involving another, more suitable one (BCI illiteracy). Finally, we list a few hybrid BCI solutions for patients and note that demonstrations with the ones based entirely on brain activity are still scarce.
A dynamic and self-adaptive classification algorithm for motor imagery EEG signals. [2020]Brain-computer interface (BCI) is a communication pathway applied for pathological analysis or functional substitution. BCI based on functional substitution enables the recognition of a subject's intention to control devices such as prosthesis and wheelchairs. Discrimination of electroencephalography (EEG) trials related to left- and right-hand movements requires complex EEG signal processing to achieve good system performance.
A Step Closer to Mind Control for Everyday Life. [2021]Brain-computer interface (BCI) technology holds promise for providing functional support systems for people with neurological disorders and other disabilities. In experimental laboratory settings, BCIs have allowed patients to communicate with researchers and control external devices-all by simply imagining the actions of different body parts.
A click-based electrocorticographic brain-computer interface enables long-term high-performance switch-scan spelling. [2023]Brain-computer interfaces (BCIs) can restore communication in movement- and/or speech-impaired individuals by enabling neural control of computer typing applications. Single command "click" decoders provide a basic yet highly functional capability.