Brain-Computer Interface Device for Severe Neurological Disorders
(BRAVO Trial)
Recruiting in Palo Alto (17 mi)
Overseen byKarunesh Ganguly, MD, PhD
Age: 18+
Sex: Any
Travel: May Be Covered
Time Reimbursement: Varies
Trial Phase: Academic
Recruiting
Sponsor: Karunesh Ganguly
Disqualifiers: Dementia, Active depression, Substance abuse, others
No Placebo Group
Approved in 1 Jurisdiction
Trial Summary
What is the purpose of this trial?This trial is testing a method that uses sensors on the brain to help people with severe neurological disorders control devices and speak. The sensors pick up brain signals and translate them into actions or speech. This could help those who struggle with movement and communication due to their condition.
Will I have to stop taking my current medications?
The trial information does not specify if you need to stop taking your current medications. It's best to discuss this with the trial coordinators.
What data supports the effectiveness of the treatment PMT/Blackrock Combination Device for severe neurological disorders?
Research shows that brain-machine interfaces (BMIs), like the PMT/Blackrock Combination Device, have made significant progress in helping patients with severe neurological impairments regain some neural functions. Studies have demonstrated that BMIs can enable people with movement and communication disorders to control assistive devices directly with their brain signals, improving their quality of life.
12345What safety data exists for the Brain-Computer Interface Device for Severe Neurological Disorders?
The BrainGate feasibility study, the largest and longest-running clinical trial of an implanted brain-computer interface, reports safety results but acknowledges that the long-term safety of these devices in humans is still unknown. Additionally, a study involving a neural interface in patients with Parkinson's disease found no serious surgical complications, suggesting a favorable safety profile in the short term.
35678How is the PMT/Blackrock Combination Device treatment different from other treatments for severe neurological disorders?
The PMT/Blackrock Combination Device is unique because it uses a brain-machine interface (BMI) to directly connect the brain to external devices, allowing real-time control and communication for patients with severe neurological disorders. This approach is different from traditional treatments as it involves implanting electrodes on the brain's surface to capture brain signals, which are then translated into actions, potentially restoring neural functions and improving quality of life.
1291011Eligibility Criteria
Adults over 21 with severe limitations in upper limb use due to conditions like stroke, ALS, MS, or spinal cord injury. They must have significant disability and be at least one year post-symptom onset for strokes or injuries. Participants need to live within two hours of UCSF and cannot be pregnant, have certain mental health issues, substance abuse history, major organ failure, prior brain surgery or seizures.Inclusion Criteria
I need help with daily activities due to my disability.
I have limited use of my arms due to a neurological condition.
It has been over a year since my stroke or spinal cord injury.
+2 more
Exclusion Criteria
Inability to comply with study follow-up visits
I have a history of seizures.
My immune system is weak.
+14 more
Trial Timeline
Screening
Participants are screened for eligibility to participate in the trial
2-4 weeks
Training and Assessment
Participants undergo training and assessment of their ability to control a complex robotic system using ECoG signals
6 months
Follow-up
Participants are monitored for safety and effectiveness after treatment
Up to 6 years
Participant Groups
The trial is testing a device combining PMT/Blackrock technology that uses brain signals (ECoG) for controlling motor and speech devices in those severely affected by neurological disorders.
1Treatment groups
Experimental Treatment
Group I: Electrocorticography-based brain computer interfaceExperimental Treatment1 Intervention
PMT/Blackrock Combination Device is already approved in United States for the following indications:
🇺🇸 Approved in United States as PMT/Blackrock Combination Device for:
- Severe neurological disorders requiring motor and speech control assistance
Find a Clinic Near You
Research Locations NearbySelect from list below to view details:
University of California San FranciscoSan Francisco, CA
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Who Is Running the Clinical Trial?
Karunesh GangulyLead Sponsor
University of California, San FranciscoLead Sponsor
National Institute on Deafness and Other Communication Disorders (NIDCD)Collaborator
References
[Brain-machine interface (BMI) - application to neurological disorders]. [2019]Brain-machine interface (BMI) is a new technology to receive input from the brain which is translated to operate a computer or other external device in real time. After significant progress during the recent 10 years, this technology is now very close to the clinical use to restore neural functions of patients with severe neurologic impairment. This technology is also a strong tool to investigate the mode of neuro-signal processing in the brain and to understand the mechanism of neural dysfunction which leads to the development of novel neurotechnology for the treatment of various sorts of neurological disorders.
Development of an implantable wireless ECoG 128ch recording device for clinical brain machine interface. [2020]Brain Machine Interface (BMI) is a system that assumes user's intention by analyzing user's brain activities and control devices with the assumed intention. It is considered as one of prospective tools to enhance paralyzed patients' quality of life. In our group, we especially focus on ECoG (electro-corti-gram)-BMI, which requires surgery to place electrodes on the cortex. We try to implant all the devices within the patient's head and abdomen and to transmit the data and power wirelessly. Our device consists of 5 parts: (1) High-density multi-electrodes with a 3D shaped sheet fitting to the individual brain surface to effectively record the ECoG signals; (2) A small circuit board with two integrated circuit chips functioning 128 [ch] analogue amplifiers and A/D converters for ECoG signals; (3) A Wifi data communication & control circuit with the target PC; (4) A non-contact power supply transmitting electrical power minimum 400[mW] to the device 20[mm] away. We developed those devices, integrated them, and, investigated the performance.
Cortical neuroprosthetics from a clinical perspective. [2021]Recent pilot clinical studies have demonstrated that subjects with severe disorders of movement and communication can exert direct neural control over assistive devices using invasive Brain-Machine Interface (BMI) technology, also referred to as 'cortical neuroprosthetics'. These important proof-of-principle studies have generated great interest among those with disability and clinicians who provide general medical, neurological and/or rehabilitative care. Taking into account the perspective of providers who may be unfamiliar with the field, we first review the clinical goals and fundamentals of invasive BMI technology, and then briefly summarize the vast body of basic science research demonstrating its feasibility. We emphasize recent translational progress in the target clinical populations and discuss translational challenges and future directions.
Brain-Computer Interfaces in Neurorecovery and Neurorehabilitation. [2023]Recent advances in brain-computer interface technology to restore and rehabilitate neurologic function aim to enable persons with disabling neurologic conditions to communicate, interact with the environment, and achieve other key activities of daily living and personal goals. Here we evaluate the principles, benefits, challenges, and future directions of brain-computer interfaces in the context of neurorehabilitation. We then explore the clinical translation of these technologies and propose an approach to facilitate implementation of brain-computer interfaces for persons with neurologic disease.
Chronic multisite brain recordings from a totally implantable bidirectional neural interface: experience in 5 patients with Parkinson's disease. [2019]OBJECTIVE Dysfunction of distributed neural networks underlies many brain disorders. The development of neuromodulation therapies depends on a better understanding of these networks. Invasive human brain recordings have a favorable temporal and spatial resolution for the analysis of network phenomena but have generally been limited to acute intraoperative recording or short-term recording through temporarily externalized leads. Here, the authors describe their initial experience with an investigational, first-generation, totally implantable, bidirectional neural interface that allows both continuous therapeutic stimulation and recording of field potentials at multiple sites in a neural network. METHODS Under a physician-sponsored US Food and Drug Administration investigational device exemption, 5 patients with Parkinson's disease were implanted with the Activa PC+S system (Medtronic Inc.). The device was attached to a quadripolar lead placed in the subdural space over motor cortex, for electrocorticography potential recordings, and to a quadripolar lead in the subthalamic nucleus (STN), for both therapeutic stimulation and recording of local field potentials. Recordings from the brain of each patient were performed at multiple time points over a 1-year period. RESULTS There were no serious surgical complications or interruptions in deep brain stimulation therapy. Signals in both the cortex and the STN were relatively stable over time, despite a gradual increase in electrode impedance. Canonical movement-related changes in specific frequency bands in the motor cortex were identified in most but not all recordings. CONCLUSIONS The acquisition of chronic multisite field potentials in humans is feasible. The device performance characteristics described here may inform the design of the next generation of totally implantable neural interfaces. This research tool provides a platform for translating discoveries in brain network dynamics to improved neurostimulation paradigms. Clinical trial registration no.: NCT01934296 (clinicaltrials.gov).
Interim Safety Profile From the Feasibility Study of the BrainGate Neural Interface System. [2023]Brain-computer interfaces (BCIs) are being developed to restore mobility, communication, and functional independence to people with paralysis. Though supported by decades of preclinical data, the safety of chronically implanted microelectrode array BCIs in humans is unknown. We report safety results from the prospective, open-label, nonrandomized BrainGate feasibility study (NCT00912041), the largest and longest-running clinical trial of an implanted BCI.
Informed Consent in Implantable BCI Research: Identifying Risks and Exploring Meaning. [2018]Implantable brain-computer interface (BCI) technology is an expanding area of engineering research now moving into clinical application. Ensuring meaningful informed consent in implantable BCI research is an ethical imperative. The emerging and rapidly evolving nature of implantable BCI research makes identification of risks, a critical component of informed consent, a challenge. In this paper, 6 core risk domains relevant to implantable BCI research are identified-short and long term safety, cognitive and communicative impairment, inappropriate expectations, involuntariness, affective impairment, and privacy and security. Work in deep brain stimulation provides a useful starting point for understanding this core set of risks in implantable BCI. Three further risk domains-risks pertaining to identity, agency, and stigma-are identified. These risks are not typically part of formalized consent processes. It is important as informed consent practices are further developed for implantable BCI research that attention be paid not just to disclosing core research risks but exploring the meaning of BCI research with potential participants.
Invasive Brain Machine Interface System. [2020]Because of high spatial-temporal resolution of neural signals obtained by invasive recording, the invasive brain-machine interfaces (BMI) have achieved great progress in the past two decades. With success in animal research, BMI technology is transferring to clinical trials for helping paralyzed people to restore their lost motor functions. This chapter gives a brief review of BMI development from animal experiments to human clinical studies in the following aspects: (1) BMIs based on rodent animals; (2) BMI based on non-human primates; and (3) pilot BMIs studies in clinical trials. In the end, the chapter concludes with a summary of potential opportunities and future challenges in BMI technology.
Importance of Graphical User Interface in the design of P300 based Brain-Computer Interface systems. [2021]Develop an effective and intuitive Graphical User Interface (GUI) for a Brain-Computer Interface (BCI) system, that achieves high classification accuracy and Information Transfer Rates (ITRs), while using a simple classification technique. Objectives also include the development of an output device, that is capable of real time execution of the selected commands.
[Development of a cognitive BMI "neurocommunicator" as a communication aid of patients with severe motor deficits]. [2019]A cognitive brain-machine interface (BMI), "neurocommunicator" has been developed by the author's research group in AIST in order to support communication of patients with severer motor deficits. The system can identify candidate messages (pictograms) in real time from electroencephalography (EEG) data, combining three core technologies; 1) a portable/wireless EEG recorder; 2) a high-speed and high-accuracy decoding algorithm; and 3) a hierarchical message generation system. The accuracy of the model at single predictions of the target was generally over 95%, corresponding to about 32 bits per minute for normal subjects. Monitor experiments have been also started for patients at their home, in which further technical improvements are required.
[Brain-Machine Interface and Neuro-Rehabilitation]. [2019]Brain-Machine Interface (BMI) is a technology that enables users to control computers/machines intuitively via their volitional brain activities. Controlling robotic arms and tablet PCs, assisting the movement of paretic limbs through robotic action/neuromuscular electrical stimulation, and other types of cybernetic device controls have been demonstrated. The continued use of BMI promotes the plasticity of brains, hence the functional reorganization of sensorimotor nervous systems can be induced in patients with motor disabilities. The application of BMI for the compensation and neurological recovery of physical movement might be clinically tolerated in the future.