11 Clinical Trials for Various Conditions
The primary aims of this study are: 1. To determine the feasibility of deploying mindBEAGLE, a portable, bedside EEG-based system, in the Intensive Care Unit in patients with disorders of consciousness (DOC) or locked-in syndrome (LIS); 2. To determine if mindBEAGLE neurophysiologic markers of cognitive function correlate with bedside behavioral assessments of consciousness; 3. To determine if mindBEAGLE neurophysiologic markers of cognitive function correlate with functional MRI (fMRI) and electroencephalography (EEG) biomarkers of consciousness; 4. To determine if mindBEAGLE can serve as an assistive communication device for people with LIS.
Locked-In Syndrome (LIS) is a devastating condition in which a person has lost the ability to communicate due to motor impairment, while being mentally intact. For people affected by this severe communication impairment, Brain-Computer Interfaces (BCI) may be the only solution that allows these people to start a conversation, ask questions, or request assistance (i.e. self-initiated communication). To-date, spelling was accomplished at a rate of 2-3 letters per minute with a predecessor device (the Medtronic Activa PC+S). To improve BCI performance, the current protocol will use the Medtronic Summit System, which offers a rechargeable battery and improved signal quality relative to Activa PC+S. Using signals from the motor hand/arm and/or motor mouth/face area, the investigators will investigate different avenues to improve the speed of communication using the Summit System. The primary objective is to evaluate the safety of the Summit System when used to chronically record subdural electrocorticographic (ECoG) signals in a BCI for use by patients with LIS in patients' homes. The secondary objective will be to evaluate the efficacy of the Summit System as a long-term source of ECoG signals for a BCI capable of allowing participants to control alternative and augmentative communication software in patients' homes.
The goal of this study is to improve our understanding of speech production, and to translate this into medical devices called intracortical brain-computer interfaces (iBCIs) that will enable people who have lost the ability to speak fluently to communicate via a computer just by trying to speak.
The purpose of this study is to obtain preliminary device safety information and demonstrate proof of principle (feasibility) of the ability of people with tetraplegia to control a computer cursor and other assistive devices with their thoughts.
VA research has been advancing a high-performance brain-computer interface (BCI) to improve independence for Veterans and others living with tetraplegia or the inability to speak resulting from amyotrophic lateral sclerosis, spinal cord injury or stoke. In this project, the investigators enhance deep learning neural network decoders and multi-state gesture decoding for increased accuracy and reliability and deploy them on a battery-powered mobile BCI device for independent use of computers and touch-enabled mobile devices at home. The accuracy and usability of the mobile iBCI will be evaluated with participants already enrolled separately in the investigational clinical trial of the BrainGate neural interface.
This project adds to non-invasive BCIs for communication for adults with severe speech and physical impairments due to neurodegenerative diseases. Researchers will optimize \& adapt BCI signal acquisition, signal processing, natural language processing, \& clinical implementation. BCI-FIT relies on active inference and transfer learning to customize a completely adaptive intent estimation classifier to each user's multi-modality signals simultaneously. 3 specific aims are: 1. develop \& evaluate methods for on-line \& robust adaptation of multi-modal signal models to infer user intent; 2. develop \& evaluate methods for efficient user intent inference through active querying, and 3. integrate partner \& environment-supported language interaction \& letter/word supplementation as input modality. The same 4 dependent variables are measured in each SA: typing speed, typing accuracy, information transfer rate (ITR), \& user experience (UX) feedback. Four alternating-treatments single case experimental research designs will test hypotheses about optimizing user performance and technology performance for each aim.Tasks include copy-spelling with BCI-FIT to explore the effects of multi-modal access method configurations (SA1.3a), adaptive signal modeling (SA1.3b), \& active querying (SA2.2), and story retell to examine the effects of language model enhancements. Five people with SSPI will be recruited for each study. Control participants will be recruited for experiments in SA2.2 and SA3.4. Study hypotheses are: (SA1.3a) A customized BCI-FIT configuration based on multi-modal input will improve typing accuracy on a copy-spelling task compared to the standard P300 matrix speller. (SA1.3b) Adaptive signal modeling will allow people with SSPI to typing accurately during a copy-spelling task with BCI-FIT without training a new model before each use. (SA2.2) Either of two methods of adaptive querying will improve BCI-FIT typing accuracy for users with mediocre AUC scores. (SA3.4) Language model enhancements, including a combination of partner and environmental input and word completion during typing, will improve typing performance with BCI-FIT, as measured by ITR during a story-retell task. Optimized recommendations for a multi-modal BCI for each end user will be established, based on an innovative combination of clinical expertise, user feedback, customized multi-modal sensor fusion, and reinforcement learning.
The CortiCom system consists of 510(k)-cleared components: platinum PMT subdural cortical electrode grids, a Blackrock Microsystems patient pedestal, and an external NeuroPort Neural Signal Processor. Up to two grids will be implanted in the brain, for a total channel count of up to 128 channels, for six months. In each participant, the grid(s) will be implanted over areas of cortex that encode speech and upper extremity movement.
The purpose of this protocol is to (1) Determine whether a one-on-one mindfulness meditation intervention or audio training improves performance on an adaptive communication system that utilizes brain-computer interface (BCI); and (2) Determine whether the intervention reduces stress in subjects with severe speech and physical impairments (SSPI). Hypothesis: The group of subjects randomized to the mindfulness meditation training will improve BCI performance and stress levels more than the audio control group.
The purpose of this study is to obtain preliminary device safety information and demonstrate proof of principle (feasibility) of the ability of people with tetraplegia to control a computer cursor and other assistive devices with their thoughts.
The goal of this clinical trial is to test how effective the mindBEAGLE device is in allowing people who are unconscious (due to a brain injury or other condition) to communicate using brain waves to answer Yes/No questions. Participants will wear a cap that will be connected to a computer that measures brain waves, wrist bands that vibrate at different strengths, and ear phones that create different levels of loud tones and will be asked to associate Yes/No answers with the vibrations or tones. They will also be asked to "think about" moving different parts of their body to answer Yes or No. The mindBEAGLE device has already been proven effective for this kind of communication in a previous study, and the study team would like to trial it on a population of unconscious people who enter the UPMC Rehabilitation Institute to see if patients are able to be trained to use the device as part of their everyday inpatient rehabilitation until they are discharged, or until they are able to regain consciousness.
Determine if Telehealth intervention can allow/empower a caregiver (who is untrained) to effectively implement and utilize a Brain-Computer Interface for communication with a participant who is "Locked in" following progression of Amyotrophic Lateral Sclerosis and other conditions.