Active clinical trials for "Locked-In Syndrome"

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 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 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.

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.

This study aims to evaluate the safety of a wireless implantable neurodevice microsystem in tetraplegic patients, as well as the efficacy of the electrodes for long-term recording of neural activities and the successful control of an external device.

In this study a new means of communication for people with locked-in syndrome will be tested. The investigators will record brain signals directly from the surface of the brain by means of a completely implantable system. These brain signals are fed wirelessly into an assistive technology device and will control this device for communication and environmental control at the users home.

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.

Aim of the work The aim of this study is to test an Arabic alphabet communication system designed to train physicians to communicate with Arabic-speaking patients with LIS. Subjects and methods Place of study: Department of Neurology at Sohag university hospital Type of study: clinical trial. Subjects: Thirty healthy subjects from three different educational levels. Ten subjects have a preparatory education level, ten subjects with a high school education or its equivalent, and ten subjects who have a university education or are still in a university education stage. They will be collected from among patients' relatives and employees of Sohag University Hospital. Methods of the study: The method shown in the figure No. 1 is the Arabic alphabet (arranged in the traditional order) printed on double-sided cardboard, with one copy facing the person and one facing the doctor. The code will be in the case of a positive selection (the desired line or letter) by looking up or one blink, but in the case of a negative selection (not the desired line or letter), it will be by looking down or two blinks. The person will choose the letters of each word and then choose the end of the word and after selecting all the words of the sentence choose the end of the sentence. After the strategy has been taught to the subject, he or she will be asked to communicate with the physician using this way.

People with locked-in syndrome cannot move their limbs or talk because of a motor impairment, but remain conscious and intellectually awake. Restoring the ability to communicate to people with locked-in syndrome will have a positive effect on their quality of life, will enable them to reintegrate into society and increase their capacity to lead productive and fulfilling lives. This study sims to develop a new assisted communication device based on a brain-computer interface, a system that allows the user to control a computer with his brain activity. The investigators will develop this brain-computer system for long-term stability and independent use by using adaptive decoders. The investigators will test the long-term stability and independence of this system with healthy volunteers, people with tetraplegia and people with locked-in syndrome over time periods of several months.