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Advanced neural decoders for the restoration of communication

用于恢复通信的高级神经解码器

基本信息

批准号：
9457173
负责人：
JAIMIE M HENDERSON
金额：
$ 76.37万
依托单位：
STANFORD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-04-01 至 2020-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9457173
关键词：
Address Algorithm Design Amyotrophic Lateral Sclerosis Augmentative and Alternative Communication Brain Brain Stem Infarctions Clinic Clinical Trials Communication Communication impairment Computer software Computers Devices Disease Electrodes Enrollment Eye Eye Movements Formulation Foundations Goals Human Impairment Implant Individual Injury Laboratories Laboratory Animals Limb structure Location Locked-In Syndrome Measures Methods Mind Monkeys Motor Motor Activity Motor Cortex Movement Mus Neurons Paralysed Participant Partner Communications Performance Physically Handicapped Principal Investigator Quadriplegia Quality of life Radial Refit Reporting Research Signal Transduction Software Design Speech Speed System Techniques Technology Testing Time Translating arm base brain computer interface communication device computerized density design disability experimental study falls graphical user interface improved innovation markov model member neurotransmission novel novel strategies performance tests pre-clinical pre-clinical research programs public health relevance relating to nervous system restoration safety and feasibility spelling

项目摘要

DESCRIPTION (provided by applicant): Difficulty with communication is a widespread problem, reported by more than 2 million people in the US. Communication may be a particular challenge for people with total paralysis ("Locked-in Syndrome" or LIS) from disorders such as brainstem strokes or advanced Amyotrophic Lateral Sclerosis (ALS). People with these disorders rely on augmentative and alternative communication (AAC) technology that can be inefficient, often not designed with their unique access needs in mind, and therefore frustrating to implement successfully. Brain-computer interface (BCI) systems provide one promising avenue for restoring communication capabilities to people with LIS. However, these systems currently offer performance well below that achievable by able-bodied computer users. The overall objective of the proposed research is to evaluate advanced neural decoding methods and interfaces for a high-performance communication system for people with LIS. To accomplish this, we propose 3 Specific Aims as follows. Aim 1: We will evaluate whether advanced decoding techniques developed in the animal laboratory can improve continuous point-and-click control of a computer cursor from signals decoded from human motor cortex. Aim 2: We will optimize parameters for high-speed discrete target selection (i.e., typing) by decoding movement intent from pre-motor cortex. Aim 3: We will test new communication interfaces based on the results of Aims 1 and 2 against each participant's usual AAC system, with the goal of providing faster and easier communication. Finally, we will assess the ability of research participants to control a commercial computer GUI and typing interface while switching between continuous and discrete decoding.