A primate model of an intra-cortically controlled FES prosthesis for grasp
A primate model of an intra-cortically controlled FES prosthesis for grasp
批准号:
7750515
负责人:
Lee Miller
金额:
$31.83万
依托单位国家:
美国
项目类别:
财政年份:
2006
资助国家:
美国
项目状态:
已结题
起止时间:
2006-01-01 至 2011-06-30
关键词:
AccountingAlgorithmsAreaAttentionBrainCervicalConsciousContractsDataDevelopmentDiscriminationElbowElectric StimulationElectrodesEnvironmentForearmFreedomGoalsHandHumanImplantIndividualInjuryIntramuscularLateralLearningLocal AnestheticsMapsMeasurementMeasuresMethodsModelingMonkeysMotorMotor CortexMovementMuscleNerveNerve BlockNeuronsParalysedPatientsPatternPerformancePrimatesProcessProsthesisQuadriplegiaResearch PersonnelSamplingSeriesShoulderSignal TransductionSpinal cord injuryStagingStimulusSystemTechniquesTestingTimeUniversitiesUpper Extremityarmbasebrain computer interfacedesigngraspimproved functioningmedian nerveneuromuscularneuroprosthesisprograms
中文摘要
这个项目的目标是开发一个上肢神经肌肉刺激的灵长类动物模型
通过皮层内记录电极控制的系统。脊髓损伤的患者
瘫痪是因为他们失去了激活肌肉的能力。这些病人的肌肉仍然可以
如果通过直接施加到肌肉或神经的电刺激来激活它们,则使其收缩。
同样,大脑中通常控制运动的区域仍然活跃,但它们与大脑的连接
由于受伤,他失去了肌肉。
凯斯西储大学(CWRU)的研究人员已经证明,
电刺激(FES)神经假体可用于恢复具有以下症状的个体的抓握功能:
四肢瘫痪尽管这些系统很出色,但它们仅限于预先编程的抓取模式,并且需要
相当有意识的注意。一个更自然的控制系统,有更多的自由度,
提供大大改进的功能。在西北大学,我们已经开发出了预测
手臂和手部肌肉在抓取运动的基础上,从大脑的微电极记录,
猴子.从一个单一的,长期植入的电极阵列,预测可以作出的活动,
肩膀手臂和手部肌肉这种类型的电极已经产生了持续的记录,
超过3年,并且最近已被批准用于人类患者的实验性使用。我们认为
像这样的皮层内记录提供了潜在的对多个程度的
通过自然思维过程的自由。通过结合西北大学和CWRU的优势
小组,我们建议开发一个脑机接口足以控制神经假体。的
开发这种神经假体系统的灵长类动物模型将是实现其功能的重要一步。
在人类患者中实施。这项申请包括以下具体目标:
1)我们建议使用一个100电极阵列植入在初级运动皮层的mnkey,以提供
输入到一组解码器,用于实时预测特定手部肌肉的活动。
2)我们建议使用目标1中开发的控制算法和植入的FES假体来恢复
药物神经阻滞引起的暂时性肌肉麻痹后抓握。3)我们建议
在不使用初始EMG测量的情况下开发这些控制算法,这是必要的,
为患者实施该系统。
英文摘要
The goal of this project is to develop a primate model of an upper extremity neuromuscularstimulation
system controlled by means of intra-cortical recording electrodes. Individuals with spinal cord injury become
paralyzed because they have lost the ability to activate their muscles. These patients' muscles can still be
made to contract if they are activated by means of electrical stimuli applied directly to the muscle or nerves.
Likewise, the areas of the brain that normally control movement are still active, but their connection to the
muscles has been lost as a result of the injury.
Researchers at Case Western Reserve University (CWRU) have demonstrated that implanted functional
electrical stimulation (FES) neuroprostheses can be used to restore grasp functions to individuals with
tetraplegia. Although remarkable, these systems are limited to pre-programmed grasp patterns, and require
considerable conscious attention. A more natural control system, with more degrees of freedom could
provide greatly improved function. At Northwestern, we have developed methods to predict the activity of
arm and hand muscles during grasping movements based on micro-electrode recordings from the brain of a
monkey. From a single, chronicallyimplanted array of electrodes, predictionscan be made of the activity of
shoulder, arm and hand muscles. This type of electrode has yielded maintained recordings for periods in
excess of 3 years, and it has recently been approved for experimental use in human patients. We believe that
intra-cortical recordings like these provide the potential for simultaneouscontrol of multipledegrees of
freedom through natural thought processes. By combining the strengths of the Northwestern and CWRU
groups, we propose to develop a brain-computer interface adequate for controlling a neuroprosthesis. The
development of a primate model of this neuroprosthetic system would be a major step toward its
implementation in human patients. This application includes the following specific aims:
1) We propose to use a 100-electrode array implanted in the primary motor cortex of a mnkey to provide the
input to a set of decoders designed to produce real-time predictions of the activity of particular hand muscles.
2) We propose to use the control algorithms developed in aim 1 and an implanted FES prosthesis to restore
grasp followingtemporary muscle paralysis induced by a pharmacological nerve block. 3) We propose to
develop these control algorithms without the use of initial EMG measurements, as would be necessary in
order to implement the system for a patient.
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海外基金