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中文摘要
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描述(由申请人提供):功能性电刺激包括通过植入电极对瘫痪肌肉进行人工激活,并已成功用于提高四肢瘫痪患者进行日常活动重要动作的能力。然而,由功能性电刺激产生的运动行为范围仅限于相对较小的一组预先编程的动作,如手的抓握和释放。由于识别引发特定运动所需的肌肉刺激模式存在重大挑战,因此尚未实现更大范围的运动。我们计划使用一种概率算法来预测基于手部轨迹信息的与广泛上肢运动相关的肌肉活动模式。预测的肌肉活动模式将被转换成振幅调制的脉冲序列,用于驱动肌肉刺激器,以唤起暂时瘫痪的动物的运动。被诱发的动作被定量地与期望的动作进行比较,以评估这种方法的整体有效性。最终,这种概率方法可以作为脑源性轨迹信息与现有功能电刺激系统之间的必要接口,实现自给自足、自我控制的上肢神经义肢系统。这样一个完整而灵活的系统将大大提高瘫痪患者的运动能力和独立性。公共卫生相关性:该项目的目标是开发一种新方法,通过植入肌肉的电极人工激活和控制瘫痪的肌肉。这项工作将有助于恢复因脊髓损伤或中风而瘫痪的个体的自主肢体运动。
英文摘要
DESCRIPTION (provided by applicant): Functional electrical stimulation involves artificial activation of paralyzed muscles with implanted electrodes and has been used successfully to improve the ability of quadriplegics to perform movements important for daily activities. The range of motor behaviors that can be generated by functional electrical stimulation, however, is limited to a relatively small set of preprogrammed movements such as hand grasp and release. A broader range of movements has not been implemented because of the substantial challenge associated with identifying the patterns of muscle stimulation needed to elicit specified movements. We plan to use a probabilistic algorithm to predict the patterns of muscle activity associated with a wide range of upper limb movements based on hand trajectory information. The predicted patterns of muscle activity will then be transformed into amplitude-modulated trains of pulses and used to drive muscle stimulators in order to evoke movements in temporarily paralyzed animals. The evoked movements are quantitatively compared to the desired movements to evaluate the overall effectiveness of this approach. Ultimately, this probabilistic method could serve as the requisite interface between brain-derived trajectory information and existing functional electrical stimulation systems to realize a self-contained and self-controlled upper limb neuroprosthetic system. Such an integrated and flexible system would greatly increase movement capability, and independence, in paralyzed individuals. PUBLIC HEALTH RELEVANCE: The goal of this project is to develop a new method to artificially activate and control paralyzed muscles with electrodes implanted in muscles. This effort will contribute to the restoration of voluntary limb movements in individuals paralyzed because of spinal cord injury or stroke.
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Physiological Function of Persistent Inward Currents in Motor Neurons
  • 批准号:
    10663030
  • 项目类别:
  • 资助金额:
    $40.84万
  • 财政年份:
    2023
  • 负责人:
    ANDREW J FUGLEVAND
  • 依托单位:
Hands-free Control of an Assistive Robotic Arm for High Level Paralysis
  • 批准号:
    10741948
  • 项目类别:
  • 资助金额:
    $14.66万
  • 财政年份:
    2023
  • 负责人:
    ANDREW J FUGLEVAND
  • 依托单位:
Machine-learning based control of functional electrical stimulation
  • 批准号:
    10319903
  • 项目类别:
  • 资助金额:
    $7.52万
  • 财政年份:
    2018
  • 负责人:
    ANDREW J FUGLEVAND
  • 依托单位:
Physiological significance of persistent inward currents in motor neurons
  • 批准号:
    8613509
  • 项目类别:
  • 资助金额:
    $12.51万
  • 财政年份:
    2013
  • 负责人:
    ANDREW J FUGLEVAND
  • 依托单位:
海外基金