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Non-Invasive System for Identifying Motoneuron Behavior

Non-Invasive System for Identifying Motoneuron Behavior
用于识别运动神经元行为的非侵入性系统
批准号:
8391692
负责人:
Gianluca De Luca
金额:
$31.86万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-12-01 至 2013-11-30

项目摘要

项目成果

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中文摘要
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英文摘要
DESCRIPTION (provided by applicant): This Phase I SBIR describes the first step towards the commercial development of an innovative technology for recording and decomposing the surface electromyographic (sEMG) signal into its constituent motor unit action potentials (motoneuron firings). The proposed SBIR will provide a much needed mechanism to further develop, harden, and make more user-friendly technology developed in our laboratory under the support of a parent R01. The impact of this project will be to provide the research community-at-large a tool to perform motor control investigations based on motoneuron firing behavior not otherwise possible, and to explore the workings of the normal or dysfunctional neuromuscular system. There are no commercially available systems designed for this purpose. In response to insistent requests from colleagues we have provided our lab-based technology in its un refined form to a few of them. The objective of Phase I is to establish the merit/feasibility of the R&D effort for Phase II by developing and testing key elements of a marketable system. The approach will combine our proven product-development skills as the leading sEMG company in the world, with our laboratory-based R&D that has developed the state-of-the art MU decomposition technology. Phase I will begin: a) transferring the current disparate laboratory-based software components for recording sEMG signals in a manner that makes them conducive for decomposition by the algorithms in an organized and easy to use commercial platform (Aim 1); developing new post-processing analysis software in a user-friendly format that broadens the ability of researchers to analyze MU firings (Aim 2); and c) expanding the current technology to enable the analysis of MUs during single-cycle upper limb movements, and prepare for Phase II analysis of gait and other functional applications (Aim 3). Evaluation and feedback from prospective end users will guide the aims towards a marketable system. The proposed deliverable at the end of Phase II will consist of: i) a body-worn data-logger (to be developed in Phase II by adapting proven technology from our product line) that supports either stationary or ambulatory recording of sensor data, and ii) PC-based decomposition software (developed in Phase I and II) that enables the researcher to easily set up data collection experiments, monitor signal quality, manage data files, perform offline decomposition, and provide selectable MU data plots and advanced analyses.
期刊论文(2)
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科研奖励(0)
会议论文
Is the notion of central fatigue based on a solid foundation?
中枢疲劳的概念有坚实的基础吗?
DOI: 10.1152/jn.00889.2015
发表时间: 2016
期刊: Journal of neurophysiology
影响因子: 2.5
作者: [Contessa,Paola, Puleo,Alessio, DeLuca,CarloJ]
通讯作者: DeLuca,CarloJ
SpeechSense: An Interactive Sensor Platform for Speech Therapy
  • 批准号:
    10256832
  • 项目类别:
  • 资助金额:
    $25.46万
  • 财政年份:
    2022
  • 负责人:
    Gianluca De Luca
  • 依托单位:
Adaptive & Individualized AAC
  • 批准号:
    10600065
  • 项目类别:
  • 资助金额:
    $58.49万
  • 财政年份:
    2019
  • 负责人:
    Gianluca De Luca
  • 依托单位:
EMG Voice Restoration
  • 批准号:
    10009728
  • 项目类别:
  • 资助金额:
    $50.63万
  • 财政年份:
    2018
  • 负责人:
    Gianluca De Luca
  • 依托单位:
EMG Voice Restoration
  • 批准号:
    10376786
  • 项目类别:
  • 资助金额:
    $58.08万
  • 财政年份:
    2018
  • 负责人:
    Gianluca De Luca
  • 依托单位:
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