Advanced Myoelectric Control for Improved Prosthetic Function

先进的肌电控制可改善假肢功能

基本信息

  • 批准号:
    RGPIN-2015-04736
  • 负责人:
  • 金额:
    $ 1.6万
  • 依托单位:
  • 依托单位国家:
    加拿大
  • 项目类别:
    Discovery Grants Program - Individual
  • 财政年份:
    2018
  • 资助国家:
    加拿大
  • 起止时间:
    2018-01-01 至 2019-12-31
  • 项目状态:
    已结题

项目摘要

Human movement is a complex process and as the number of movements increase, the processes involved become even more complicated. Surface electromyography (sEMG) is one method of monitoring the electrical activity that results from muscle contraction muscle behaviour and gaining further insight into neuromuscular function. ******The long-term goal of my research program is to use new technologies to better understand neuromuscular function and voluntary movement and to develop more robust dynamic muscle models. The short-term objectives of my research are to examine the variety of factors that affect neuromuscular function using advanced techniques including sEMG and dynamic force measures. One method to observe neuromuscular function is through the use of surface electrodes to record myoelectric signals (MES) from contracting muscles. The MES measures the result of the neural commands sent to the muscle and can provide information regarding the neural mechanisms responsible for deficiencies and function. Traditionally, surface electrodes record activity and the number of available channels on a data acquisition system limits the number of muscles measured. Recently, advances in MES processing have resulted in new techniques, which are more robust. High-density electromyography (HD-EMG) allows the acquisition of significantly greater numbers of signal channels and therefore greater information. These new systems allow for the development of topographical maps, which can then be used to further study muscle activation patterns. ******The data obtained from HD-EMG systems will allow researchers to better investigate interlimb coordination (i.e. the coordination of more than one limb) and neuromuscular function in movement efficiency and to develop better models of human movement. This has applications in a number of different fields and occupational settings from industrial ergonomics to biomechanics. The advancement of this technology to newer, wireless HD-EMG systems has enabled researchers to investigate function without restriction and in practical settings. This research will also help to develop better prosthesis control systems and advance robotics (e.g. external dermoskeletons). The development of new signal processing techniques, including novel methods of utilizing the data collected from HDEMG will help to advance research. **
人体运动是一个复杂的过程,随着运动数量的增加,所涉及的过程变得更加复杂。表面肌电图(sEMG)是监测由肌肉收缩肌肉行为引起的电活动并进一步了解神经肌肉功能的一种方法。** 我的研究计划的长期目标是使用新技术来更好地了解神经肌肉功能和随意运动,并开发更强大的动态肌肉模型。我的研究的短期目标是使用先进的技术,包括表面肌电图和动态力的措施,检查影响神经肌肉功能的各种因素。观察神经肌肉功能的一种方法是通过使用表面电极来记录来自收缩肌肉的肌电信号(MES)。MES测量发送到肌肉的神经命令的结果,并可以提供有关负责缺陷和功能的神经机制的信息。传统上,表面电极记录活动,数据采集系统上可用通道的数量限制了测量的肌肉数量。最近,MES处理的进步导致了新技术的出现,这些技术更加强大。高密度肌电图(HD-EMG)可以采集更多的信号通道,从而获得更多的信息。这些新系统允许开发地形图,然后可以用于进一步研究肌肉激活模式。** 从HD-EMG系统获得的数据将使研究人员能够更好地研究肢体间协调(即多个肢体的协调)和运动效率中的神经肌肉功能,并开发更好的人体运动模型。这在许多不同的领域和职业环境中有应用,从工业人机工程学到生物力学。这项技术的进步,更新,无线HD-EMG系统,使研究人员能够调查功能不受限制,并在实际设置。这项研究还将有助于开发更好的假肢控制系统和先进的机器人技术(例如外部皮骨骼)。开发新的信号处理技术,包括利用从HDEMG收集的数据的新方法,将有助于推进研究。**

项目成果

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Kuruganti, Usha其他文献

Effect of age and sex on strength and spatial electromyography during knee extension
  • DOI:
    10.1186/s40101-020-00219-9
  • 发表时间:
    2020-04-15
  • 期刊:
  • 影响因子:
    3.1
  • 作者:
    Pradhan, Ashirbad;Malagon, Gemma;Kuruganti, Usha
  • 通讯作者:
    Kuruganti, Usha
The bilateral leg strength deficit is present in old, young and adolescent females during isokinetic knee extension and flexion
Bilateral deficit expressions and myoelectric signal activity during submaximal and maximal isometric knee extensions in young, athletic males
High density electromyography data of normally limbed and transradial amputee subjects for multifunction prosthetic control
  • DOI:
    10.1016/j.jelekin.2011.12.012
  • 发表时间:
    2012-06-01
  • 期刊:
  • 影响因子:
    2.5
  • 作者:
    Daley, Heather;Englehart, Kevin;Kuruganti, Usha
  • 通讯作者:
    Kuruganti, Usha
Sensors for monitoring workplace health

Kuruganti, Usha的其他文献

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{{ truncateString('Kuruganti, Usha', 18)}}的其他基金

Infrastructure for Human Movement Analysis
人体运动分析基础设施
  • 批准号:
    RTI-2023-00080
  • 财政年份:
    2022
  • 资助金额:
    $ 1.6万
  • 项目类别:
    Research Tools and Instruments
Advanced Methods of Human Machine Interface for Improved Myoelectric Control
改进肌电控制的人机界面先进方法
  • 批准号:
    RGPIN-2021-02638
  • 财政年份:
    2022
  • 资助金额:
    $ 1.6万
  • 项目类别:
    Discovery Grants Program - Individual
Advanced Methods of Human Machine Interface for Improved Myoelectric Control
改进肌电控制的人机界面先进方法
  • 批准号:
    RGPIN-2021-02638
  • 财政年份:
    2021
  • 资助金额:
    $ 1.6万
  • 项目类别:
    Discovery Grants Program - Individual
Advanced Myoelectric Control for Improved Prosthetic Function
先进的肌电控制可改善假肢功能
  • 批准号:
    RGPIN-2015-04736
  • 财政年份:
    2019
  • 资助金额:
    $ 1.6万
  • 项目类别:
    Discovery Grants Program - Individual
Advanced Myoelectric Control for Improved Prosthetic Function
先进的肌电控制可改善假肢功能
  • 批准号:
    RGPIN-2015-04736
  • 财政年份:
    2017
  • 资助金额:
    $ 1.6万
  • 项目类别:
    Discovery Grants Program - Individual
Biomedical Engineering Research for Insole Wearable Sensors
鞋垫可穿戴传感器的生物医学工程研究
  • 批准号:
    492421-2015
  • 财政年份:
    2016
  • 资助金额:
    $ 1.6万
  • 项目类别:
    Engage Grants Program
Advanced Myoelectric Control for Improved Prosthetic Function
先进的肌电控制可改善假肢功能
  • 批准号:
    RGPIN-2015-04736
  • 财政年份:
    2016
  • 资助金额:
    $ 1.6万
  • 项目类别:
    Discovery Grants Program - Individual
Advanced Myoelectric Control for Improved Prosthetic Function
先进的肌电控制可改善假肢功能
  • 批准号:
    RGPIN-2015-04736
  • 财政年份:
    2015
  • 资助金额:
    $ 1.6万
  • 项目类别:
    Discovery Grants Program - Individual
Myoelectric signal analysis and muscle modeling
肌电信号分析和肌肉建模
  • 批准号:
    298131-2009
  • 财政年份:
    2013
  • 资助金额:
    $ 1.6万
  • 项目类别:
    Discovery Grants Program - Individual
Ergonomic Evaluation of Cymbal Manufacturing
镲片制造的人体工程学评估
  • 批准号:
    461356-2013
  • 财政年份:
    2013
  • 资助金额:
    $ 1.6万
  • 项目类别:
    Engage Grants Program

相似海外基金

Multichannel Surface Electromyography Techniques and Myoelectric Control
多通道表面肌电技术和肌电控制
  • 批准号:
    571588-2022
  • 财政年份:
    2022
  • 资助金额:
    $ 1.6万
  • 项目类别:
    University Undergraduate Student Research Awards
End-to-end Reinforcement Learning for Myoelectric Control
肌电控制的端到端强化学习
  • 批准号:
    559280-2021
  • 财政年份:
    2022
  • 资助金额:
    $ 1.6万
  • 项目类别:
    Alexander Graham Bell Canada Graduate Scholarships - Doctoral
Pattern Recognition Based Myoelectric Control for Emerging Human-Machine Interfaces
基于模式识别的新兴人机界面肌电控制
  • 批准号:
    RGPIN-2020-04776
  • 财政年份:
    2022
  • 资助金额:
    $ 1.6万
  • 项目类别:
    Discovery Grants Program - Individual
Clinical Validation of Myoelectric Implant for Intuitive Prosthesis Control
用于直观假肢控制的肌电植入物的临床验证
  • 批准号:
    10290697
  • 财政年份:
    2022
  • 资助金额:
    $ 1.6万
  • 项目类别:
Advanced Methods of Human Machine Interface for Improved Myoelectric Control
改进肌电控制的人机界面先进方法
  • 批准号:
    RGPIN-2021-02638
  • 财政年份:
    2022
  • 资助金额:
    $ 1.6万
  • 项目类别:
    Discovery Grants Program - Individual
Pattern Recognition Based Myoelectric Control for Emerging Human-Machine Interfaces
基于模式识别的新兴人机界面肌电控制
  • 批准号:
    RGPAS-2020-00109
  • 财政年份:
    2022
  • 资助金额:
    $ 1.6万
  • 项目类别:
    Discovery Grants Program - Accelerator Supplements
Novel Machine Learning Methods for Robust Myoelectric Control
用于鲁棒肌电控制的新型机器学习方法
  • 批准号:
    RGPIN-2021-02627
  • 财政年份:
    2022
  • 资助金额:
    $ 1.6万
  • 项目类别:
    Discovery Grants Program - Individual
Developing a virtual training environment for semi-autonomous Myoelectric prosthetic hand control
开发半自主肌电假手控制虚拟训练环境
  • 批准号:
    561537-2021
  • 财政年份:
    2021
  • 资助金额:
    $ 1.6万
  • 项目类别:
    University Undergraduate Student Research Awards
Novel Machine Learning Methods for Robust Myoelectric Control
用于鲁棒肌电控制的新型机器学习方法
  • 批准号:
    RGPIN-2021-02627
  • 财政年份:
    2021
  • 资助金额:
    $ 1.6万
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    Discovery Grants Program - Individual
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基于模式识别的新兴人机界面肌电控制
  • 批准号:
    RGPAS-2020-00109
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    2021
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  • 项目类别:
    Discovery Grants Program - Accelerator Supplements
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