Advanced Myoelectric Control for Improved Prosthetic Function
Advanced Myoelectric Control for Improved Prosthetic Function
批准号:
RGPIN-2015-04736
负责人:
Kuruganti, Usha
金额:
$1.6万
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2019
资助国家:
加拿大
项目状态:
已结题
起止时间:
2019-01-01 至 2020-12-31
中文摘要
人类的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)是一种监测由肌肉收缩行为引起的电活动的方法,可以进一步了解神经肌肉功能。******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自主运动,并开发更强大的动态肌肉模型。我研究的短期目标是使用先进的技术,包括肌电图和动态力测量,来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收缩肌肉的肌电信号。MES测量发送到肌肉的神经指令的结果,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,表面电极记录活动和数据采集系统上可用通道的数量限制了测量肌肉的数量。最近,MES处理的进步产生了更强大的新技术。高密度肌电图(HD-EMG)可以获得大量的信号通道,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,并开发更好的人类运动模型。这在许多不同的领域和职业环境中都有应用,从工业人体工程学到生物力学。这项技术的进步,无线HD-EMG系统,使研究人员能够不受限制地研究功能,并在实际环境中。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(例如外部皮肤骨骼)。新的信号处理技术的发展,包括利用从HDEMG收集的数据的新方法,将有助于推进研究。**
英文摘要
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. **
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会议论文
Infrastructure for Human Movement Analysis
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批准号:RTI-2023-00080
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项目类别:Research Tools and Instruments
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资助金额:$5.28万
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财政年份:2022
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负责人:Kuruganti, Usha
-
依托单位:
Advanced Methods of Human Machine Interface for Improved Myoelectric Control
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批准号:RGPIN-2021-02638
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项目类别:Discovery Grants Program - Individual
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资助金额:$2.04万
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财政年份:2022
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负责人:Kuruganti, Usha
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依托单位:
Advanced Methods of Human Machine Interface for Improved Myoelectric Control
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批准号:RGPIN-2021-02638
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项目类别:Discovery Grants Program - Individual
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资助金额:$2.04万
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财政年份:2021
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负责人:Kuruganti, Usha
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依托单位:
Advanced Myoelectric Control for Improved Prosthetic Function
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批准号:RGPIN-2015-04736
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项目类别:Discovery Grants Program - Individual
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资助金额:$1.6万
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财政年份:2018
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负责人:Kuruganti, Usha
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依托单位:
Advanced Myoelectric Control for Improved Prosthetic Function
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批准号:RGPIN-2015-04736
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项目类别:Discovery Grants Program - Individual
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资助金额:$1.6万
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财政年份:2017
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负责人:Kuruganti, Usha
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依托单位:
Biomedical Engineering Research for Insole Wearable Sensors
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批准号:492421-2015
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项目类别:Engage Grants Program
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资助金额:$1.82万
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财政年份:2016
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负责人:Kuruganti, Usha
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依托单位:
Advanced Myoelectric Control for Improved Prosthetic Function
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批准号:RGPIN-2015-04736
-
项目类别:Discovery Grants Program - Individual
-
资助金额:$1.6万
-
财政年份:2016
-
负责人:Kuruganti, Usha
-
依托单位:
Advanced Myoelectric Control for Improved Prosthetic Function
-
批准号:RGPIN-2015-04736
-
项目类别:Discovery Grants Program - Individual
-
资助金额:$1.6万
-
财政年份:2015
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负责人:Kuruganti, Usha
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依托单位:
Myoelectric signal analysis and muscle modeling
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批准号:298131-2009
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项目类别:Discovery Grants Program - Individual
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资助金额:$1.53万
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财政年份:2013
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负责人:Kuruganti, Usha
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依托单位:
Ergonomic Evaluation of Cymbal Manufacturing
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批准号:461356-2013
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项目类别:Engage Grants Program
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资助金额:$1.82万
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财政年份:2013
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负责人:Kuruganti, Usha
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依托单位:
Evaluation and Design Progression of a Video Gaming Station
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批准号:436912-2012
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项目类别:Engage Grants Program
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资助金额:$1.82万
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财政年份:2012
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负责人:Kuruganti, Usha
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依托单位:
Myoelectric signal analysis and muscle modeling
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批准号:298131-2009
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项目类别:Discovery Grants Program - Individual
-
资助金额:$1.53万
-
财政年份:2012
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负责人:Kuruganti, Usha
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依托单位:
Myoelectric signal analysis and muscle modeling
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批准号:298131-2009
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项目类别:Discovery Grants Program - Individual
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资助金额:$1.53万
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财政年份:2011
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负责人:Kuruganti, Usha
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依托单位:
Myoelectric signal analysis and muscle modeling
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批准号:298131-2009
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项目类别:Discovery Grants Program - Individual
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资助金额:$1.53万
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财政年份:2010
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负责人:Kuruganti, Usha
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依托单位:
Myoelectric signal analysis and muscle modeling
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批准号:298131-2009
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项目类别:Discovery Grants Program - Individual
-
资助金额:$1.53万
-
财政年份:2009
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负责人:Kuruganti, Usha
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依托单位:
PGSB/ESB
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批准号:222543-1999
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项目类别:Postgraduate Scholarships
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资助金额:$1.39万
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财政年份:2000
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负责人:Kuruganti, Usha
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依托单位:
PGSB/ESB
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批准号:222543-1999
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项目类别:Postgraduate Scholarships
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资助金额:$1.39万
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财政年份:1999
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负责人:Kuruganti, Usha
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依托单位:
海外基金