Improving the Performance, Robustness and Reliability of Myoelectric Control
提高肌电控制的性能、鲁棒性和可靠性
基本信息
- 批准号:RGPIN-2014-04920
- 负责人:
- 金额:$ 1.82万
- 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:2017
- 资助国家:加拿大
- 起止时间:2017-01-01 至 2018-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The loss or congenital absence of a limb is a major disability that can have considerable physical and psychological impact on the life of an amputee. It is estimated that there are more than 3 million upper limb amputees globally, with the rate of incidence growing steadily. The loss of an upper limb, in particular, can greatly affect an individual’s level of independence and self-esteem, as well as lead to overuse injuries of the neck, shoulders and back. Although upper limb prostheses have evolved considerably, the method of controlling them has changed little since the 1960s. These devices use the electromyogram (electrical signals generated while contracting muscles of the residual limb) to determine the intent of the user. Termed myoelectric control, this approach is functional and non-invasive, but commercially available systems provide limited control and can be unintuitive. Recently, significant advances in myoelectric control have been shown in the literature. Pattern-based approaches have shown the ability to control more motions, more intuitively, but robustness remains a concern. Our recent work has highlighted possibilities for greatly improving the reliability of these systems through algorithmic improvements and better understanding of confounding factors. Furthermore, we have identified flaws in the assumptions that form the basis of the standard design approach. The objective of this research is to apply these findings, using novel approaches in signal processing and system design, and novel pressure sensing technology to improve the control, performance and reliability of upper limb prosthetics, and human-machine interfaces in general.
肢体的丧失或先天缺失是一种主要的残疾,可能会对截肢者的生活产生相当大的生理和心理影响。据估计,全球有300多万上肢截肢者,发病率稳步增长。尤其是失去上肢,会极大地影响个人的独立性和自尊水平,并导致颈部、肩部和背部过度使用损伤。尽管上肢假肢已经有了很大的发展,但自20世纪60年代以来,控制上肢假肢的方法几乎没有改变。这些设备使用肌电(收缩残肢肌肉时产生的电信号)来确定使用者的意图。这种方法被称为肌电控制,是一种功能性和非侵入性的方法,但商业上可用的系统提供的控制有限,可能不直观。最近,文献中显示了肌电控制方面的重大进展。基于模式的方法已经显示出能够更直观地控制更多运动,但健壮性仍然是一个令人担忧的问题。我们最近的工作强调了通过改进算法和更好地了解混杂因素,极大地提高这些系统可靠性的可能性。此外,我们还发现了构成标准设计方法基础的假设中的缺陷。本研究的目的是应用这些发现,在信号处理和系统设计中使用新的方法,以及新的压力传感技术,以提高上肢假肢的控制、性能和可靠性,以及总体上的人机界面。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Scheme, Erik其他文献
Electromyogram pattern recognition for control of powered upper-limb prostheses: State of the art and challenges for clinical use
- DOI:
10.1682/jrrd.2010.09.0177 - 发表时间:
2011-01-01 - 期刊:
- 影响因子:0
- 作者:
Scheme, Erik;Englehart, Kevin - 通讯作者:
Englehart, Kevin
Fractal Analysis of Human Gait Variability via Stride Interval Time Series
- DOI:
10.3389/fphys.2020.00333 - 发表时间:
2020-04-15 - 期刊:
- 影响因子:4
- 作者:
Phinyomark, Angkoon;Larracy, Robyn;Scheme, Erik - 通讯作者:
Scheme, Erik
A long short-term recurrent spatial-temporal fusion for myoelectric pattern recognition
- DOI:
10.1016/j.eswa.2021.114977 - 发表时间:
2021-04-21 - 期刊:
- 影响因子:8.5
- 作者:
Khushaba, Rami N.;Scheme, Erik;Al-Jumaily, Adel - 通讯作者:
Al-Jumaily, Adel
Resolving the Limb Position Effect in Myoelectric Pattern Recognition
- DOI:
10.1109/tnsre.2011.2163529 - 发表时间:
2011-12-01 - 期刊:
- 影响因子:4.9
- 作者:
Fougner, Anders;Scheme, Erik;Stavdahl, Oyvind - 通讯作者:
Stavdahl, Oyvind
Motion Normalized Proportional Control for Improved Pattern Recognition-Based Myoelectric Control
- DOI:
10.1109/tnsre.2013.2247421 - 发表时间:
2014-01-01 - 期刊:
- 影响因子:4.9
- 作者:
Scheme, Erik;Lock, Blair;Englehart, Kevin - 通讯作者:
Englehart, Kevin
Scheme, Erik的其他文献
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{{ truncateString('Scheme, Erik', 18)}}的其他基金
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:
$ 1.82万 - 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:
$ 1.82万 - 项目类别:
Discovery Grants Program - Accelerator Supplements
Development of a Pressure-Based Gait Biometric for User Access Control
开发用于用户访问控制的基于压力的步态生物识别
- 批准号:
558340-2020 - 财政年份:2021
- 资助金额:
$ 1.82万 - 项目类别:
Alliance Grants
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:2021
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Accelerator Supplements
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:2021
- 资助金额:
$ 1.82万 - 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:2020
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Accelerator Supplements
Development of a Pressure-Based Gait Biometric for User Access Control
开发用于用户访问控制的基于压力的步态生物识别
- 批准号:
558340-2020 - 财政年份:2020
- 资助金额:
$ 1.82万 - 项目类别:
Alliance Grants
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:2020
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Improving the Performance, Robustness and Reliability of Myoelectric Control
提高肌电控制的性能、鲁棒性和可靠性
- 批准号:
RGPIN-2014-04920 - 财政年份:2019
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Concurrent EMG and EEG Analysis for Quantitative Motor Assessment
用于定量运动评估的同步肌电图和脑电图分析
- 批准号:
538323-2019 - 财政年份:2019
- 资助金额:
$ 1.82万 - 项目类别:
Engage Grants Program
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