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:
    2019
  • 资助国家:
    加拿大
  • 起止时间:
    2019-01-01 至 2020-12-31
  • 项目状态:
    已结题

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.
肢体的丧失或先天性缺失是一种严重的残疾,对截肢者的生活会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,发病率稳步上升。特别是上肢的丧失,会极大地影响一个人的独立性和自尊水平,并导致颈部、肩部和背部的过度使用损伤。虽然上肢假肢已经有了很大的发展,但自20世纪60年代以来,控制它们的方法几乎没有改变。这些设备使用肌电图(在收缩残肢肌肉时产生的电信号)来确定用户的意图。这种方法被称为肌电控制,是功能性的和非侵入性的,但是商业上可用的系统提供有限的控制并且可能是不直观的。** 最近,文献中已经显示了肌电控制的重大进展。基于模式的方法已经显示出更直观地控制更多运动的能力,但鲁棒性仍然是一个问题。我们最近的工作强调了通过算法改进和更好地了解混杂因素来大大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,使用新的方法在信号处理和系统设计,和新的压力传感技术,以提高控制,性能和可靠性的上肢假肢,和人机界面一般。

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)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

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
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
Motion Normalized Proportional Control for Improved Pattern Recognition-Based Myoelectric Control
Resolving the Limb Position Effect in Myoelectric Pattern Recognition

Scheme, Erik的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ 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
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:
    RGPAS-2020-00109
  • 财政年份:
    2020
  • 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:
    2020
  • 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
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:
    2018
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual

相似海外基金

From mine to client: improving the performance, robustness and resilience of mineral supply chain logistics systems
从矿山到客户:提高矿产供应链物流系统的性能、稳健性和弹性
  • 批准号:
    577201-2022
  • 财政年份:
    2022
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Alliance Grants
Digitally networked dynamical systems: Performance and robustness analysis
数字网络动力系统:性能和鲁棒性分析
  • 批准号:
    DP210103272
  • 财政年份:
    2021
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Projects
RAPID: Improving Capabilities to Measure the Robustness of Critical Communications Infrastructure: A Case Study of COVID-19 Quarantine-Induced Internet Performance
RAPID:提高衡量关键通信基础设施稳健性的能力:COVID-19 隔离引起的互联网性能案例研究
  • 批准号:
    2028506
  • 财政年份:
    2020
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Standard Grant
FET: Small: Modeling, Simulation, and Design for Robustness and Performance in Semiconductor-Based Quantum Computing
FET:小型:基于半导体的量子计算的鲁棒性和性能的建模、仿真和设计
  • 批准号:
    2007200
  • 财政年份:
    2020
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Standard Grant
FMitF: Track II: Usability, Robustness, and Performance Improvements for CIVL
FMITF:轨道 II:CIVL 的可用性、稳健性和性能改进
  • 批准号:
    2019309
  • 财政年份:
    2020
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Standard Grant
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:
    2018
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Development of robustness evaluation method for river levees against floods and earthquakes for performance-based design
开发基于性能的设计的河堤抗洪水和地震的鲁棒性评估方法
  • 批准号:
    17H01290
  • 财政年份:
    2017
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Grant-in-Aid for Scientific Research (A)
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:
    2017
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
PFI:AIR - TT: Improving Robustness of Nanoscale Threshold Logic based Digitial Circuits and the Performance of Design Algorithms
PFI:AIR - TT:提高基于纳米级阈值逻辑的数字电路的鲁棒性和设计算法的性能
  • 批准号:
    1701241
  • 财政年份:
    2017
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Standard Grant
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:
    2016
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了