• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

利用外周信息控制手部假肢。

Control of hand prostheses using peripheral information.

机构信息

ARTS Lab, Scuola Superiore Sant'Anna, 56127 Pisa, Italy.

出版信息

IEEE Rev Biomed Eng. 2010;3:48-68. doi: 10.1109/RBME.2010.2085429.

DOI:10.1109/RBME.2010.2085429
PMID:22275201
Abstract

Several efforts have been carried out to enhance dexterous hand prosthesis control by impaired individuals. Choosing which voluntary signal to use for control purposes is a critical element to achieve this goal. This review presents and discusses the recent results achieved by using electromyographic signals, recorded either with surface (sEMG) or intramuscular (iEMG) electrodes, and electroneurographic (ENG) signals. The potential benefits and shortcomings of the different approaches are described with a particular attention to the definition of all the steps required to achieve an effective hand prosthesis control in the different cases. Finally, a possible roadmap in the field is also presented.

摘要

已经开展了多项工作来增强残疾个体对手灵巧假肢的控制能力。选择用于控制目的的自愿信号是实现这一目标的关键因素。本文综述了使用肌电图信号(通过表面电极 [sEMG] 或肌内电极 [iEMG] 记录)和神经电图信号(ENG)所取得的最新研究成果。描述了不同方法的潜在优势和缺点,并特别关注在不同情况下实现手灵巧假肢有效控制所需的所有步骤的定义。最后,还提出了该领域的可能发展方向。

相似文献

1
Control of hand prostheses using peripheral information.利用外周信息控制手部假肢。
IEEE Rev Biomed Eng. 2010;3:48-68. doi: 10.1109/RBME.2010.2085429.
2
Relationship between grasping force and features of single-channel intramuscular EMG signals.抓握力与单通道肌内 EMG 信号特征之间的关系。
J Neurosci Methods. 2009 Dec 15;185(1):143-50. doi: 10.1016/j.jneumeth.2009.09.006. Epub 2009 Sep 10.
3
Surface EMG in advanced hand prosthetics.先进手部假肢中的表面肌电图
Biol Cybern. 2009 Jan;100(1):35-47. doi: 10.1007/s00422-008-0278-1. Epub 2008 Nov 18.
4
Estimation of the knee joint angle from surface electromyographic signals for active control of leg prostheses.基于表面肌电信号估计膝关节角度以实现腿部假肢的主动控制。
Physiol Meas. 2009 Sep;30(9):931-46. doi: 10.1088/0967-3334/30/9/005. Epub 2009 Aug 6.
5
Pattern recognition of hand movements with low density sEMG for prosthesis control purposes.用于假肢控制目的的基于低密度表面肌电信号的手部动作模式识别
IEEE Int Conf Rehabil Robot. 2013 Jun;2013:6650361. doi: 10.1109/ICORR.2013.6650361.
6
Comparing Surface and Intramuscular Electromyography for Simultaneous and Proportional Control Based on a Musculoskeletal Model: A Pilot Study.基于肌肉骨骼模型的表面肌电与肌内肌电同步和比例控制比较:一项初步研究。
IEEE Trans Neural Syst Rehabil Eng. 2018 Sep;26(9):1735-1744. doi: 10.1109/TNSRE.2018.2859833. Epub 2018 Jul 25.
7
Classification of finger activation for use in a robotic prosthesis arm.用于机器人假肢手臂的手指激活分类。
IEEE Trans Neural Syst Rehabil Eng. 2002 Dec;10(4):290-3. doi: 10.1109/TNSRE.2002.806831.
8
Technology and instrumentation for detection and conditioning of the surface electromyographic signal: state of the art.用于表面肌电信号检测与调理的技术和仪器:现状
Clin Biomech (Bristol). 2009 Feb;24(2):122-34. doi: 10.1016/j.clinbiomech.2008.08.006. Epub 2008 Nov 29.
9
Intelligent multifunction myoelectric control of hand prostheses.智能多功能假手肌电控制
J Med Eng Technol. 2002 Jul-Aug;26(4):139-46. doi: 10.1080/03091900210142459.
10
[Research on proportional control system of prosthetic hand based on FMG signals].基于功能性肌肉群(FMG)信号的假手比例控制系统研究
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2013 Feb;30(1):39-44.

引用本文的文献

1
Surface electromyography markers of motor learning during laparoscopic skill acquisition: associations with performance and movement efficiency.腹腔镜技能习得过程中运动学习的表面肌电图标志物:与操作表现和运动效率的关联
J Robot Surg. 2025 Jun 28;19(1):330. doi: 10.1007/s11701-025-02505-z.
2
Phasor-Based Myoelectric Synergy Features: A Fast Hand-Crafted Feature Extraction Scheme for Boosting Performance in Gait Phase Recognition.基于相量的肌电协同特征:一种快速手工特征提取方案,用于提高步态相位识别性能。
Sensors (Basel). 2024 Sep 8;24(17):5828. doi: 10.3390/s24175828.
3
Improvement of hand functions of spinal cord injury patients with electromyography-driven hand exoskeleton: A feasibility study.
肌电图驱动的手部外骨骼对脊髓损伤患者手部功能的改善:一项可行性研究。
Wearable Technol. 2021 Jan 5;1:e8. doi: 10.1017/wtc.2020.9. eCollection 2020.
4
Dual Stream Long Short-Term Memory Feature Fusion Classifier for Surface Electromyography Gesture Recognition.双通道长短时记忆特征融合分类器用于表面肌电手势识别。
Sensors (Basel). 2024 Jun 4;24(11):3631. doi: 10.3390/s24113631.
5
Intelligent Human-Computer Interaction: Combined Wrist and Forearm Myoelectric Signals for Handwriting Recognition.智能人机交互:用于手写识别的腕部和前臂肌电信号联合应用
Bioengineering (Basel). 2024 May 4;11(5):458. doi: 10.3390/bioengineering11050458.
6
A Sensory Feedback Neural Stimulator Prototype for Both Implantable and Wearable Applications.一种适用于植入式和可穿戴应用的感觉反馈神经刺激器原型。
Micromachines (Basel). 2024 Mar 30;15(4):480. doi: 10.3390/mi15040480.
7
Continuous Motion Estimation of Knee Joint Based on a Parameter Self-Updating Mechanism Model.基于参数自更新机制模型的膝关节连续运动估计
Bioengineering (Basel). 2023 Aug 31;10(9):1028. doi: 10.3390/bioengineering10091028.
8
Stimulation of peroneal nerves reveals maintained somatosensory representation in transtibial amputees.刺激腓总神经显示经胫截肢者的体感表征得以保留。
Front Hum Neurosci. 2023 Sep 7;17:1240937. doi: 10.3389/fnhum.2023.1240937. eCollection 2023.
9
Recent trends and challenges of surface electromyography in prosthetic applications.表面肌电图在假肢应用中的最新趋势与挑战
Biomed Eng Lett. 2023 Apr 22;13(3):353-373. doi: 10.1007/s13534-023-00281-z. eCollection 2023 Aug.
10
Regenerative Peripheral Nerve Interface Surgery: Anatomic and Technical Guide.再生周围神经接口手术:解剖学与技术指南。
Plast Reconstr Surg Glob Open. 2023 Jul 17;11(7):e5127. doi: 10.1097/GOX.0000000000005127. eCollection 2023 Jul.