• 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

使用增强现实眼镜进行无电极视觉假体/外骨骼控制的初步技术概念验证研究。

Electrode-free visual prosthesis/exoskeleton control using augmented reality glasses in a first proof-of-technical-concept study.

机构信息

Laboratory of Computer Assisted Medicine, Division of Medical Engineering, Department of Electrical Engineering, Medical Engineering and Computer Science, Offenburg University, Badstr. 24, 77652, Offenburg, Germany.

Laboratory of NeuroScience, Division of Medical Engineering, Department of Electrical Engineering, Medical Engineering and Computer Science, Offenburg University, Badstr. 24, 77652, Offenburg, Germany.

出版信息

Sci Rep. 2020 Oct 1;10(1):16279. doi: 10.1038/s41598-020-73250-6.

DOI:10.1038/s41598-020-73250-6
PMID:33004950
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7530745/
Abstract

In the field of neuroprosthetics, the current state-of-the-art method involves controlling the prosthesis with electromyography (EMG) or electrooculography/electroencephalography (EOG/EEG). However, these systems are both expensive and time consuming to calibrate, susceptible to interference, and require a lengthy learning phase by the patient. Therefore, it is an open challenge to design more robust systems that are suitable for everyday use and meet the needs of patients. In this paper, we present a new concept of complete visual control for a prosthesis, an exoskeleton or another end effector using augmented reality (AR) glasses presented for the first time in a proof-of-concept study. By using AR glasses equipped with a monocular camera, a marker attached to the prosthesis is tracked. Minimal relative movements of the head with respect to the prosthesis are registered by tracking and used for control. Two possible control mechanisms including visual feedback are presented and implemented for both a motorized hand orthosis and a motorized hand prosthesis. Since the grasping process is mainly controlled by vision, the proposed approach appears to be natural and intuitive.

摘要

在神经假肢领域,目前最先进的方法是使用肌电图(EMG)或眼电图/脑电图(EOG/EEG)来控制假肢。然而,这些系统既昂贵又需要长时间校准,容易受到干扰,并且需要患者进行长时间的学习阶段。因此,设计更强大、更适合日常使用并满足患者需求的系统仍然是一个开放的挑战。在本文中,我们提出了一种使用增强现实(AR)眼镜进行假肢、外骨骼或其他末端执行器的完全视觉控制的新概念,这是在概念验证研究中首次提出的。通过使用配备单目摄像头的 AR 眼镜,跟踪附着在假肢上的标记。通过跟踪和使用头部相对于假肢的最小相对运动来注册。为一个机动手矫形器和一个机动手假肢展示并实现了两种可能的包括视觉反馈的控制机制。由于抓取过程主要由视觉控制,因此所提出的方法似乎是自然和直观的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cd5/7530745/705a8b79b13b/41598_2020_73250_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cd5/7530745/9bdf12a06d16/41598_2020_73250_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cd5/7530745/05d9ad634ade/41598_2020_73250_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cd5/7530745/4872d09d9a53/41598_2020_73250_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cd5/7530745/bdc9b14f31cf/41598_2020_73250_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cd5/7530745/345880462ca4/41598_2020_73250_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cd5/7530745/2d8562fee4c5/41598_2020_73250_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cd5/7530745/fc9579194015/41598_2020_73250_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cd5/7530745/705a8b79b13b/41598_2020_73250_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cd5/7530745/9bdf12a06d16/41598_2020_73250_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cd5/7530745/05d9ad634ade/41598_2020_73250_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cd5/7530745/4872d09d9a53/41598_2020_73250_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cd5/7530745/bdc9b14f31cf/41598_2020_73250_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cd5/7530745/345880462ca4/41598_2020_73250_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cd5/7530745/2d8562fee4c5/41598_2020_73250_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cd5/7530745/fc9579194015/41598_2020_73250_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cd5/7530745/705a8b79b13b/41598_2020_73250_Fig8_HTML.jpg

相似文献

1
Electrode-free visual prosthesis/exoskeleton control using augmented reality glasses in a first proof-of-technical-concept study.使用增强现实眼镜进行无电极视觉假体/外骨骼控制的初步技术概念验证研究。
Sci Rep. 2020 Oct 1;10(1):16279. doi: 10.1038/s41598-020-73250-6.
2
EMG Biofeedback for online predictive control of grasping force in a myoelectric prosthesis.肌电图生物反馈用于肌电假肢抓握力的在线预测控制
J Neuroeng Rehabil. 2015 Jun 19;12:55. doi: 10.1186/s12984-015-0047-z.
3
Enhancing brain-machine interface (BMI) control of a hand exoskeleton using electrooculography (EOG).利用眼电图(EOG)增强对手部外骨骼的脑机接口(BMI)控制。
J Neuroeng Rehabil. 2014 Dec 16;11:165. doi: 10.1186/1743-0003-11-165.
4
Improving internal model strength and performance of prosthetic hands using augmented feedback.利用增强反馈提高假肢手的内部模型强度和性能。
J Neuroeng Rehabil. 2018 Jul 31;15(1):70. doi: 10.1186/s12984-018-0417-4.
5
An EEG/EOG-based hybrid brain-neural computer interaction (BNCI) system to control an exoskeleton for the paralyzed hand.一种基于脑电图/眼电图的混合式脑-神经计算机交互(BNCI)系统,用于控制瘫痪手部的外骨骼。
Biomed Tech (Berl). 2015 Jun;60(3):199-205. doi: 10.1515/bmt-2014-0126.
6
Closed-loop control of grasping with a myoelectric hand prosthesis: which are the relevant feedback variables for force control?肌电假手抓握的闭环控制:力控制的相关反馈变量有哪些?
IEEE Trans Neural Syst Rehabil Eng. 2014 Sep;22(5):1041-52. doi: 10.1109/TNSRE.2014.2318431. Epub 2014 Apr 29.
7
i-MYO: A multi-grasp prosthetic hand control system based on gaze movements, augmented reality, and myoelectric signals.i-MYO:一种基于眼球运动、增强现实和肌电信号的多抓握假肢手控制系统。
Int J Med Robot. 2024 Feb;20(1):e2617. doi: 10.1002/rcs.2617.
8
Stereovision and augmented reality for closed-loop control of grasping in hand prostheses.用于手部假肢抓握闭环控制的立体视觉与增强现实技术。
J Neural Eng. 2014 Aug;11(4):046001. doi: 10.1088/1741-2560/11/4/046001. Epub 2014 Jun 3.
9
Immersive augmented reality system for the training of pattern classification control with a myoelectric prosthesis.沉浸式增强现实系统,用于肌电假体模式分类控制训练。
J Neuroeng Rehabil. 2021 Feb 4;18(1):25. doi: 10.1186/s12984-021-00822-6.
10
Myocontrol is closed-loop control: incidental feedback is sufficient for scaling the prosthesis force in routine grasping.肌电控制是闭环控制:偶然的反馈足以对日常抓握中的假体力进行缩放。
J Neuroeng Rehabil. 2018 Sep 3;15(1):81. doi: 10.1186/s12984-018-0422-7.

引用本文的文献

1
Emerging Applications of Augmented and Mixed Reality Technologies in Motor Rehabilitation: A Scoping Review.增强现实和混合现实技术在运动康复中的新兴应用:一项范围综述
Sensors (Basel). 2025 Mar 25;25(7):2042. doi: 10.3390/s25072042.
2
Metaverse Wearables for Immersive Digital Healthcare: A Review.元宇宙可穿戴设备在沉浸式数字医疗保健中的应用:综述。
Adv Sci (Weinh). 2023 Nov;10(31):e2303234. doi: 10.1002/advs.202303234. Epub 2023 Sep 22.
3
Effects of targeted muscle reinnervation on spinal cord motor neurons in rats following tibial nerve transection.

本文引用的文献

1
Hybrid EEG/EOG-based brain/neural hand exoskeleton restores fully independent daily living activities after quadriplegia.基于脑电/肌电混合的脑/神经手外骨骼可帮助四肢瘫痪患者恢复完全独立的日常生活活动。
Sci Robot. 2016 Dec 6;1(1). doi: 10.1126/scirobotics.aag3296. Epub 2016 Nov 16.
2
Eyes are faster than hands: A soft wearable robot learns user intention from the egocentric view.眼睛比手快:一种柔软可穿戴机器人从自我中心视角学习用户意图。
Sci Robot. 2019 Jan 30;4(26). doi: 10.1126/scirobotics.aav2949.
3
Non-contact visual control of personalized hand prostheses/exoskeletons by tracking using augmented reality glasses.
胫神经横断后靶向肌肉再支配对大鼠脊髓运动神经元的影响。
Neural Regen Res. 2022 Aug;17(8):1827-1832. doi: 10.4103/1673-5374.332153.
通过使用增强现实眼镜进行跟踪实现对个性化手部假肢/外骨骼的非接触式视觉控制。
3D Print Med. 2020 Feb 24;6(1):6. doi: 10.1186/s41205-020-00059-4.
4
Fast, robust, and accurate monocular peer-to-peer tracking for surgical navigation.快速、鲁棒、准确的单目点对点手术导航跟踪。
Int J Comput Assist Radiol Surg. 2020 Mar;15(3):479-489. doi: 10.1007/s11548-019-02111-z. Epub 2020 Jan 16.
5
Smart Neuroprosthetics Becoming Smarter, but Not for Everyone?智能神经假肢变得越来越智能,但并非适用于所有人?
EClinicalMedicine. 2018 Sep 6;2-3:11-12. doi: 10.1016/j.eclinm.2018.08.005. eCollection 2018 Aug-Sep.
6
Biomimetic Intraneural Sensory Feedback Enhances Sensation Naturalness, Tactile Sensitivity, and Manual Dexterity in a Bidirectional Prosthesis.仿生神经内感觉反馈可增强双向假肢的感觉自然度、触觉灵敏度和手动灵巧度。
Neuron. 2018 Oct 10;100(1):37-45.e7. doi: 10.1016/j.neuron.2018.08.033. Epub 2018 Sep 20.
7
Demonstration of a semi-autonomous hybrid brain-machine interface using human intracranial EEG, eye tracking, and computer vision to control a robotic upper limb prosthetic.利用人类颅内脑电图、眼动追踪和计算机视觉控制机器人上肢假肢的半自主混合脑机接口演示。
IEEE Trans Neural Syst Rehabil Eng. 2014 Jul;22(4):784-96. doi: 10.1109/TNSRE.2013.2294685. Epub 2013 Dec 12.
8
Treatment of phantom limb pain (PLP) based on augmented reality and gaming controlled by myoelectric pattern recognition: a case study of a chronic PLP patient.基于肌电模式识别的增强现实和游戏控制治疗幻肢痛(PLP):一例慢性 PLP 患者的案例研究。
Front Neurosci. 2014 Feb 25;8:24. doi: 10.3389/fnins.2014.00024. eCollection 2014.
9
Restoring natural sensory feedback in real-time bidirectional hand prostheses.实时双向手部假肢恢复自然感觉反馈。
Sci Transl Med. 2014 Feb 5;6(222):222ra19. doi: 10.1126/scitranslmed.3006820.
10
Personalized neuroprosthetics.个性化神经假体。
Sci Transl Med. 2013 Nov 6;5(210):210rv2. doi: 10.1126/scitranslmed.3005968.