Summary

人机界面集成的低成本传感器,具有神经肌肉电刺激系统中风后康复平衡

Published: April 12, 2016
doi:

Summary

A novel low-cost human-machine interface for interactive post-stroke balance rehabilitation system is presented in this article. The system integrates off-the-shelf low-cost sensors towards volitionally driven electrotherapy paradigm. The proof-of-concept software interface is demonstrated on healthy volunteers.

Abstract

当在大脑中携带来自心脏血液的区域的动脉脉冲串或凝块阻碍血液流向脑部,从而防止氧和营养物质的递送中风引起。大约有一半的中风幸存者留下了某种程度的残疾。恢复性神经康复方法的创新迫切需要,以减少长期残疾。神经系统的重组其结构,功能和连接,以本征或外在刺激的响应的能力被称为神经可塑性。神经可塑性涉及脑卒中后功能障碍,而且在康复。有利neuroplastic改变可能与非侵入性的电疗变得容易,如神经肌肉电刺激(NMES)和感官电刺激(SES)。 NMES涉及运动神经和肌肉的协调电刺激电流的连续的短脉冲而SES invo激活它们感觉神经的LVES刺激导致从几乎没有感知到高度不愉快而变化的感觉电流。在这里,在康复过程积极皮质参与可能通过驱动与生物信号表示同步有源感知和意志努力非侵入电疗(肌电图(EMG),脑电图(EEG),眼电(EOG))来促进。要在资源贫乏的设置, 例如 ,在低收入和中等收入国家实现这一目标,我们在场外的现成视频游戏传感器技术利用最新进展提出了一种低成本的人机界面(HMI)。在本文中,我们讨论了低成本的现成的架子传感器具有无创电疗视觉听觉生物反馈,以帮助平衡康复过程中姿势控制集成了开源软件的界面。我们证明对健康志愿者的证明了概念。

Introduction

引起的脑,脊髓或视网膜梗死神经功能障碍的一个插曲叫脑卒中1。中风是一个全球性的健康问题和残疾全球1的第四大原因。在像印度和中国,世界上人口最多的两个国家的国家,因中风神经功能障碍被标记为隐藏疫情2。一中风后的最常见的医疗并发症的是具有高达73%的在第一年后中风3报告发病瀑布。在中风后下跌是多方面的,既包括脊柱脊髓上和因素,如平衡和视觉空间忽视4。通过Geurts并确定1同仁5综述)多方位受损最大重量双足站立,2)速度慢,3)定向的不精确性,和中移动4)单环子最大额面重量的变化如天平上小幅度因素秋天里SK。在日常活动所造成的影响可能是显著因为以前的作品表明,平衡与粗大运动功能5,6日间能力和独立性有关。此外,Geurts和同事5建议除了肌力脊髓上多感觉整合(和肌肉协调7)是用于其缺乏当前协议平衡恢复的关键。对多感觉整合,我们对volitionally驱动的非侵入性的电疗假设8(NMES / SES)的是,这个适应性行为可以被塑造和患肢,使的NMES / SES辅助运动中调节的感觉输入活跃知觉便利大脑可以招募交替运动通路9,如果需要,将这一信息反馈到后续的运动输出。

为了实现资源volitionally驱动NMES / SES辅助平衡训练国定贫困设定,低成本的人机界面(HMI)是通过利用现有的开源软件和最新进展在场外的现成的视频游戏传感器技术视觉听觉的生物反馈开发的。 NMES涉及已被证实可以改善肌肉强度和降低痉挛10神经和肌肉的协调电刺激。此外,SES涉及感觉神经的刺激电流唤起的感觉,其中前期发表的作品11表明应用subsensory刺激在胫前肌单是有效的衰减姿势摆动。在这里,人机将互动中风后平衡疗法,其中volitionally驱动NMES / SES的脚踝肌肉会作为一个肌肉放大器(与NMES),以及增强传入反馈(与SES)期间成为可能感觉运动统合协助健康脚踝战略12,13,14中姿势摇摆,以保持直立姿态。这是根据杜塔 8提出的假设,即通过非侵入性的电疗影响相关的脚踝肌肉的增加皮质兴奋性,可能使踝关节僵硬的改善脊髓以上调制。事实上,先前的工作已经表明,NMES / SES引起在皮质兴奋性持久的变化,可能作为共活化运动和感觉纤维15,16的结果。此外,Khaslavskaia和Sinkjaer 17表明人类的存在NMES / SES的时间同步电机驱动皮质增强运动皮质兴奋性。因此,volitionally驱动NMES / SES可诱导脊髓反射短期的可塑性( 例如 ,相互IA抑制17)其中,通过降途径给定的运动神经元池项目皮质神经元能抑制通过在IA-抑制性的对抗性运动神经元池人类18, 如图1,向邻perant调节模式(见杜塔8)。

图1
图1:概念在杜塔细节等人 21)基本交互式人机界面(HMI)来驱动压力(COP)的中心光标移到提示的目标,以改善下volitionally驱动的神经肌肉电刺激踝关节肌肉协调(NMES) -assisted visuomotor平衡疗法脑电图脑电图,MN:α-运动神经元,IN:IA-抑制中间神经元,肌电图检查:肌电图,DRG:背根神经节。从837再现。 请点击此处查看该图的放大版本。

该前 – 后(AP)的质量(COM)的中心位移进行通过踝plantarflexors(如内侧腓肠肌和比目鱼肌)和脊屈肌(如胫前肌),而内 – 外(ML)位移都受到脚踝反相器(例如胫前肌)和evertors(如腓骨长进行和肌肉芽孢)。因此,中风相关的脚踝损伤包括踝关节背屈肌肉无力,并增加了踝关节痉挛屈肌肌肉导致受损的姿势控制。这里,敏捷训练方案6可以在虚拟现实中利用(VR)基于游戏平台挑战动态平衡其中任务逐渐困难增大,这可能在预防跌倒6是比静态拉伸/重量移锻炼计划更为有效。例如,主题可以动态的平衡visuomotor任务,其中的难度,可以逐步提高到阿梅尔期间执行volitionally驱动NMES / SES协助AP和ML位移重量iorate卒中后特定的脚踝控制问题双足站立中移动。朝着一个资源贫乏的设置volitionally驱动NMES / SES辅助平衡疗法,我们提出这也可以从低用于数据收集低成本HMI移动脑/身体成像(MOBI)19,对视觉听觉生物反馈在MoBILAB离线数据的勘探成本的传感器(见奥赫达 20)。

Protocol

注意:HMI软件管道的基础上开发的免费的开源软件,并在关闭的,现成的低成本视频游戏传感器(详细信息:https://team.inria.fr/nphys4nrehab/software/和https: //github.com/NeuroPhys4NeuroRehab/JoVE)。该HMI软件管道在基于虚拟现实的游戏平台为visuomotor平衡疗法(VBT)8修改功能范围的任务(mFRT)21时提供的数据收集。 图2a示出了诊断眼跟踪器设置,其中所述视?…

Representative Results

图4显示了平稳的追求任务期间的一个身强力壮的性能进行量化提取离线注视眼功能。提取以下特性如表1所示: 特征1 =目标刺激位置和参与者的固定点,当刺激是变化在水平方向上的位置的质心之间的百分比偏差。 特征2 =目标刺激位置和参与者的固定点?…

Discussion

运动和平衡疗法的简单,易用,临床有效的低成本的工具将在低资源设置为神经康复模式的转变。它很可能具有很高的社会影响,因为像中风神经系统疾病将在今后由于世界人口老龄化2急剧增加。还有就是,因此,迫切需要充分利用网络的物理系统中的能力,自定义,监控,支持远程站点神经康复最近成为可能通过电信计算,网络和物理过程的集成。为实现这一总体目标,中风后的追求?…

Divulgations

The authors have nothing to disclose.

Acknowledgements

联合的范围内进行的研究资讯及通讯科技有针对性的计划 – 信通空,由法国国家科学研究中心,INRIA和DST支持下CEFIPRA的保护伞。笔者想感谢的学生,特别是Rahima Sidiboulenouar,RISHABH塞加尔,并且Gorish AGGARWAL的支持,对实验装置的开发。

Materials

NMES stimulator Vivaltis, France PhenixUSBNeo NMES stimulator cum EMG sensor (Figure 2b)
Balance Board Nintendo, USA Wii Balance Board Balance Board (Figure 2b)
Motion Capture Microsoft, USA XBOX-360 Kinect Motion Capture (Figure 2b)
Eye Tracker  Eye Tribe The Eye Tribe SmartEye Tracker (Figure 2a)
EEG Data Acquisition System Emotiv, Australia Emotiv Neuroheadset Wireless EEG headset (Figure 2b)
EEG passive electrode Olimex EEG-PE EEG passive electrode for EOG and references (6 in number)(Figure 2b)
EEG active electrode Olimex EEG-AE EEG active electrode (10 in number)(Figure 2b)
Computer with PC monitor Dell Data processing and visual feedback (Figure 2)
Softwares, EMG electrodes, NMES electrodes, and cables

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Citer Cet Article
Kumar, D., Das, A., Lahiri, U., Dutta, A. A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation. J. Vis. Exp. (110), e52394, doi:10.3791/52394 (2016).

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