IEEE trans:一种低成本的脑卒中患者下肢运动康复脑机接口系统

2021-06-08 MedSci原创 MedSci原创

脑中风是一组以脑部缺血及出血性损伤症状为主要临床表现的疾病,又称脑卒中或脑血管意外,具有极高的病死率和致残率,主要分为出血性脑中风(脑出血或蛛网膜下腔出血)和缺血性脑中风(脑梗塞、脑血栓形成)两大类,

脑中风是一组以脑部缺血及出血性损伤症状为主要临床表现的疾病,又称脑卒中或脑血管意外,具有极高的病死率和致残率,主要分为出血性脑中风(脑出血或蛛网膜下腔出血)和缺血性脑中风(脑梗塞、脑血栓形成)两大类,以脑梗塞最为常见。脑中风发病急,病死率高,是世界上最重要的致死性疾病之一。中风的死亡率也有随年龄增长而上升的趋势,由于一直缺乏有效的治疗措施,目前认为预防是最好的措施.中风影响下肢的运动,这些运动有助于站立和行走动作,以及广泛的日常生活活动(ADL)。虽然中风后患者可以经常进行强化的常规康复治疗以恢复神经损伤(可能需要6个月的时间),但他们进行ADL仍然有一定的困难,因为他们的下肢功能受损和异常步态模式依然持续存在。

脑卒中后运动恢复的常规物理治疗方法有多种,如像疗法和跑步机训练。此外,基于机器人技术的替代性康复疗法,如外骨骼和智能步行器,正在被开发用于步态恢复。作为替代方案,脚踏式康复设备相对便宜,在步态和下肢康复方面都显示出了有效性。 事实上,基于电动自行车或踏板的系统已经成功地应用于中风患者的康复。这些系统可以在合理的治疗时间框架内提供大量下肢屈伸试验的重复性和功能性活动,增强中风后幸存者的肌肉活动和协调、肌肉力量、平衡和功能独立性 。

脑-机接口(BCI)和脑-机械接口(BMI)是测量中枢神经系统(CNS)活动并将其转换为替代、恢复、增强和补充人工输出的通信系统,通过改善自然中枢神经系统输出,从而改变中枢神经系统与其外部或内部环境之间的持续相互作用。基于脑电图(EEG)的系统被设计用于中风后患者的康复,提供了控制终端应用的途径,如功能性电刺激和机器人外骨骼 。本研究旨在开发一种基于低计算成本技术的BMI,,以提供更自然的闭环,当患者通过执行踏板来传递控制命令以触发小型机动运动自行车(MMEB)时,在下肢康复期间接收被动踏板作为反馈。

Fig. 1. - Proposed system for EEG processing and pedaling imagery recognition during the Calibration and On-line phases.

实验流程图

BMI分为3个子系统:信号采集、信号处理和计算机接口。所提出的脑电信号处理和蹬踏图像识别系统分为两个阶段:a)利用休息和蹬踏脑电数据进行BMI校正;b) 当参与者通过执行踏板来触发机器发送控制命令时进行在线识别。从每个受试者收集包含与静息状态和蹬踏类别相关的模式的EEG数据以校准BMI。然后,将这些数据分为训练集和测试集。 通过OpenBCI系统的Cyton模块和OpenViBE软件,以250hz的采样率采集与蹬踏心肌梗死相关的脑电信号。应用黎曼方法计算静态和踩踏板MI试验的空间特征。研究了两种去除冗余特征的特征选择方法:快速邻域成分分析法(FNCA) 和成对特征贴近度法(PWFP),以获得提高分类可分性的最佳方法,以及在线测试中BMI性能的最佳方法。

Fig. 2. - Representation of the experimental setup while a subject was triggering the proposed BMI by pedaling MI. (a) Platform for EEG acquisition and processing; (b) EEG cap of 64 electrodes, bike-control and visual cues; (c) EEG locations (circles filled with red color) used in our experiments; (d) Sequence of stimuli used to guide the users executing pedaling MI.

实验装置设置图

采用LDA分类器对静止状态和蹬踏进行判别。该分类器在其他使用基于脑电的脑机接口识别真实或想象运动任务的研究中显示了有希望的结果。采用exercepeutic公司生产的商用小型机动健身车(ACTIVCycle-Mini-Exercise Bike 7101型)通过被动踏板辅助下肢运动。选择8名健康受试者(其中1名女性,7名男性,年龄22~36岁,右侧为优势肢体)作为对照组。选择右侧肢体占优势的2例脑卒中后患者PS1(女,46岁,右偏瘫,出血性脑卒中发生于5年前)和PS2(女,48岁,左偏瘫,缺血性脑卒中发生于约2年前)作为脑卒中后组。每位参与者被要求想象日常生活中的一项常见活动。对于每个参与者,在七个疗程中进行脑电图数据库收集,每个疗程间隔3分钟休息。,使用准确度(ACC)、Kappa、真阳性率(TPR)和假阳性率(FPR)度量算法有效性。

结果显示,PWPF在健康受试者中表现最好(ACC=68.23)± 2.22%,Kappa=0.36± 0.04,TPR=72.92± 4.38%,FPR=36.46± 5.44%)和卒中后患者(对于PS1,ACC=75%,Kappa=0.50,TPR=66.67%,FPR=16.67%,而对于PS2,ACC=83.33%,Kappa=0.67,TPR=75%,FPR=8.33%)。校准阶段,OpenViBE对健康受试者的FPR值在14.84%和50%之间,而PS1和PS2患者的FPR值分别为18.75%和32.81%。四名有BCIs经验的受试者(P01、P02、P03和P08)触发了第1和第2阶段的所有试验的MMEB,受试者P01、P02和P03的ACC达到100%,最小潜伏期为1秒左右。

中风后患者从第1阶段到第2阶段的表现有所改善。例如,患者PS1在第一个疗程中仅触发了一次MMEB试验,但在第二个疗程中增加到五次成功试验,而患者PS2在第1和第2个疗程中分别成功完成了七次和十一次试验。值得一提的是,这些患者从第1阶段到第2阶段的触发潜伏期缩短,受试者PS1的触发潜伏期显著改善(4.57± 0.00秒和2.03秒± 分别为0.42秒)。对于患者PS2,潜伏期为2.90 秒和1.99秒  。与对照组相比,这些卒中后患者在触发MMEB的同时,感觉到了更多的动力和益处,甚至仅仅获得了一次成功的试验,比如PS1。 中风后PS1表现最低,这可能与患者难以理解所要求的任务有关。我们注意到,在实验过程中,直观的刺激序列帮助了这个患者。此外,注意触发潜伏期可能受到两个因素的影响:1)受试者注意力分散或较低;2) 分类器性能差。

总之,本文研制了一种便携式低成本BMI踏板康复,它主要由低成本、开源的硬件和软件组成,可以作为一种低成本的脑卒中患者下肢康复系统进行推广。

Romero-Laiseca M A , Delisle-Rodriguez D , Cardoso V , et al. A Low-Cost Lower-Limb Brain-Machine Interface Triggered by Pedaling Motor Imagery for Post-Stroke Patients Rehabilitation[J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering

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    2022-01-14 bsmagic9140
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    2021-07-25 小小医者

    #脑机接口#离应用已不远了

    0

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    2021-06-09 smart Ren

    认真学习

    0

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    2021-06-09 健健

    卒中虽然是临床上常见病,溶栓,取栓等血管内治疗也很成熟,但是仍然有很多未知问题有待认知!

    0

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    2021-06-09 Kiki徐

    👍👍👍👍

    0

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    2021-06-08 言西早

    脑中风是一组以脑部缺血及出血性损伤症状为主要临床表现的疾病

    0

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