CN112543978A - 用于上肢中风后认知障碍患者康复的软件和硬件系统 - Google Patents
用于上肢中风后认知障碍患者康复的软件和硬件系统 Download PDFInfo
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Abstract
本发明涉及医学。一种用于上肢中风后认知障碍患者康复的硬件/软件系统,包括虚拟现实手套、带有传感器的控制器、脑电图仪以及安装有特定任务游戏的计算机。手套配置有可在空间中跟踪手指和手部运动的内置传感元件的。控制器位于肩关节上,以在游戏中进行锻炼期间收集有关肩关节运动的信息。计算机被配置为从前述设备接收信息;对接收的有关患者大脑、手臂肌肉以及精细运动技能的信息进行计算机分析;确定患者的疲劳程度;自动调整游戏中的锻炼并选择最有效的锻炼;并将患者康复结果存储在数据库中。本发明为上肢中风后认知障碍的患者提供了更有效的康复。
Description
技术领域
该技术方案涉及计算机和医学领域,尤其涉及一种用于上肢中风后认知障碍患者康复的软件和硬件系统。
背景技术
全世界每年有1500万人中风,几天之内就有500万人死亡,并且另有500万人残疾。2010年世界上约有3300万人伴随中风后遗症生活。认知障碍(CI)导致患者残疾和社交失调,并且在某些情况下比运动失调扮演更大的角色。平均而言,中风后CI的发病率很高,大约一半的患者会发生。
在这种情况下,发生中风后运动失调的比例为80%,它们是持续性残疾的主要原因之一,并且代表了连续性神经康复的全球目标之一。此外,通常,上肢功能恢复发生在较晚的日子,通常仍然是患者残疾的唯一原因。
上肢功能康复是一项劳动密集型过程,通常花费数月和数年的精力仅能恢复手臂的整体运动,而手部的运动,尤其是,精细的运动技能仍是不可能的,从而导致日常活动受到严重限制。越来越多的基于证据的数据表明,旨在获得技能的重复、密集的训练可以提高上肢的恢复能力。然而,有时由于手臂运动水平不足的障碍而无法进行获得技能的训练。由于使用了计算机虚拟策略、激活了生物反馈功能、患者参与,新的自动化和机器人设备的实施、用于手臂恢复的游戏策略为手臂瘫痪恢复开辟了新的视野。
众所周知,人类手臂运动技能的发展与脑半球专业化和脑半球相互作用的发展直接相关,因此与言语、记忆、注意力以及其他认知功能的发展直接相关。对现有技术的分析表明,精细运动技能诊断的各个要素是评估和控制人类神经心理学状态特殊性的方法的组成部分。通常,在这样的研究期间获得的,由特定执行任务定义的有关手臂精细运动技能的信息量是有限的。
现有技术解决方案公开了对脑血管疾病患者的认知障碍治疗(RU2268723C1,publ27.01.2006,远东医科大学),该治疗包括在10天内以静脉内输注的形式施用微循环和促智药,然后在1个月内施用相同药物的片剂,并同时进行旨在提高对患者至关重要的社交技能的神经心理学训练,,这些技能与姓名、重要日期、药物以及家居用品的位置有关,随着患者的进步,这两项任务变得复杂;每周进行3次30分钟的训练;治疗过程包括12次训练。
已知的治疗方法需要高水平专业人士的监督和参与,并且该方法不能在没有外部帮助的情况下由患者(也适用于脑血管疾病患者)实施。
此外,现有技术解决方案RU2581707С1,publ.20.04.2016,Viktor M.Shklovsky及其同事,公开了一种评估伴有脑病变的脑功能减弱的患者的治疗和康复效率的方法,包括神经心理学检查,该方法在治疗和康复之前和之后随着时间进行。测试包括主要的语言和非语言功能的评估。每个测试结果均以1到10的等级进行评估,并用于确定患者在治疗和康复过程中的大脑能力状态动态。
这种方法的缺点是劳动强度大、需要大量刺激材料以及特殊材料进行训练、耗时长、对神经科医生或神经心理学家的资格要求高。这种方法尚不易于广泛应用,因为它需要高度专业的医生-神经心理学家的参与,并且它本质上是一种诊断技术,但不是认知功能矫正的方法。
另外,存在一种现有技术解决方案,其公开了一种通过使用Schulte表和噪声图像在脑血管病理学上纠正认知障碍的方法(RU2506963C2,publ.20.02.2014,高等职业教育国家资助的教育机构、俄罗斯联邦卫生与社会发展部的克拉斯诺亚尔斯克国立医科大学的教授V.F.Voino-Yasenetsky,State-Financed Educational Institution of the HigherProfessional Education proff.V.F.Voino-Yasenetsky Krasnoyarsk State MedicalUniversity of Ministry of Health and Social Development of the RussianFederation),包括为患者提供“噪声图片”上的对象图像并可能增加“噪声”密度、对患者给出的图像进行识别、在监视器上显示“噪声图片”上的图像,同时还额外提供了一系列清晰描绘的对象图像,并且在其中一个对象上存在来自“噪声图片”的对象,患者通过从提供的变体中识别和选择对象,识别“噪声图片”上的对象,该任务将在设定的时间内执行,其最大间隔由医生定义,并在到期时通过在监视器上显示的患者得分来评估该任务,而显示的得分与图像“噪声”的密度直接成正比,在该密度下患者给出正确的答案,并由公式计算得出,得分显示伴随着视觉和/或声音手段,在至少10天之内进行矫正训练,每天一次,一次训练的持续时间最长为40分钟。
已知技术方案的缺点是本发明用于恢复与视觉识别和视觉注意有关的功能的单向性、缺乏训练其他高级脑功能的任务、以及缺乏复杂性多样的任务、刺激物质的数量有限。
此外,HandTutor、Meditouch(以色列)以及Rapael智能手套、Neofect(韩国)的现有技术解决方案的目的是在术后骨科疾病、难产症中恢复神经系统疾病后的精细运动技能。
然而,上述解决方案在缺乏运动模式分析的可能性、对患者期望的动作的预测方面具有有限的功能,不可能为所有患者收集分析并将康复结果存储在分析存储数据库中,不可能在康复过程中涉及患者手部和腕部的不同部位。
所要求保护的解决方案的优点如下:当使用上肢中风后认知障碍患者康复的软件和硬件系统时,将为创造出额外激活运动皮层的条件,使用游戏动机,而该系统是可移动的,不会引起手部痉挛的增加,并且患者在家中无需外部帮助即可使用。
发明内容
所要求保护的技术方案要解决的技术问题是创建用于上肢中风后认知障碍患者康复的软件和硬件系统,其特征在独立权利要求中描述。从属权利要求中提出了本发明实施方式的其他变型。
技术结果是提高具有上肢中风后认知障碍的患者的康复效率。
在实施该技术解决方案时获得的附加技术成果是减少中枢神经系统损害和运动失调(disorders)患者的康复时间,并减少医生的压力。
康复方法基于大脑可塑性和生物反馈。脑部康复与精细运动(motor)技能的发展密切相关。
在优选实施例中,要求保护的用于上肢中风后认知障碍患者康复的软件和硬件系统,该系统包括:
虚拟现实手套(VR手套),所述虚拟现实手套(VR手套)具有在空间中跟踪手指和手部运动的集成传感元件;
带有传感器的控制器,所述控制器位于肩关节上,以在特定任务游戏中锻炼期间收集有关肩关节运动的信息;
脑电图仪,所述脑电图仪通过检测从其不同区域发出的电脉冲,扫描在特定任务游戏中锻炼期间患者的大脑反应;
计算机,所述计算机安装有特定任务游戏,这刺激了患者手臂运动功能的发展,并且所述计算机被配置为:
·从上述设备接收有关在特定任务游戏中锻炼期间患者的手指和手臂的运动、大脑活动的信息;
·对获得的有关患者的大脑、手臂肌肉以及精细运动技能的信息进行深入的计算机分析;
·基于所分析的信息确定患者的易疲劳性水平,哪些游戏锻炼可以改善患者的康复能力以及哪些锻炼需要更正;
·自动更正必要的游戏锻炼并选择最有效的锻炼;
·每个游戏会话后,将患者康复结果存储在分析存储数据库(大数据)中。
在特定实施例中,额外使用VR耳机或眼镜。
在另一特定实施例中,使用人工神经网络进行最有效锻炼的选择、易疲劳性水平的确定以及锻炼结果的评估。
在另一特定实施例中,软件和硬件系统还包括医生和患者的个人区域。
在另一个特定实施例中,在用于康复的认知游戏期间,患者执行以下锻炼:
a)手指弯曲-伸展;
b)摊开-贴拢;
c)各个手指的动作;
d)腕部旋转、保持。
在另一特定实施例中,从外部信号和感应电势中预过滤脑电图信号。
附图说明
将根据附图进一步描述本发明的实施方式,附图被呈现以阐明本发明的主要内容,并且绝不限制本发明的领域。以下附图已附加到本申请中:
图1示出了康复过程的示意图。患者使用虚拟现实手套和连接的脑电图仪在计算机上进行锻炼。视图中的数字表示以下内容:
1.虚拟现实手套。
2.VR手套肩部传感器。
3.患者。
4.装有特定于任务的认知游戏的计算机。
5.脑电图仪。
6.连接到患者的脑电图仪电极。
图2示出了VR手套组件的示意图。视图中的数字表示以下内容:
11.手套(作为材料)。
12.惯性传感器IMU,其包括加速度计、陀螺仪以及/或磁力计。
13.振动电机传递振动感。
14.系统板。
15.电池。
16.连接电线。
17.壳体。
18.与外部光学跟踪集成的光电二极管。
图3表示在肩关节上带有传感器的VR手套。视图中的数字表示以下内容:
1.虚拟现实手套。
2.VR手套肩部传感器。
21.VR手套外壳,其包括系统板和电池。
22.VR手套腕式传感器。
23.连接电线。
图4示出了上肢运动功能趋势;
图5示出了日常活动得分的提高。
具体实施方式
在接下来给出的本发明实施方式的详细描述中列出了旨在确保清楚地理解本发明的许多实施方式细节。然而,对于本领域技术人员而言显而易见的是,如何以给定的和没有给定的实施细节使用本发明。在其他情况下,没有详细描述公知的方法、过程以及组件,以免模糊本发明。
此外,从给出的说明中将清楚的是,本发明不限于给定的实施方式。保留本发明的主要内容和形式的许多可能的修改、改变、变化以及替换对于本领域技术人员将是显而易见的。
本发明旨在创建用于上肢中风后认知障碍患者的康复的软件和硬件系统。该解决方案使患者能够在医生的远程监督下在家中进行锻炼。由于要求保护的解决方案还包括医生和患者的个人区域。
所要求保护的康复软件和硬件系统包括以下组件:
a)具有手指和手部跟踪的集成传感元件的虚拟现实手套(VR手套);
c)脑电图仪;
d)装有特定任务的认知游戏的计算机;
e)软件读取并传送患者的运动到系统;
f)一组康复的特定任务的游戏;
g)用于适合分析康复结果的匿名化分析存储数据库(大数据)。
通过一组特定任务的认知游戏,执行对要求保护的上肢中风后认知障碍患者的软件和硬件系统中的患者康复。游戏控制是基于某些手势-锻炼和良好的运动技能。
下面是患者在游戏中进行锻炼的示例:
1.手指弯曲-伸展;
2.摊开-贴拢;
3.各个手指的动作;
4.腕部旋转、保持。
5.腕关节弯曲、伸展。
起作用的进行深入检查的肌肉类型如下给出:
·前臂肌群、浅层
ο圆形肌
ο桡侧腕屈肌
ο掌长肌
ο指浅屈肌
ο尺侧腕屈肌
ο肱桡肌
·前臂肌群、深层
ο拇长屈肌
ο指深屈肌
ο旋前方肌
·后臂肌群、浅层
ο桡侧腕长伸肌
ο桡侧腕短伸肌
ο指伸肌
ο尺侧腕伸肌
ο小指伸肌
·后臂肌群、深层
ο后旋肌(前臂肌)
ο拇长展肌
ο拇短伸肌
ο拇长伸肌
ο食指伸肌
·拇指球肌群
ο拇短展肌
ο拇短屈肌
ο拇对掌肌
ο拇收肌
·对侧隆肌群
ο小指展肌
ο小指伸肌
ο小指长屈肌
ο掌短肌
·中手肌群
ο蚓状肌
ο手骨间背侧肌
在开始游戏之前,患者将其手放置并固定在VR手套中,其中集成传感元件用于追踪手指和手。然后,他/她将手套连接到计算机、下载并启动针对运动功能的开发的特定任务的认知游戏。在康复期间,患者不仅要做运动,还要尝试定期正确地进行锻炼。
使用Unity游戏引擎开发游戏(包括虚拟现实游戏)。Unity—用于计算机游戏开发的跨平台环境。Unity可以创建运行在20多种不同操作系统(包括个人计算机、游戏机、移动设备、Internet应用程序等)上的应用程序。Unity的主要优势是可视化开发环境的可用性、跨平台支持以及模块化组件系统。这些功能旨在创建3D游戏,包括VR眼镜游戏。
前提条件是,该手套用作操纵器,使得患者可以进行主动的手和手指的运动,从而使计算机游戏对象能够在监视器上进行设定的运动,从而可以引起传感元件的触发及其在计算机中的记录。该系统提供在每个游戏会话之后将患者康复结果存储在分析存储数据库(大数据)中。医生拥有对分析存储数据库中数据的完全访问权限,之后能够对进度进行客观跟踪并将其与其他患者的收集数据进行比较。
如下图2所示,手套(11)由布制成,内部放置有以下:
(12)IMU传感器8个,每个都包括加速度计、陀螺仪以及/或磁力计,其中4个传感器位于小指、无名指、中指以及食指的最后指骨附近,2个传感器分别位于拇指的第一个指骨和第二个指骨,1个传感器位于系统板,1个传感器位于腕部;
(13)振动马达5个,每只手指1个(在除拇指以外的所有手指的最后指骨附近以及在拇指的最后指骨上);
(14)系统板和计算模块、系统板上安装的用于通过无线电通道与计算机或其他设备进行通信的Bluetooth无线模块,;
(15)电池;
(16)将传感器、振动马达、电池连接至系统板所需的电线;
(17)系统板和电池外壳。
与现有技术中已知的类似物相比,要求保护的解决方案中的VR手套可以感应到手臂或手指在任何方向上的任何运动,而其他产品只能跟踪手指的弯曲。
对于需要更精确地监控精细运动技能的神经康复任务,要求保护的解决方案中的传感器系统是通过带有在肩关节(2)上传感器的控制器添加的,还可以是通过光学跟踪来添加的。
如下面在图3中详细描述的,IMU传感器的相互布置使得能够有效解决手指上的数据“漂移”和空间中的手位置的问题,并且能够更有效地跟踪肩关节的运动。与具有外部跟踪的系统(基于光电传感器或液体发射二极管和外部照相机)相比,该解决方案可以在没有任何外部设备的情况下使用,这对于与移动设备(智能电话)一起工作非常方便。
具有传感器(2)的控制器也可以在无线实施例中实现,并通过无线电信道(蓝牙或WiFi)连接到计算模块(21)。在这种情况下,电池和无线电模块位于带有控制器(2)的单个模块中。
带有传感器的控制器位于肩关节上,以收集锻炼过程中有关肩关节运动的信息。
在游戏会话期间,患者可以使用VR耳机或眼镜。
锻炼期间测量的手臂肌肉活动参数如下:
·肌肉活动幅度。幅度水平表示神经信号的水平。
·幅度变化率。幅度变化率为我们提供了有关认知联系深度的详细信息。
·肌肉活动的不可控制的水平。测量手臂肌肉活动的不可控制的水平能够得出关于校正传入信号的时延程度的结论。此参数还用于测量锻炼过程中患者的疲劳程度。
·对变量的因变量和独立范围的统计分析和描述性统计的方法。数据分布的类型通过Shapiro-Wilk检验评估。
脑电图仪通过检测从不同区域发出的电脉冲来扫描在特定任务游戏中锻炼期间患者的大脑反应。脑电图信号已从外部信号和感应电势中预过滤。此外,脑电图仪的使用能够对以下任务进行跟踪:
·最有效锻炼的自动选择;
·测量患者的易疲劳性水平。
患者的易疲劳性水平在肌肉骨骼中风后认知障碍的有效康复中起着重要作用。将脑电图仪与人工神经网络一起使用能够高精度地确定疲劳程度。此外,该技术能够使大脑活动与康复结果相关联,并且使患者最有效锻炼的选择过程自动化。
在锻炼以解决游戏任务期间,将从VR手套、带有传感器的控制器以及脑电图仪接收到的数据实时传输到计算机,其中对获得的手臂肌肉活动、精细运动技能以及大脑活动参数进行深入的计算机分析。基于分析的信息,确定患者的易疲劳性水平、确定哪些游戏锻炼改善患者的康复和哪些需要纠正。如有必要,将更正所需的游戏锻炼,并自动选择最有效的锻炼。使用人工神经网络进行最有效锻炼的选择、疲劳程度的确定以及锻炼结果的评估。
该技术的原理是使用虚拟空间对新的运动技能进行常规训练。例如,建议患者通过腿部和手指的运动、面部表情或肩胛带来控制虚拟手臂或一只手臂。VR眼镜的使用能够创建足够的真实感,从而在大脑运动部分中创建新的神经连接。除了一般运动功能的训练外,锻炼结束后,患者还可以返回现实并经历自身身体控制原理变化的短暂压力。它导致运动神经元的混乱放电,其中可能存在控制受损肢体的神经元。随后,它作为创建新的生物神经连接的主要基础,该新的神经连接绕过大脑受损部分控制所关注的肌肉骨骼部分。
所要求保护的神经康复解决方案中使用的技术能够获取在空间中手指、手腕以及前臂的精确位置和运动的数据,并实时传输这些数据以供计算机使用。
例如,在计算设备上,计算机上安装了软件驱动程序,该驱动程序使用传感器数据(角速度和加速度矢量)并将其转换为以下关节的空间转向四元数:食指、中指以及无名指的手指末节指骨相对于手掌的转动(弯曲)和小指相对于手掌在垂直面中的转动(弯曲);食指、中指、无名指以及小指在水平面(手掌平面)中的转动;拇指在空间中相对于手掌的转动/弯曲;手(手掌)相对于肘关节的转动/弯曲;肘关节相对于肩关节的转动。
然后,基于获得的角度,使用逆运动学算法(关于关节连接及其线性尺寸的数据)来计算所有其他关节的转动和所有手部关节的相对位置。
要求保护的解决方案的效率由涉及的项目团队成员进行的研究支持。俄罗斯联邦医学生物学局西伯利亚临床中心克拉斯诺亚尔斯克接受神经康复课程的43名患者参与了该研究。将患者随机分为两组。
主要组-20人,(10位男性、10位女性),年龄在44至74岁之间(中位年龄-61岁)。
对照组–23人,(17名男性、6名女性),年龄在46至76岁之间(中位年龄-59)。
所有患者均在6至24个月前患有半球性缺血性中风,脑MRT结果证实了该诊断。
为了神经检查结果的统计处理,填写了以下量表(scales):NIHSS–神经学等级、改良的用于手臂痉挛评估的Ashworth量表、一组用于评估上肢功能能力的量表:运动评估量表,F小节–上肢整体运动技能、G–手部运动、H–手部精细动作技能。Fugl-Meyer评估量表、9孔柱测试(9HPT)用于上肢运动失调的评估;DASH量表用于评估上肢轻瘫引起的日常功能失调。医院焦虑和抑郁量表用于情绪-意志失调水平的客观化。
除了广泛的神经系统检查外,所有患者均接受了准临床随访检查以更准确地确定背景疾病、临床以及生化血液和尿液分析、头颅动脉超声检查、心电图检查、治疗师检查。
在研究开始时,各组在性别、年龄、中风严重性、手痉挛强度、手精细运动技能水平、情绪-意志失调水平、头臂动脉狭窄的严重程度、合并症的严重程度方面没有差异。
在主要组中,除了标准的医院治疗外,还在两周内使用要求保护的系统对患者进行每周5天每天一次持续40-60分钟的手部精细运动技能训练。
在对照组中,仅给患者标准治疗,包括:药物治疗、被动、主动训练上肢运动的指导会话、上肢肌肉按摩、在康复医师/指导员给出指示后以患者自我训练形式的手部精细运动技能的恢复的锻炼,两周内,每天40-60分钟,每周5天。
治疗过程后,重新评估了手部运动失调和日常功能水平。此外,还对NIHSS、Ashwort以及HADS量表的得分进行了跟踪评估。
使用应用程序软件包Statistics 7(Statsoft,美国)进行研究数据的统计处理。使用Kolmogorov-Smirnov检验进行正态性评估。使用Mann-Whitney非参数统计评估独立组的比较结果,p<0.05的差异被认为有统计学意义。使用Wilcoxon非参数统计进行非独立组的分析。根据χ2标准进行属性比较。使用Spearman的非参数检验进行相关性评估。
两组的治疗课程结束后,根据运动评估量表(表1、2)记录的神经系统状态、情绪-意志失调水平、痉挛强度、上肢运动失调水平得分均有统计学意义的改善。
此外,在主要组中,通过瘫痪臂的9孔柱测试和DASH测试分量表(表2)记录了其他变化,这说明在额外使用了作为康复技术的要求保护的系统后,日常功能达到了更高水平。表1
对照组治疗课程前后(治疗第14天)上肢运动活动、心理测验量表以及日常功能受限程度的得分。
注意:*-在p<0.05时,变化被认为具有统计学意义。
表2
主要组治疗课程前后(治疗第14天)上肢运动活动、心理测验量表以及日常功能受限程度的得分。
注意:*-在p<0.05时,变化被认为具有统计学意义。
在比较治疗课程后的治疗组时,记录到运动评估量表、上肢分段,尤其是手运动和精细运动技能子量表的总体水平有统计学意义的差异,并且在日常功能得分上也有统计学意义的改善(p<0.05)。
使用要求保护的系统进行的训练大大提高了患者恢复的动力和态度。结果–在HADS抑郁量表下,各组之间存在差异(表3)。
表3
治疗后主要组和对照组的上肢运动活动、心理测验量表和日常工作受限程度的得分
(曼恩-惠尼(Mann-Whitney)检验)
注意:*-在p<0.05时,变化被认为具有统计学意义。
在评估随访观察结果时,如果使用了要求保护的系统康复的组中,失调的严重程度和功能水平在统计学意义上更好(表4)。
表4
诊后病历中主要组和对照组的上肢运动活动、心理测验量表以及日常功能受限程度的得分(曼恩·惠尼检验)
注意:*-在p<0.05时,变化被认为具有统计学意义。
如表4所示,主要组患者的上肢功能量表(Fugle-Mayer量表、运动评估量表)显示出额外改善,此外,与上肢相关的日常活动在统计学上有显著改善,以及通过HADS抑郁子量表,情绪背景也得到了改善。
上肢运动功能趋势如图4所示。主要(2)和对照(1)组患者在研究开始时,两周治疗课程结束时和诊后病历中,通过Fugle-Meyer评估量表的上肢运动功能趋势。X-方向–研究组,Y-方向–Fugle-Meyer评估量表得分。
注意:–在p<0.05时,变化被认为具有统计学意义。
对与上肢功能失调有关的日常功能趋势的分析使我们得出结论,即所使用的系统对改善日常活动得分具有显著作用(图5)。在研究开始时、两周治疗课程结束时以及随访观察6个月后,主要(2)组和对照组患者的上肢残疾得分趋势。X-方向–研究组,Y-方向–DASH量表得分。
注意:*–在p<0.05时,变化被认为具有统计学意义。
如图5所示,在诊后病历中观察到上肢残疾得分的降低,这表明上肢功能的高功能恢复,患者重新融入日常生活。
通过斯皮尔曼(Spearman)等级方法进行的研究数据相关性分析的结果确定了某些相互关系的存在。在属性之间定义了适度的关联:
–性别和USDG数据:男性更常遭受头臂动脉闭塞性疾病(直接,中度,r=0.46,p<0.05);
–血管池和痉挛得分(左血管池疾病在Ashworth量表得分较高,相互关系–中度,(r=0.33,p<0.05),手功能水平–较低–反向,中度(r=-0.34,p<0.05)和由手部失调引起的差异性的随访水平–较高(直接,中度,r=0.36,p<0.05);
–子宫颈血管超声检查和上肢残疾指数(直接,中度,r=0.46,p<0.05)
–通过NIHSS量表的神经系统状态失调的严重程度的得分,和通过FMA量表的上肢功能能力程度的得分(r=-0.38,p<0.05,反向,中度),
–MMSE得分和FMA量表的上肢功能能力水平(r=0.46,p<0.05,直接,中度)
以下得分与上肢持续残疾(DASH)的高随访得分相关:
–头臂动脉狭窄的严重程度(r=-0.32,p<0.05,反向因果关系,中度),
–通过MAS量表(r=-0.34,p<0.05,反向因果关系,中度)研究开始时的手部精细运动技能水平,
–研究开始时神经系统缺损的严重程度(r=0.32,p<0.05,直接因果关系,中度)。
研究结果使得可以表明,与标准的中风后治疗相比,使用用于上肢中风后认知障碍患者康复的软件和硬件系统是一种高效的技术,这不仅对失调水平有影响,还对瘫痪手的日常使用的增强有影响。此外,患者对该技术很感兴趣,它通过使患者参与训练过程来提高训练的动力。
随后的观察数据使得可以认为,手部精细运动技能的恢复显着增加使用假肢的水平,从而改善功能恢复和日常活动。
如果出现明显的手部轻瘫,则通过在未受影响和轻瘫的肢体上用两副手套进行训练,可以使未受影响的肢体参与其中。
所要求保护的系统的优点是加快了患者康复的速度。
在实施要求保护的用于患者康复的软件和硬件系统时,还额外获得了以下优点:
-分析患者的运动模式、预测患者所需的动作;
-生物反馈适用于不同身体部位(前臂、肩膀、轻瘫的腿等),并将它们组合成一个单一的系统;
-测量手指在任何方向上以任意数量的摆动;
-测量手掌在任何方向上的转动和摆动;
-测量手部、腕部在任意方向上以任意数量的运动和转动;
-分析精细运动技能;
-平稳(离散)地测量运动参数;
-测量被动运动范围;
-测量主动运动范围;
-测量手指运动速度;
-运动质量特性,例如颤抖或流动性;
-监测病人康复进度;
-收集所有患者的分析并将康复结果存储在分析存储数据库中。
本申请材料已经代表了所要求保护的技术方案的优选实施例,该优选实施例不应被用作限制其他特定实施例,这些特定实施例也不超出所要求保护的保护范围并且对于本领域技术人员而言是显而易见的。
Claims (6)
1.一种用于上肢中风后认知障碍患者康复的软件和硬件系统,其特征在于,包括:
虚拟现实手套(VR手套),所述虚拟现实手套(VR手套)具有在空间中跟踪手指和手部运动的集成传感元件;
带有传感器的控制器,所述控制器位于肩关节上,以在特定任务游戏中锻炼期间收集有关所述肩关节的运动的信息;
脑电图仪,所述脑电图仪通过检测从其不同区域发出的电脉冲,扫描在特定任务游戏中锻炼期间患者的大脑反应;
计算机,所述计算机安装有特定任务游戏,这刺激了患者的手臂运动功能的发展,并且所述计算机被配置为:
·从上述设备接收有关在特定任务游戏中锻炼期间患者的手指和手臂的运动、大脑活动的信息;
·对获得的有关患者的大脑、手臂肌肉以及精细运动技能的信息进行深入的计算机分析;
·基于所分析的信息确定患者的易疲劳性水平,哪些游戏锻炼可以改善患者的康复能力以及哪些锻炼需要更正;
·自动更正必要的游戏锻炼并选择最有效的锻炼;
·每个游戏会话后,将患者康复结果存储在分析存储数据库(大数据)中。
2.根据权利要求1所述的系统,其特征在于,额外使用了VR耳机或眼镜。
3.根据权利要求1所述的系统,其特征在于,使用人工神经网络进行最有效锻炼的选择、易疲劳性水平的确定以及锻炼结果的评估。
4.根据权利要求1所述的系统,其特征在于,所述系统额外包括医生和患者的个人区域。
5.根据权利要求1所述的系统,其特征在于,在用于康复的认知游戏期间,患者执行以下锻炼:
a)手指弯曲-伸展;
b)摊开-贴拢;
c)各个手指的动作;
d)腕部旋转、保持。
6.根据权利要求1所述的系统,其特征在于,从外部信号和感应电势中预过滤脑电图信号。
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US20210321909A1 (en) | 2021-10-21 |
EP3901961A4 (en) | 2022-08-10 |
WO2020256577A1 (ru) | 2020-12-24 |
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