CN114470516A - Control method, control system, electronic device and medium for stimulation mode - Google Patents
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Abstract
Description
Translated fromChinese技术领域technical field
本发明涉及时序数据处理技术领域，尤其涉及一种刺激模式的控制方法、控制系统、电子设备及介质。The invention relates to the technical field of time series data processing, and in particular, to a stimulation mode control method, a control system, an electronic device and a medium.
背景技术Background technique
神经电刺激技术，是利用外科手术在脑特定区域或脊髓植入电极，通过电刺激调控相关神经元的活动，从而达到治疗神经系统疾病的目的。神经电刺激技术较传统损毁手术具有相对安全、可逆以及术后可调整等优势，已经在癫痫、帕金森症等一些神经系统疾病上取得了显著的疗效。Nerve electrical stimulation technology is to use surgical operation to implant electrodes in specific areas of the brain or spinal cord, and regulate the activities of related neurons through electrical stimulation, so as to achieve the purpose of treating neurological diseases. Compared with traditional destructive surgery, electrical nerve stimulation technology has the advantages of relative safety, reversibility, and postoperative adjustment. It has achieved remarkable curative effects in some neurological diseases such as epilepsy and Parkinson's disease.
发明内容SUMMARY OF THE INVENTION
本发明要解决的技术问题是：提供一种刺激模式的控制方法、控制系统、电子设备及介质。The technical problem to be solved by the present invention is to provide a stimulation mode control method, control system, electronic device and medium.
本发明解决其技术问题所采用的技术方案是：The technical scheme adopted by the present invention to solve its technical problems is:
第一方面，所述刺激模式的控制方法包括：构建已测生理信号的特定数据集合；判断待测生理信号是否属于所述特定数据集合；当判断结果为“是”时，启动刺激并选择匹配的刺激模式。In the first aspect, the control method of the stimulation mode includes: constructing a specific data set of the measured physiological signals; judging whether the physiological signal to be measured belongs to the specific data set; when the judgment result is "Yes", start stimulation and select matching stimulation mode.
进一步地，所述生理信号采用多个导联检测；所述特定数据集合包括：已测生理信号的传播模式及其出现概率；其中所述传播模式包括：生理信号的预警通道数量、预警传播时序中的至少一种。Further, the physiological signal is detected by using multiple leads; the specific data set includes: the propagation mode of the measured physiological signal and its occurrence probability; wherein the propagation mode includes: the number of early warning channels of the physiological signal, the timing of early warning propagation at least one of them.
进一步地，所述判断待测生理信号是否属于所述特定数据集合包括：当待测生理信号的预警通道数量大于或等于预警通道数量的设置阈值时，判断结果为“是”；和/或当待测生理信号的预警传播时序符合匹配预警传播时序的设置阈值时，判断结果为“是”。Further, the judging whether the physiological signal to be measured belongs to the specific data set includes: when the number of early warning channels of the physiological signal to be measured is greater than or equal to the set threshold of the number of early warning channels, the judgment result is "Yes"; and/or when When the early warning propagation sequence of the physiological signal to be measured meets the set threshold matching the early warning propagation sequence, the judgment result is "Yes".
进一步地，所述预警通道数量的判断优先级高于预警传播时序。Further, the judgment priority of the number of early warning channels is higher than the early warning dissemination sequence.
进一步地，所述刺激模式的匹配优先级依次为预警通道数量的差异、预警传播时序的匹配相似度、传播模式的出现概率。Further, the matching priorities of the stimulation patterns are, in order, the difference in the number of early warning channels, the matching similarity of the early warning propagation sequence, and the occurrence probability of the propagation pattern.
进一步地，所述刺激模式包括刺激参数；所述刺激参数包括刺激波形的强度、脉宽、频率、电荷密度中的至少一种。Further, the stimulation mode includes stimulation parameters; the stimulation parameters include at least one of the intensity, pulse width, frequency, and charge density of the stimulation waveform.
第二方面，本发明提供了一种刺激模式的控制系统，用于运行上述的控制方法，包括：上位机，其用于构建所述特定数据集合；下位机，其用于存储所述特定数据集合，并判断待测生理信号是否属于所述特定数据集合，以选择匹配的刺激模式。In a second aspect, the present invention provides a stimulation mode control system for running the above control method, comprising: an upper computer for constructing the specific data set; a lower computer for storing the specific data set, and determine whether the physiological signal to be measured belongs to the specific data set, so as to select a matching stimulation pattern.
进一步地，所述下位机包括：采集模块、匹配模块、预警模块、判断模块和警示模块；当判断结果为“否”时，所述下位机控制警示模块进行警示；所述上位机包括：数据加载模块、计算模块和设置模块。Further, the lower computer includes: a collection module, a matching module, an early warning module, a judgment module and a warning module; when the judgment result is "No", the lower computer controls the warning module to warn; the upper computer includes: data Load modules, compute modules, and setup modules.
第三方面，本发明提供了一种电子设备，包括：处理器和存储器，所述存储器用于存储所述处理器可执行的机器可读指令，当电子设备运行时，所述处理器与所述存储器之间通信连接，所述机器可读指令被所述处理器执行时执行上述的控制方法。In a third aspect, the present invention provides an electronic device, comprising: a processor and a memory, where the memory is used to store machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the The memory is communicatively connected, and the machine-readable instructions are executed by the processor to execute the above-mentioned control method.
第四方面，本发明提供了一种计算机可读存储介质，该计算机可读存储介质上存储有计算机程序，该计算机程序被处理器运行时执行上述的控制方法。In a fourth aspect, the present invention provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and the computer program executes the above-mentioned control method when the computer program is run by a processor.
本发明的有益效果是，本发明的刺激模式的控制方法、控制系统，通过预警算法能够获取多个通道或导联实时的时序数据的预警结果，根据预警结果综合判断是否实施刺激，并选择匹配的刺激模式进行刺激，可以提高刺激的准确率。The beneficial effect of the present invention is that the stimulation mode control method and control system of the present invention can obtain the early warning results of real-time time series data of multiple channels or leads through the early warning algorithm, comprehensively judge whether to implement stimulation according to the early warning results, and select matching The stimulation mode can improve the accuracy of stimulation.
附图说明Description of drawings
下面结合附图和实施例对本发明进一步说明。The present invention will be further described below in conjunction with the accompanying drawings and embodiments.
图1是本发明的刺激模式的控制方法的工作流程图。FIG. 1 is a flow chart of the control method of the stimulation mode of the present invention.
图2是本发明的传播矩阵的示意图。Figure 2 is a schematic diagram of the propagation matrix of the present invention.
图3是本发明的相似矩阵的聚类结果示意图。FIG. 3 is a schematic diagram of the clustering result of the similarity matrix of the present invention.
图4是本发明的第一种传播模式的及其出现概率的示意图。FIG. 4 is a schematic diagram of the first propagation mode of the present invention and its occurrence probability.
图5是本发明的第二种传播模式的及其出现概率的示意图。FIG. 5 is a schematic diagram of the second propagation mode of the present invention and its occurrence probability.
图6是本发明的第三种传播模式的及其出现概率的示意图。FIG. 6 is a schematic diagram of the third propagation mode of the present invention and its occurrence probability.
图7是本发明的刺激模式的控制系统的结构示意图。FIG. 7 is a schematic structural diagram of the control system of the stimulation mode of the present invention.
图8是本发明的聚类算法对肌电信号的处理结果示意图。FIG. 8 is a schematic diagram of the processing result of the EMG signal by the clustering algorithm of the present invention.
图9是本发明的聚类算法对癫痫信号的处理结果示意图。FIG. 9 is a schematic diagram of the processing result of the epilepsy signal by the clustering algorithm of the present invention.
图10是本发明的肌电信号和癫痫信号的特征对比图。FIG. 10 is a characteristic comparison diagram of the electromyographic signal and epilepsy signal of the present invention.
具体实施方式Detailed ways
现在结合附图对本发明作进一步详细的说明。这些附图均为简化的示意图，仅以示意方式说明本发明的基本结构，因此其仅显示与本发明有关的构成。The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are all simplified schematic diagrams, and only illustrate the basic structure of the present invention in a schematic manner, so they only show the structures related to the present invention.
在本发明的描述中，需要说明的是，除非另有明确的规定和限定，术语“安装”、“相连”、“连接”应做广义理解，例如，可以是固定连接，也可以是可拆卸连接，或一体地连接；可以是机械连接，也可以是电连接；可以是直接相连，也可以通过中间媒介间接相连，可以是两个元件内部的连通。此外，限定有“第一”、“第二”的特征可以明示或者隐含地包括一个或者更多个该特征。在本发明的描述中，除非另有说明，“多个”的含义是两个或两个以上。对于本领域的普通技术人员而言，可以具体情况理解上述术语在本发明中的具体含义。In the description of the present invention, it should be noted that the terms "installed", "connected" and "connected" should be understood in a broad sense, unless otherwise expressly specified and limited, for example, it may be a fixed connection or a detachable connection Connection, or integral connection; can be mechanical connection, can also be electrical connection; can be directly connected, can also be indirectly connected through an intermediate medium, can be internal communication between two elements. Furthermore, features delimited with "first", "second" may expressly or implicitly include one or more of that feature. In the description of the present invention, unless otherwise specified, "plurality" means two or more. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood in specific situations.
在本案中，所述生理信号例如但不限于脑电信号，可以通过控制系统匹配不同的刺激模式，以适应各种神经系统疾病。现以癫痫发病的脑电信号为例，对本案的刺激模式的控制方法进行具体说明。In this case, the physiological signals, such as but not limited to EEG signals, can be matched with different stimulation patterns by the control system to adapt to various neurological diseases. Taking the EEG signal of epilepsy as an example, the control method of the stimulation pattern in this case will be explained in detail.
癫痫疾病状态一般可以分为发作间期、发作前期、发作期及发作后期这四个状态。发作间期表示患者处于正常状态的脑电信号，发作前期表示患者处于病发之前的一段时间的脑电信号，发作期表示患者处于癫痫发作时的脑电信号，发作后期表示患者癫痫发作之后一段时间的脑电信号。由于发作前期的脑电信号与正常的脑电信号相比会更加活跃，因此，可以利用发作前期的脑电信号来进行癫痫发作预警。Epilepsy states can generally be divided into four states: interictal, preictal, ictal, and postictal. The interictal period indicates the EEG signal of the patient in a normal state, the preictal period indicates the EEG signal of the patient in a period of time before the onset of the disease, the ictal period indicates the EEG signal of the patient during an epileptic seizure, and the postictal period indicates the period after the patient has an epileptic seizure. EEG signals over time. Since the EEG signals in the pre-ictal period are more active than normal EEG signals, the EEG signals in the pre-ictal period can be used for early warning of epileptic seizures.
如图1所示，本发明提供了一种刺激模式的控制方法，主要包括以下步骤：构建已测生理信号的特定数据集合；判断待测生理信号是否属于特定数据集合；当判断结果为“是”时，启动刺激并选择匹配的刺激模式；当判断结果为“否”时，进行警示或禁用刺激，当然也可以通过人工操作控制系统选择匹配的刺激模式。As shown in FIG. 1 , the present invention provides a stimulation mode control method, which mainly includes the following steps: constructing a specific data set of the measured physiological signal; judging whether the physiological signal to be measured belongs to the specific data set; when the judgment result is "Yes" ", activate the stimulation and select the matching stimulation mode; when the judgment result is "No", warn or disable the stimulation, of course, the matching stimulation mode can also be selected through the manual operation control system.
可选的，生理信号采用多个通道检测；特定数据集合包括：已测生理信号的传播模式及其出现概率；其中传播模式包括：生理信号的预警通道数量、预警传播时序中的至少一种。其中刺激模式的控制方法的具体操作过程如下：S1：获取若干个传播模式及每个传播模式出现的概率，形成特定数据集合。S2：选取特定数据集合中的至少一个传播模式并设置一一对应的刺激模式。S3：多个通道同时输出多个预警结果，根据多个预警结果，判断是否启动刺激；若判断结果为“是”，则利用刺激模式对目标对象进行刺激。Optionally, the physiological signal is detected by using multiple channels; the specific data set includes: the propagation mode of the measured physiological signal and its occurrence probability; wherein the propagation mode includes at least one of the number of early warning channels of the physiological signal and the early warning propagation sequence. The specific operation process of the control method of the stimulation mode is as follows: S1: Acquire a number of propagation modes and the probability of occurrence of each propagation mode to form a specific data set. S2: Select at least one propagation mode in a specific data set and set a one-to-one corresponding stimulation mode. S3: Multiple channels output multiple early warning results at the same time, according to the multiple early warning results, determine whether to activate stimulation; if the judgment result is "Yes", use the stimulation mode to stimulate the target object.
需要说明的是，在监测脑电信号时，一般会在目标对象脑部安装多个电极(即多个通道或导联)，多个电极可以分别被布置在目标对象脑部的不同位置进行脑电信号的监测，一个通道对应一个电极。当目标对象处于发作前期时，多个通道监测到的脑电信号变化会按照一定的顺序进行，这个通道数量可以理解为预警通道数量，这个通道位置的变化顺序可理解为是癫痫传播时序，二者形成癫痫的传播模式。例如，共有5个通道，分别记为通道一、通道二、通道三、通道四和通道五，每个通道分别对应目标对象脑部的不同位置。当目标对象处于癫痫发作前期时，5个通道监测到的脑电信号之间会发生联动。例如，通道一首先监测到发作前期的脑电信号，随着时间推移，通道二、通道三、通道四和通道五再依次监测到发作前期的脑电信号，此时，癫痫传播时序为“通道一→通道二→通道三→通道四→通道五”。当然，癫痫发作传播时序也可以是“通道一→通道三→通道二→通道四→通道五”或者“通道一→通道三→通道四→通道二→通道五”等等。换言之，癫痫的预警通道数量可以反映癫痫发作前期的脑电信号的通道数量；癫痫的预警传播时序可以反映癫痫发作前期的脑电信号变化的通道顺序。将已测的脑电数据发送给上位机，将预警通道数量(即产生预警的通道数量)其出现概率或预警传播时序(即产生预警的传播时序)其出现概率，用于构建特定数据集合。It should be noted that, when monitoring EEG signals, multiple electrodes (ie, multiple channels or leads) are generally installed on the target subject's brain, and multiple electrodes can be arranged at different positions on the target subject's brain for brain testing. Monitoring of electrical signals, one channel corresponds to one electrode. When the target object is in the pre-seizure stage, the changes of EEG signals monitored by multiple channels will be carried out in a certain order. The number of channels can be understood as the number of early warning channels, and the sequence of changes in the position of this channel can be understood as the sequence of epilepsy propagation. Two form the mode of transmission of epilepsy. For example, there are 5 channels in total, denoted as
下面对每个步骤进行具体说明。Each step is described in detail below.
步骤S1：获取若干个传播模式及每个传播模式出现的概率，形成特定数据集合。Step S1: Obtain a number of propagation modes and the probability of each propagation mode to form a specific data set.
本步骤获取若干个传播模式及每个传播模式出现的概率可以采用自动获取或者手动获取方式，手动获取例如是将已有的传播模式直接存入上位机中，自动获取例如可以利用目标对象癫痫发作前期的历史数据，通过聚类算法对历史数据进行处理，得到若干个传播模式及每个传播模式出现的概率。其中，历史数据包括多个通道监测的不同位置的脑电数据，聚类算法例如可以是传播矩阵相似度聚类算法，通过聚类算法对历史数据进行处理，具体包括以下步骤。In this step, several propagation modes and the probability of occurrence of each propagation mode can be acquired automatically or manually. For example, manual acquisition is to directly store the existing propagation modes in the host computer. For automatic acquisition, for example, the target object can have epileptic seizures. The previous historical data is processed through the clustering algorithm to obtain several propagation modes and the probability of each propagation mode. The historical data includes EEG data at different locations monitored by multiple channels, and the clustering algorithm may be, for example, a propagation matrix similarity clustering algorithm, and processing the historical data through the clustering algorithm specifically includes the following steps.
S11、预处理：对所有通道监测到的历史数据，进行带通滤波处理，筛选出处于癫痫发作前期的历史数据区间段，再用宽度为t1的滑动窗口，依次取出该历史数据区间段的多个片段，对每个片段做均方根(RMS)处理，使得历史数据的波形更加平滑。S11. Preprocessing: Perform band-pass filtering on the historical data monitored by all channels to filter out the historical data interval in the pre-epilepsy stage, and then use a sliding window with a width of t1 to sequentially take out the historical data interval. Multiple segments, root mean square (RMS) processing is performed on each segment to make the waveform of the historical data smoother.
S12、互卷积：卷积是两个变量在某范围内相乘后求和的结果。将多个通道进行两两排列组合，用窗宽为t2，步进为Δt的滑动窗口，分别对两个通道监测得到的数据依次选取数据片段，假设两个通道都能够选取出M个数据片段，分别记为Ma和Mb，将数据片段Ma和Mb之间进行两两卷积运算。例如，Ma1与Mb1、Mb2、Mb3、...Mbj分别进行卷积运算，Ma2与Mb1、Mb2、Mb3、...Mbj分别进行卷积运算，以此类推，Mai与Mb1、Mb2、Mb3、...Mbj分别进行卷积运算，这样两个通道的数据之间进行卷积运算一共可以得到M×M个卷积结果。S12. Interconvolution: Convolution is the result of summing two variables after multiplying them within a certain range. Arrange and combine multiple channels in pairs, use a sliding window with a window width of t2 and a step of Δt, and select data segments in turn for the data monitored by the two channels, assuming that both channels can select M data. The segments are denoted as Ma andMb respectively, anda pairwise convolution operation is performed between the data segmentsMa andMb . For example, Ma1 performs convolution operations with Mb1 , Mb2 , Mb3 , ... Mbj respectively, and Ma2 performs convolution operations with Mb1 , Mb2 , Mb3 , ... Mbj By analogy, Mai and Mb1 , Mb2 , Mb3 , . . . Mbj perform convolution operations respectively, so that a total of M×M convolution results can be obtained by performing convolution operations between the data of the two channels.
S13、链接确认：如果M×M个卷积结果中的最大值大于阈值X，则认为这两个通道之间存在链接关系，否则认为两个通道之间不存在链接关系。S13. Link confirmation: if the maximum value in the M×M convolution results is greater than the threshold X, it is considered that there is a link relationship between the two channels, otherwise it is considered that there is no link relationship between the two channels.
S14、时差计算：获取步骤S13中得到的存在链接关系的多组通道，结合滑动窗次数及步进Δt，计算卷积结果的最大值对应的两个数据片段之间的时差。例如，卷积结果中的最大值是由Ma1和Mb3卷积得到的，但是数据片段Ma1和Mb3对应的时刻是不一样的，因此，需要计算出数据片段Ma1和Mb3之间的时差。S14. Time difference calculation: Acquire multiple groups of channels with a link relationship obtained in step S13, and calculate the time difference between two data segments corresponding to the maximum value of the convolution result in combination with the number of sliding windows and the step Δt. For example, the maximum value in the convolution result is obtained by convolution of Ma1 and Mb3 , but the corresponding moments of the data segments Ma1 and Mb3 are different. Therefore, it is necessary to calculate the difference between the data segments Ma1 and Mb3 . time difference.
S15、传播矩阵：设通道数目为N，重复步骤S11至S14，可以得到T个N×N维的传播矩阵(如图2所示)，传播矩阵中的数值可以是具体的时差值或者将时差值进行二值化处理后的数值。传播矩阵的横轴表示第j个通道(1≤i≤N)，传播矩阵的纵轴表示第i个通道(1≤j≤N)，传播矩阵中的数值如果是非零值，则表明第j个通道和第i个通道之间存在链接关系，如果传播矩阵中的数值为“1”，则表明第j个通道的传播顺序在第i个通道之前。S15. Propagation matrix: set the number of channels to N, and repeat steps S11 to S14 to obtain T N×N-dimensional propagation matrices (as shown in Figure 2). The values in the propagation matrix can be specific time difference values or The time difference value is the value after binarization. The horizontal axis of the propagation matrix represents the jth channel (1≤i≤N), and the vertical axis of the propagation matrix represents the ith channel (1≤j≤N). If the value in the propagation matrix is a non-zero value, it indicates the jth channel There is a link relationship between the ith channel and the ith channel. If the value in the propagation matrix is "1", it means that the propagation order of the jth channel is before the ith channel.
S16、传播矩阵相似度：将每个传播矩阵进行矢量化处理，得到传播矩阵对应的向量，再计算两两向量之间的相似度。相似度的计算方法例如可以采用皮尔森相关系数、欧几里得距离等等，可以根据实际情况进行选择。S16. Propagation matrix similarity: vectorize each propagation matrix to obtain a vector corresponding to the propagation matrix, and then calculate the similarity between two vectors. For example, the calculation method of the similarity may use the Pearson correlation coefficient, the Euclidean distance, etc., which may be selected according to the actual situation.
S17、相似矩阵：以T个传播矩阵两两之间的相似度作为元素，可以得到一个T×T维的相似矩阵。S17. Similarity matrix: Taking the similarity between the T propagation matrices as elements, a T×T-dimensional similarity matrix can be obtained.
S18、相似矩阵聚类：对相似矩阵进行聚类处理，可以得到若干个具有刻板性的传播模式及每个传播模式出现的概率。例如，如图3所示，K1、K2、K3分别表示传播模式一、传播模式二和传播模式三出现的频次。每个传播模式分别代表N个通道的数据之间的联动关系。根据不同传播模式出现的频次，计算每个传播模式出现的概率。如图4至图6所示，传播模式一出现的概率为K1/(K1+K2+K3)，传播模式二出现的概率为K2/(K1+K2+K3)，传播模式三出现的概率为K3/(K1+K2+K3)，并且，每个传播模式对应的起始时间也有所不同，例如，传播模式一对应的起始时间为0-12ms，传播模式二对应的起始时间为0-70ms，传播模式三对应的起始时间为0-7ms，表明每个传播模式出现的时间也是有区别的。S18. Similarity matrix clustering: by clustering the similarity matrix, several stereotyped propagation modes and the probability of each propagation mode appearing can be obtained. For example, as shown in FIG. 3 , K1, K2, and K3 represent the frequency of occurrence of
将经过上述步骤获得的若干个传播模式及每个传播模式出现的概率组成特定数据集合，存入上位机中。需要注意的是，用户可以对上位机中保存的传播模式、刺激模式或刺激效果参数进行选择、编辑、新建及保存等操作，如果用户认为上位机中已有的传播模式不符合要求，可以新建或者编辑传播模式，新建或编辑以后，上位机可以自动根据新的传播模式重新计算每个传播模式出现的概率。Several propagation modes obtained through the above steps and the probability of occurrence of each propagation mode are formed into a specific data set and stored in the upper computer. It should be noted that the user can select, edit, create and save the propagation mode, stimulation mode or stimulation effect parameters saved in the host computer. If the user thinks that the existing propagation mode in the host computer does not meet the requirements, you can create a new one. Or edit the propagation mode. After creating or editing, the host computer can automatically recalculate the probability of each propagation mode according to the new propagation mode.
步骤S2：选取特定数据集合中的至少一个传播模式并设置相应的刺激模式。Step S2: Select at least one propagation mode in the specific data set and set the corresponding stimulation mode.
需要说明的是，用户选取上位机中显示的传播模式中的至少一个，并根据选出的传播模式设置相应的刺激模式，例如可以设置刺激波形的强度、脉冲宽度、频率、电荷密度等参数(即刺激参数)。设置好后需要点击“生效”按钮，使得选出的传播模式及相应的刺激模式传输给下位机或者体内机。It should be noted that the user selects at least one of the propagation modes displayed in the host computer, and sets the corresponding stimulation mode according to the selected propagation mode. For example, parameters such as the intensity, pulse width, frequency, and charge density of the stimulation waveform can be set ( i.e. stimulus parameters). After setting, you need to click the "Enable" button, so that the selected propagation mode and the corresponding stimulation mode are transmitted to the lower computer or the internal computer.
步骤S3：多个通道同时输出多个预警结果，根据多个预警结果，判断是否启动刺激；若判断结果为“是”，则利用刺激模式对目标对象进行刺激。具体的，判断待测生理信号是否属于特定数据集合包括：当待测生理信号的预警通道数量大于或等于预警通道数量的设置阈值时，判断结果为“是”；和/或当待测生理信号的预警传播时序匹配预警传播时序的设置值时，判断结果为“是”。Step S3: Multiple channels simultaneously output multiple early warning results, and according to the multiple early warning results, determine whether to activate stimulation; if the judgment result is "Yes", use the stimulation mode to stimulate the target object. Specifically, judging whether the physiological signal to be measured belongs to a specific data set includes: when the number of early warning channels of the physiological signal to be measured is greater than or equal to the set threshold for the number of early warning channels, the judgment result is "Yes"; and/or when the physiological signal to be measured is The judgment result is "Yes" when the early warning propagation timing matches the set value of the early warning propagation timing.
优选的，预警通道数量的判断优先级高于预警传播时序，即当预警通道数量大于预警通道数量的设置阈值时，判断结果一定为“是”，此时的判断过程不再考量预警传播时序是否匹配。Preferably, the priority of judging the number of early warning channels is higher than the sequence of early warning propagation, that is, when the number of early warning channels is greater than the set threshold of the number of early warning channels, the judgment result must be "Yes", and the judgment process at this time no longer considers whether the early warning propagation sequence is match.
优选的，刺激模式的匹配优先级依次为预警通道数量的差异、预警传播时序的匹配度、传播模式的出现概率。在选择匹配的刺激模式时，会将癫痫的传播模式与特定数据集合中刺激模式对应的传播模式比较，优先选择预警通道数量的差异最小的刺激模式，其次是预警传播时序的匹配度最高，最后是传播模式的出现概率最大。Preferably, the matching priorities of the stimulation patterns are the difference in the number of early warning channels, the matching degree of the early warning dissemination sequence, and the occurrence probability of the dissemination pattern. When selecting a matching stimulus pattern, the epilepsy propagation pattern will be compared with the propagation pattern corresponding to the stimulus pattern in the specific data set, and the stimulus pattern with the smallest difference in the number of early warning channels is selected first, followed by the highest matching degree of early warning propagation timing, and finally is the propagation mode with the highest probability of occurrence.
需要说明的是，多个通道同时输出多个预警结果，可以采用癫痫预警算法对每个通道采集到的实时时序数据进行癫痫预警判断，输出的预警结果包括启动预警或者不预警。若预警结果为启动预警，则记录对应的预警通道数量及预警传播时序。癫痫预警算法根据实际情况有多种，现列举一种癫痫预警算法的步骤，包括：T1：对多个通道实时采集的脑电原始数据分别进行预处理；T2：计算脑电数据的信号特征；T3：根据信号特征对脑电数据进行分类，输出预警结果。It should be noted that multiple channels output multiple early warning results at the same time, and the epilepsy early warning algorithm can be used to perform epilepsy early warning judgment on the real-time time series data collected by each channel, and the output early warning results include the activation of early warning or no early warning. If the warning result is to activate the warning, the corresponding number of warning channels and the timing of warning transmission are recorded. There are many kinds of epilepsy early warning algorithms according to the actual situation. Now, the steps of an epilepsy early warning algorithm are listed, including: T1: preprocess the EEG raw data collected in real time by multiple channels; T2: calculate the signal characteristics of the EEG data; T3: Classify EEG data according to signal features, and output early warning results.
需要说明的是，步骤T1中的预处理包括降噪、降采样及多窗口划分。多窗口划分可以采用窗口部分重叠或者不重叠的方式。多窗口划分的目的是每次选取出一个脑电数据的序列片段。步骤T2中的特征信号例如是过零点系数，过零点系数为过零率的映射或过零数的映射；映射为具有正相关或负相关的映射函数；以及映射函数为线性或非线性的。过零点系数能够反映脑电信号的序列片段内的数据值过零点的频次。根据脑电数据的过零点系数，可以区分出正常脑电数据和癫痫发作前期脑电数据。例如，过零点计算公式可以为C＝1-sqrt(num{x(1:N-1).*x(2:N)<0}/(N-1))，N表示待处理的序列片段内有N个点，x(1:N-1)表示序列片段内的前N-1个点的数组，x(2:N)表示序列片段内的后N-1个点的数组，x(1:N-1).*x(2:N)表示两个数组之间进行点对点相乘，num{x(1:N-1).*x(2:N)<0}/(N-1)表示点对点相乘后的结果小于0的概率，即过零率。然后，再通过1-sqrt(num{x(1:N-1).*x(2:N)<0}/(N-1))处理，将过零率映射为取值范围在0-1之间的过零点系数。在该计算公式下，过零点系数越大，表明脑电数据振荡活跃程度越低，过零点系数越小，表明脑电数据振荡活跃程度越高。计算出每个通道监测到的脑电数据的序列片段的过零点系数，并将每个过零点系数输入已经训练过的分类器中，分类器能够输出每个序列片段的分类结果。例如，分类器输出“1”表示该脑电信号片段为癫痫发作前状态，输出“0”表示该脑电信号片段为正常状态。当一个通道内的脑电数据的序列片段由连续Y个分类结果均为“1”，则认为目标对象处于癫痫发作前，需要启动预警；否则不预警。如果判断结果为启动预警，则需要记录分类结果为“1”的脑电数据对应的时刻(即预警时刻)以及通道序号(即预警通道)。It should be noted that the preprocessing in step T1 includes noise reduction, downsampling and multi-window division. The multi-window division can adopt the way that the windows partially overlap or do not overlap. The purpose of multi-window division is to select a sequence segment of EEG data each time. The characteristic signal in step T2 is, for example, a zero-crossing coefficient, which is a mapping of a zero-crossing rate or a mapping of zero-crossing numbers; a mapping function with positive or negative correlation; and a mapping function that is linear or nonlinear. The zero-crossing coefficient can reflect the frequency of zero-crossing of data values in the sequence segment of the EEG signal. According to the zero-crossing coefficient of EEG data, normal EEG data and pre-epilepsy EEG data can be distinguished. For example, the zero-crossing point calculation formula can be C=1-sqrt(num{x(1:N-1).*x(2:N)<0}/(N-1)), where N represents the sequence fragment to be processed There are N points in it, x(1:N-1) represents the array of the first N-1 points in the sequence fragment, x(2:N) represents the array of the last N-1 points in the sequence fragment, x( 1:N-1).*x(2:N) means point-to-point multiplication between two arrays, num{x(1:N-1).*x(2:N)<0}/(N- 1) Indicates the probability that the result of point-to-point multiplication is less than 0, that is, the zero-crossing rate. Then, through 1-sqrt(num{x(1:N-1).*x(2:N)<0}/(N-1)), the zero-crossing rate is mapped to a value range of 0- Zero-crossing coefficient between 1. Under this formula, the larger the zero-crossing coefficient, the lower the oscillating activity of the EEG data, and the smaller the zero-crossing coefficient, the higher the oscillating activity of the EEG data. Calculate the zero-crossing coefficient of the sequence segment of the EEG data monitored by each channel, and input each zero-crossing coefficient into the trained classifier, and the classifier can output the classification result of each sequence segment. For example, the classifier output "1" indicates that the EEG signal segment is in a pre-seizure state, and output "0" indicates that the EEG signal segment is in a normal state. When the sequence segment of the EEG data in one channel is classified as "1" by consecutive Y, it is considered that the target object is before epileptic seizure, and an early warning needs to be activated; otherwise, no early warning is given. If the judgment result is that the early warning is activated, the time corresponding to the EEG data with the classification result of "1" (ie the early warning time) and the channel serial number (ie the early warning channel) need to be recorded.
在本发明中，根据多个预警结果，判断是否启动刺激，具体包括：S31：将预警时刻进行排序得到实际预警传播时序，S32：若预警通道的数量NSZ大于或等于第一阈值N，则直接启动刺激；S32：若预警通道的数量NSZ小于第一阈值N，则将实际预警传播时序与传播模式进行匹配，若匹配结果为实际预警传播时序是传播模式的子集，再启动刺激。In the present invention, judging whether to activate stimulation according to a plurality of early warning results specifically includes: S31: sorting the early warning times to obtain the actual early warning propagation sequence, S32: if the number NSZ of the early warning channels is greater than or equal to the first threshold N, then Directly start the stimulation; S32: If the number of early warning channels NSZ is less than the first threshold N, then match the actual early warning propagation sequence with the propagation mode, if the matching result is that the actual early warning propagation sequence is a subset of the propagation mode, then activate the stimulus again.
需要说明的是，将记录下来的多个预警时刻按照升序或者降序进行排序(与传播模式的时序顺序一致即可)，生成实际预警传播时序，同时记录预警通道的数目。如果预警通道的数量NSZ大于或等于第一阈值N，则直接启动刺激，刺激时，采用步骤S2中预设的刺激模式。若预警通道的数量NSZ小于第一阈值N，则将实际预警时序与传播模式进行匹配，如果匹配结果为实际预警传播时序是传播模式的子集，再启动刺激。传播模式实质上也是一段时序，是由多个通道的时刻拼接起来的，当实际预警传播时序是传播模式的子集时，认为也是需要启动刺激的，否则不刺激。例如，传播模式的时序顺序是12345，如果实际预警时序为123或者234等子集，则也是需要启动刺激的。刺激时，采用步骤S2中预设的刺激模式。用户根据刺激效果可以再重复步骤S1至S3。It should be noted that the recorded multiple early warning moments are sorted in ascending or descending order (which is consistent with the time sequence of the propagation mode) to generate the actual early warning propagation time sequence, and at the same time record the number of early warning channels. If the number of warning channels NSZ is greater than or equal to the first threshold N, the stimulation is directly started, and the stimulation mode preset in step S2 is used during stimulation. If the number of early warning channels NSZ is less than the first threshold N, the actual early warning sequence is matched with the propagation mode. If the matching result is that the actual early warning propagation sequence is a subset of the propagation mode, the stimulation is restarted. The propagation mode is essentially a time sequence, which is spliced together by the moments of multiple channels. When the actual early warning propagation sequence is a subset of the propagation mode, it is considered that stimulation needs to be activated, otherwise it will not be stimulated. For example, the sequence sequence of the propagation mode is 12345. If the actual early warning sequence is a subset such as 123 or 234, it is also necessary to activate the stimulus. During stimulation, the preset stimulation mode in step S2 is used. The user may repeat steps S1 to S3 according to the stimulation effect.
如图7所示，本发明还提供了一种刺激模式的控制系统，运行上述的刺激模式的控制方法。该系统包括上位机1和下位机2。上位机1(如远程终端、CPU、云服务器)，用于获取、保存及显示特定数据集合，以及设置刺激模式。下位机2(如计算机、处理器)用于存储所述特定数据集合，并判断待测生理信号是否属于特定数据集合，以选择匹配的刺激模式。下位机包括：采集模块21、匹配模块22、预警模块23、判断模块24和警示模块25(如声音提示、禁用刺激控制电路等)；当判断结果为“否”时，下位机2控制警示模块25进行警示；上位机1包括：数据加载模块11、计算模块12和设置模块13。As shown in FIG. 7 , the present invention also provides a stimulation mode control system, which runs the above stimulation mode control method. The system includes
优选的，本控制系统还可以用于植入体，还包括体内机3，安装于目标对象体内，用于采集多个通道的实时时序数据以及启动刺激。上位机1与体内机3连接，下位机2与体内机3连接。Preferably, the control system can also be used for implants, and further includes an in-
具体的，采集模块21用于接收体内机3采集到的目标对象的实时时序数据。预警模块23用于接收采集模块21获取的实时时序数据，并对实时时序数据进行癫痫预警算法处理，得到实际预警传播时序及预警通道数目。判断模块24用于判断预警通道数目NSZ是否大于或等于第一阈值N，第一阈值N的大小可以根据实际情况进行设置。匹配模块22用于将实际预警传播时序与传播模式进行匹配，如果匹配结果为实际预警传播时序是传播模式的子集，则将匹配结果发送给体内机3，体内机3对目标对象施加刺激。Specifically, the collection module 21 is configured to receive the real-time time series data of the target object collected by the in-
具体的，数据加载模块11与计算模块12连接，计算模块12与设置模块13连接；设置模块13与匹配模块32连接。数据加载模块11用于读取、显示历史数据，以及显示通道数目。计算模块12用于计算、显示特定数据集合。上位机1还具有进度条功能，可以查看计算进程，因为计算量比较大时，显示界面可能会卡住，这时如果进度条仍然是在工作的，那么表明整个运算还是在正常进行的，不需要重启运算。设置模块13用于选择传播模式，还可以对传播模式进行编辑、新建和保存等操作，同时可以根据选定的传播模式设置相应的刺激模式，并将选定的传播模式和刺激模式传输给体内机3，体内机3施加刺激时根据预设的刺激模式进行刺激。Specifically, the data loading module 11 is connected to the
实施例Example
本实施例还可以采用上述控制方法中的聚类算法对患者的癫痫信号和肌电信号分别进行处理，获得图8至图10的结果，以区分癫痫信号和肌电信号，避免造成误判和误刺激。图8是肌电信号的原始波形和经RMS处理后的波形，图9是癫痫信号的原始波形和经RMS处理后的波形。对比这两张图可以发现，肌电信号的传播无时序性，而癫痫信号的传播具有时序性。并且，请参考图10，癫痫信号中具有高链接强度的通道数目少，通道之间的链接强度比较集中，时差较大；而肌电信号具有高链接强度的通道数目多，通道之间的链接强度比较分散，时差较小。表明采用本方法可以有效区分出癫痫信号和肌电信号，本发明能够有效提高癫痫刺激的准确性，减少误判。In this embodiment, the clustering algorithm in the above-mentioned control method can also be used to process the epilepsy signal and the EMG signal of the patient respectively, and the results shown in Figs. false stimulus. FIG. 8 is the original waveform of the EMG signal and the waveform after RMS processing, and FIG. 9 is the original waveform of the epilepsy signal and the waveform after RMS processing. Comparing these two figures, it can be found that the propagation of EMG signals has no timing, while the propagation of epilepsy signals has timing. And, please refer to Figure 10, the number of channels with high link strength in epilepsy signals is small, the link strength between channels is relatively concentrated, and the time difference is large; while the number of channels with high link strength in EMG signals is large, and the links between channels are large. The intensity is relatively dispersed, and the time difference is small. It is shown that the method can effectively distinguish the epilepsy signal and the myoelectric signal, and the present invention can effectively improve the accuracy of epilepsy stimulation and reduce misjudgment.
本发明还提供了一种电子设备，包括处理器和存储器，存储器用于存储处理器可执行的机器可读指令，当电子设备运行时，处理器与存储器之间通信连接，机器可读指令被处理器执行时执行上述的刺激模式的控制方法的步骤。The present invention also provides an electronic device, including a processor and a memory, the memory is used for storing machine-readable instructions executable by the processor, when the electronic device is running, the processor and the memory are communicatively connected, and the machine-readable instructions are The processor executes the steps of the above-mentioned stimulation mode control method when executed.
本发明还提供了一种计算机可读存储介质，该计算机可读存储介质上存储有计算机程序，该计算机程序被处理器运行时执行上述的刺激模式的控制方法的步骤。实际应用中，计算机可读介质可以是上述系统中所包含的，也可以是单独存在的。计算机可读存储介质承载有一个或者多个程序，当一个或多个程序被执行时，实现所描述的分析方法。计算机可读存储介质可以是非易失性的计算机可读存储介质，例如可以包括但不限于：便携式计算机磁盘、硬盘、随机访问存储器(RAM)、只读存储器(ROM)、可擦式可编程只读存储器(EPROM或闪存)、便携式紧凑磁盘只读存储器(CDROM)、光存储器件、磁存储器件，或者上述的任意合适的组合，但不用于限制本申请保护的范围。The present invention also provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and the computer program executes the steps of the above-mentioned stimulation mode control method when the computer program is run by the processor. In practical applications, the computer-readable medium may be included in the above-mentioned system, or may exist independently. The computer-readable storage medium carries one or more programs that, when executed, implement the described analysis methods. The computer-readable storage medium may be a non-volatile computer-readable storage medium, such as, but not limited to, portable computer disks, hard disks, random access memory (RAM), read only memory (ROM), erasable programmable Read memory (EPROM or flash memory), portable compact disk read only memory (CDROM), optical storage device, magnetic storage device, or any suitable combination of the above, but are not intended to limit the scope of protection of this application.
综上，本发明的刺激模式的控制方法、控制系统，结合已测生理信号的传播模式及预警算法，构建已测生理信号的特定数据集合，然后判断待测生理信号是否属于特定数据集合；当判断结果为“是”时，启动刺激并选择匹配的刺激模式，实现了刺激模式的有效调控，避免了无效刺激及其产生的副作用，可以大幅提高刺激的准确率和安全性。此外，本发明还能够有效区分出癫痫信号和肌电信号，提升癫痫预警的准确率和癫痫刺激的准确率，减少误判，具有很高的应用价值。To sum up, the stimulation mode control method and control system of the present invention, combined with the propagation mode of the measured physiological signal and the early warning algorithm, construct a specific data set of the measured physiological signal, and then judge whether the physiological signal to be measured belongs to the specific data set; when When the judgment result is "Yes", the stimulation is activated and the matching stimulation mode is selected, which realizes the effective regulation of the stimulation mode, avoids invalid stimulation and its side effects, and can greatly improve the accuracy and safety of stimulation. In addition, the present invention can also effectively distinguish epilepsy signals and myoelectric signals, improve the accuracy of epilepsy warning and epilepsy stimulation, reduce misjudgment, and has high application value.
以上述依据本发明的理想实施例为启示，通过上述的说明内容，相关工作人员完全可以在不偏离本项发明技术思想的范围内，进行多样的变更以及修改。本项发明的技术性范围并不局限于说明书上的内容，必须要如权利要求范围来确定其技术性范围。Taking the above ideal embodiments according to the present invention as inspiration, and through the above description, relevant personnel can make various changes and modifications without departing from the technical idea of the present invention. The technical scope of the present invention is not limited to the content in the specification, and the technical scope must be determined according to the scope of the claims.
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