CN113456213B - 一种基于人工智能的射频消融参数优化和信息合成方法及*** - Google Patents
一种基于人工智能的射频消融参数优化和信息合成方法及*** Download PDFInfo
- Publication number
- CN113456213B CN113456213B CN202110932338.0A CN202110932338A CN113456213B CN 113456213 B CN113456213 B CN 113456213B CN 202110932338 A CN202110932338 A CN 202110932338A CN 113456213 B CN113456213 B CN 113456213B
- Authority
- CN
- China
- Prior art keywords
- radio frequency
- sensor
- frequency ablation
- artificial intelligence
- decision
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
- A61B18/04—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body by heating
- A61B18/042—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body by heating using additional gas becoming plasma
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
- A61B18/04—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body by heating
- A61B18/12—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body by heating by passing a current through the tissue to be heated, e.g. high-frequency current
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
- A61B18/04—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body by heating
- A61B18/12—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body by heating by passing a current through the tissue to be heated, e.g. high-frequency current
- A61B18/14—Probes or electrodes therefor
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
- A61B5/6843—Monitoring or controlling sensor contact pressure
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6846—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be brought in contact with an internal body part, i.e. invasive
- A61B5/6847—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be brought in contact with an internal body part, i.e. invasive mounted on an invasive device
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
- A61B5/7267—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems involving training the classification device
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/40—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
- G16H40/63—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B17/00—Surgical instruments, devices or methods, e.g. tourniquets
- A61B2017/00973—Surgical instruments, devices or methods, e.g. tourniquets pedal-operated
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
- A61B2018/00571—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body for achieving a particular surgical effect
- A61B2018/00577—Ablation
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
- A61B2018/00571—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body for achieving a particular surgical effect
- A61B2018/00589—Coagulation
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
- A61B2018/00571—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body for achieving a particular surgical effect
- A61B2018/00601—Cutting
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
- A61B2018/00636—Sensing and controlling the application of energy
- A61B2018/0069—Sensing and controlling the application of energy using fuzzy logic
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
- A61B2018/00636—Sensing and controlling the application of energy
- A61B2018/00696—Controlled or regulated parameters
- A61B2018/00702—Power or energy
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
- A61B2018/00636—Sensing and controlling the application of energy
- A61B2018/00696—Controlled or regulated parameters
- A61B2018/00714—Temperature
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
- A61B2018/00636—Sensing and controlling the application of energy
- A61B2018/00696—Controlled or regulated parameters
- A61B2018/0072—Current
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
- A61B2018/00636—Sensing and controlling the application of energy
- A61B2018/00696—Controlled or regulated parameters
- A61B2018/00732—Frequency
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
- A61B2018/00636—Sensing and controlling the application of energy
- A61B2018/00696—Controlled or regulated parameters
- A61B2018/00755—Resistance or impedance
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
- A61B2018/00636—Sensing and controlling the application of energy
- A61B2018/00696—Controlled or regulated parameters
- A61B2018/00761—Duration
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
- A61B2018/00636—Sensing and controlling the application of energy
- A61B2018/00696—Controlled or regulated parameters
- A61B2018/00767—Voltage
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
- A61B2018/00636—Sensing and controlling the application of energy
- A61B2018/00773—Sensed parameters
- A61B2018/00791—Temperature
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
- A61B2018/00636—Sensing and controlling the application of energy
- A61B2018/00773—Sensed parameters
- A61B2018/00875—Resistance or impedance
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B18/00—Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
- A61B2018/00636—Sensing and controlling the application of energy
- A61B2018/00904—Automatic detection of target tissue
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B2560/00—Constructional details of operational features of apparatus; Accessories for medical measuring apparatus
- A61B2560/02—Operational features
- A61B2560/0242—Operational features adapted to measure environmental factors, e.g. temperature, pollution
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4836—Diagnosis combined with treatment in closed-loop systems or methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/043—Architecture, e.g. interconnection topology based on fuzzy logic, fuzzy membership or fuzzy inference, e.g. adaptive neuro-fuzzy inference systems [ANFIS]
Landscapes
- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Surgery (AREA)
- Medical Informatics (AREA)
- Public Health (AREA)
- General Health & Medical Sciences (AREA)
- Biomedical Technology (AREA)
- Physics & Mathematics (AREA)
- Animal Behavior & Ethology (AREA)
- Heart & Thoracic Surgery (AREA)
- Molecular Biology (AREA)
- Veterinary Medicine (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Otolaryngology (AREA)
- Plasma & Fusion (AREA)
- Biophysics (AREA)
- Pathology (AREA)
- Artificial Intelligence (AREA)
- Primary Health Care (AREA)
- Epidemiology (AREA)
- Physiology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Mathematical Physics (AREA)
- Psychiatry (AREA)
- Signal Processing (AREA)
- Business, Economics & Management (AREA)
- General Business, Economics & Management (AREA)
- Fuzzy Systems (AREA)
- Evolutionary Computation (AREA)
- Urology & Nephrology (AREA)
- Surgical Instruments (AREA)
Abstract
一种基于人工智能的射频消融参数优化和信息合成方法及***,该方法应用于射频消融控制器,包括处理器和人工智能模块;射频消融控制器的处理器响应于样本数据,进行预处理并发送至人工智能模块;人工智能模块根据预处理后的样本数据以及针对样本数据的射频消融控制参数建立人工神经网络模型;处理器响应于等离子刀上各传感器采集的信号,进行预处理;人工智能模块将预处理后的传感器数据导入人工神经网络模型进行分析和融合,得到射频消融控制参数。本发明根据环境参数,结合人工神经网络,可以提供病灶组织的位置、消融范围大小等信息,有助于医生判断病灶组织的情况和控制消融过程中的能量传输,有助于减小二次创伤。
Description
技术领域
本发明涉及射频消融技术领域,具体地说,涉及一种基于人工智能的射频消融参数优化和信息合成方法及***。
背景技术
目前,现有的射频消融设备主要聚焦于电压和功率的产生,以成功地将高频电能传输到病人的目标组织;而且主要依靠主治医生的临床经验进行操作,相应的控制参数尚缺少精确的热学依据。由于消融的过程涉及到生物学、传热学、力学、临床医学等诸多学科领域,因此需要精确控制消融范围,尽可能减少不必要的损伤,保证在不伤及正常组织细胞的情况下最大限度地摧毁病灶细胞。
在手术过程中一般利用电流和温度的阈值来估计和控制能量传输,保护病人的安全和保障医疗器械的使用。但是测量动态电流和温度不能实现实时控制,并且效率不高。而且目前的消融设备不能做到自动闭环的消融或凝血的攻率和能量配置。
此外,鉴于微创操作技术具有较高的技术门槛和较长的学习曲线,年轻的医师难以具备足够的知识和经验,对年轻医师的培训和工作初期的指导尤其困难,现有的培训方法通常依赖于知识点讲解、视频介绍等,医师的长期操作经验无法精确表达,不能很好地帮助初学者了解操作步骤、辨识操作环境;对于射频参数的控制,需要考虑到决策输出针对人体治疗中的不同组织类型,如软组织、脂肪、骨头等;根据对模型及环境的单一分析不足以应付复杂的实际情况。因此,临床中亟待一种信息合成的方法和***,可以在临床实操和模拟培训中,进行辅助的环境分析,并且提供匹配的操作参数,供医师参考。
发明内容
本发明的目的是针对目前消融设备无法进行攻率和能量自动配置的问题,提出一种基于人工智能的射频消融参数优化和信息合成方法及***。
本发明的技术方案是:
本发明提供一种基于人工智能的射频消融参数优化和信息合成方法,该方法应用于射频消融控制器,包括处理器和人工智能模块;
S1:射频消融控制器的处理器响应于样本数据,所述的样本数据为目标物质及其周围环境的传感器参数,处理器对前述样本数据进行预处理并发送至人工智能模块;
S2、人工智能模块将预处理后的样本数据以及针对前述样本数据的射频消融控制参数进行模糊计算,建立人工神经网络模型,所述控制参数包括消融发生、触发时间和能量频率;
S3、处理器响应于等离子刀上各传感器采集的信号,对前述信号进行预处理并发送至人工智能模块;
S4、人工智能模块将预处理后的传感器数据导入步骤S2建立的人工神经网络模型进行分析和融合,得到射频消融控制参数。
进一步地,该方法应用于射频消融控制器,所述射频消融控制器的信号输入端与等离子刀上各传感器的信号输出端相连,且射频消融控制器输出等离子刀的控制参数。
进一步地,所述的传感器包括电压、电流、阻抗、温度、湿度和接触力等。
进一步地,步骤S1和S3中,预处理具体包括:
S1-1、对传感器信号数据进行放大和滤波;
S1-2、对滤波后的信号数据进行信号调节,包括线性和非线性校正。
进一步地,所述的步骤S2中,模糊计算具体包括:
S2-1、针对样本数据,构建传感器信号数据集S;构建控制器的决策集;根据信号数据集S中的元素对决策集D输出的影响构建决策矩阵V:
S2-2、对V进行归一化,并对每行求和,将求和后的数据组合成传感器系数矩阵W,对W进行归一化;
S2-3、对于样本数据所在的综合环境,分别针对单一环境根据柯西分布构建对应的关系矩阵R,所述的关系矩阵为k个;
S2-4、对传感器系数矩阵W和k个单一环境的关系矩阵R分别进行融合,即F=WR,得到k个单一采集环境的融合结果,[F1,F2,…,Fk];
S2-5、按照步骤S2-1至S2-4将多组样本的k个单一组织环境的融合结果[F1,F2,…,Fk],以及各样本对应的射频消融控制参数输入人工神经网络,设置网络的层数进行自学习,得到与样本数据对应的单一组织环境系数,建立的人工神经网络模型。
进一步地,所述的步骤S2中,模糊计算具体包括:
S2-1、构建传感器信号数据集S=[s1,s2,…,sn],n为传感器的数量;
基于传感器的种类和性质构建控制器的决策集D=[d1,d2,…,dm],m为决策结果数量,所述的决策集的元素为控制参数,包括消融电压电平,消融功率,脉冲时间,脉冲幅度和脉冲频率;
根据信号数据集S中的元素对决策集D输出的影响构建决策矩阵V,如表1所示:
表1
其中,vnm代表编号为n的传感器对应编号为m决策的决策因子,vij代表决策矩阵因子,i代表传感器的编号,i∈[1,2,3…,n],j代表决策输出的编号,j∈[1,2,3…,m];
S2-3、对于样本数据所在的综合环境,分别针对单一环境根据柯西分布构建对应的关系矩阵R,rij是单一环境矩阵中的元素:
其中,α、β为经验参数,si为编号为i的传感器信号数据,aij为单一环境中编号为i的传感器对应决策输出编号为j的阈值;
S2-4、对步骤S2-2获取的传感器系数矩阵W和步骤S2-3获得的k个单一环境的关系矩阵R进行融合,即F=WR,F为单一环境的融合结果,即
进一步地,α=1,β=2。
进一步地,阈值aij根据目标物质所在环境的电阻率进行设置。
一种基于人工智能的射频消融参数优化和信息合成***,该***包括射频消融控制器、等离子刀和控制脚闸;
所述等离子刀的刀头上设置有多种传感器,用于实时连续地采集目标物质及其周围环境的数据,并将数据传输至所述的射频消融控制器;
所述的控制脚闸通过有线或无线的方式连接射频消融控制器,且控制脚闸供用户控制射频信号的输出;
所述的射频消融控制器输出控制信号至等离子刀,以调整控制参数。
本发明的有益效果:
本发明的多传感器自适应等离子射频消融手术***,通过环境传感器,感应和采集病灶组织及其周围环境的信号,结合人工神经网络,可以提供病灶组织的位置、消融范围大小等信息,有助于医生判断病灶组织的情况和控制消融过程中的能量传输,有助于减小二次创伤。
本发明的其它特征和优点将在随后具体实施方式部分予以详细说明。
附图说明
通过结合附图对本发明示例性实施方式进行更详细的描述,本发明的上述以及其它目的、特征和优势将变得更加明显,其中,在本发明示例性实施方式中,相同的参考标号通常代表相同部件。
图1为本发明的结构示意图;
图2为本发明所述的人工神经网络的算法示意图;
图3为本发明所述的电压、功率及温度变化曲线;
图4为本发明实施例的自适应消融过程与常规消融过程的电压变化对比示意图。
图1中:1、输入接口;2、输出接口;3、等离子刀;4、刀头;5、脚闸;
具体实施方式
下面将参照附图更详细地描述本发明的优选实施方式。虽然附图中显示了本发明的优选实施方式,然而应该理解,可以以各种形式实现本发明而不应被这里阐述的实施方式所限制。
一种基于人工智能的射频消融参数优化和信息合成方法,该方法应用于射频消融控制器,包括处理器和人工智能模块;
S1:射频消融控制器的处理器响应于样本数据,所述的样本数据为目标物质的传感器参数,处理器对前述样本数据进行预处理并发送至人工智能模块;
S2、人工智能模块将预处理后的样本数据以及针对前述样本数据的射频消融控制参数进行模糊计算,建立人工神经网络模型,所述控制参数包括消融发生、触发时间和能量频率;其中,模糊计算具体包括:
S2-1、针对样本数据,构建传感器信号数据集S;构建控制器的决策集;根据信号数据集S中的元素对决策集D输出的影响构建决策矩阵V:
S2-2、对V进行归一化,并对每行求和,将求和后的数据组合成传感器系数矩阵W,对W进行归一化;
S2-3、对于样本数据所在的综合环境,分别针对单一环境根据柯西分布构建对应的关系矩阵R,所述的关系矩阵为k个;
S2-4、对传感器系数矩阵W和k个单一环境的关系矩阵R分别进行融合,即F=WR,得到k个单一采集环境的融合结果,[F1,F2,…,Fk];
S2-5、按照步骤S2-1至S2-4将多组样本的k个单一组织环境的融合结果[F1,F2,…,Fk],以及各样本对应的射频消融控制参数输入人工神经网络,如图2所示,设置网络的层数进行自学习,得到与样本数据对应的单一组织环境系数,建立的人工神经网络模型;
具体实施时,步骤S2为:
S2-1、构建传感器信号数据集S=[s1,s2,…,sn],n为传感器的数量;
基于传感器的种类和性质构建控制器的决策集D=[d1,d2,…,dm],m为决策结果数量,所述的决策集的元素为控制参数,包括消融电压电平,消融功率,脉冲时间,脉冲幅度和脉冲频率等;
根据信号数据集S中的元素对决策集D输出的影响构建决策矩阵V,如表1所示:
表1
其中,vnm代表编号为n的传感器对应编号为m决策的决策因子,vij代表决策矩阵因子,i代表传感器的编号,i∈[1,2,3…,n],j代表决策输出的编号,j∈[1,2,3…,m];
S2-3、对于样本数据所在的综合环境,分别针对单一环境根据柯西分布构建对应的关系矩阵R,rij是单一环境矩阵中的元素:
其中,α、β为经验参数,si为编号为i的传感器信号数据,aij为单一环境中编号为i的传感器对应决策输出编号为j的阈值;
S2-4、对步骤S2-2获取的传感器系数矩阵W和步骤S2-3获得的k个单一环境的关系矩阵R进行融合,即F=WR,F为单一环境的融合结果,即
S3、处理器响应于等离子刀上各传感器采集的信号,对前述信号进行预处理并发送至人工智能模块;
S4、人工智能模块将预处理后的传感器数据导入步骤S2建立的人工神经网络模型进行分析和融合,得到结果。
进一步地,该方法应用于射频消融控制器,所述射频消融控制器的信号输入端与等离子刀上各传感器的信号输出端相连,且射频消融控制器输出控制信号至等离子刀,以调整控制参数,可以在临床实操和模拟培训中,进行辅助的环境分析,并且提供匹配的操作参数,供医师参考。
进一步地,所述的传感器包括但不限于电压、电流、阻抗、温度、湿度和接触力等。
进一步地,步骤S1和S3中,预处理具体包括:
S1-1、对传感器信号数据进行放大和滤波;其中,滤波包括高通、低通和带通滤波;高通、低通滤波可以有效降噪,带通滤波可以移除非生理伪信号;
S1-2、对滤波后的信号数据进行信号调节,包括线性和非线性校正;常见线性校正有使用偏移量对信号进行修正,如环境温度正负3°的调节。非线性校正即对信号进行线性非线性校正可采用分段拟合的形式,一般采用多项式和解析函数ex,lgx等,通过传感器输入数据、环境参数、传感器输出数据,采用最小二乘法求得拟合函数近似替代非线性关系,从而补偿传感器信号的非线性损失,获得保真的传感器信号数据。
进一步地,阈值aij根据人体电阻对照表(表2)和频率对照表(表3)进行设置。
表2
表3
根据融合结果,依据人体不同组织的特性在特定温度下自适应调整输出电流、电压、功率等参数,以达到最佳手术和病灶组织配置参数的需要;依据电压设定值、功率及温度变化曲线,如图4所示,在等离子发生器100v~350v的区间上,进行辅助提示,建议使用100kHz方波自适应功率100w~400w,使用200kHz、300kHz、400kHz高频谐波在100w功率下用于凝血,其中对软骨的切割可以精细化控制在100~120微米。
一种多传感器自适应等离子消融***:该***包括射频消融控制器、等离子刀和控制脚闸;
所述等离子刀的刀头上设置有多种传感器,用于实时连续地采集病灶组织及其周围环境的数据,并将数据传输至所述的射频消融控制器;
所述的控制脚闸通过有线或无线的方式连接射频消融控制器,且控制脚闸供用户控制射频信号的输出;
所述的射频消融控制器输出控制信号至等离子刀的显示界面,对用户调控输出电流和电压进行辅助参考。
以上已经描述了本发明的各实施例,上述说明是示例性的,并非穷尽性的,并且也不限于所披露的各实施例。在不偏离所说明的各实施例的范围和精神的情况下,对于本技术领域的普通技术人员来说许多修改和变更都是显而易见的。
Claims (7)
1.一种基于人工智能的射频消融参数优化和信息合成方法,其特征在于:该方法应用于射频消融控制器,包括处理器和人工智能模块;
S1、射频消融控制器的处理器响应于样本数据,所述的样本数据为目标物质及其周围环境的传感器参数,处理器对前述样本数据进行预处理并发送至人工智能模块;
S2、人工智能模块将预处理后的样本数据以及针对前述样本数据的射频消融控制参数进行模糊计算,建立人工神经网络模型,所述控制参数包括消融发生、触发时间和能量频率;
S3、处理器响应于等离子刀上各传感器采集的信号,对前述信号进行预处理并发送至人工智能模块;
S4、人工智能模块将预处理后的传感器数据导入步骤S2建立的人工神经网络模型进行分析和融合,得到射频消融控制参数;
所述的步骤S2中,模糊计算具体包括:
S2-1、针对样本数据,构建传感器信号数据集S;构建控制器的决策集;根据信号数据集S中的元素对决策集D输出的影响构建决策矩阵V:
S2-2、对V进行归一化,并对每行求和,将求和后的数据组合成传感器系数矩阵W,对W进行归一化;
S2-3、对于样本数据所在的综合环境,分别针对单一环境根据柯西分布构建对应的关系矩阵R,所述的关系矩阵为k个;
S2-4、对传感器系数矩阵W和k个单一环境的关系矩阵R分别进行融合,即F=WR,得到k个单一采集环境的融合结果,[F1,F2,…,Fk];
S2-5、按照步骤S2-1至S2-4将多组样本的k个单一组织环境的融合结果[F1,F2,…,Fk],以及各样本对应的射频消融控制参数输入人工神经网络,设置网络的层数进行自学习,得到与样本数据对应的单一组织环境系数,建立的人工神经网络模型;
所述的步骤S2中,模糊计算具体包括:
S2-1、构建传感器信号数据集S=[s1,s2,...,sn],n为传感器的数量;
基于传感器的种类和性质构建控制器的决策集D=[d1,d2,...,dm],m为决策结果数量,所述的决策集的元素为控制参数,包括消融电压电平,消融功率,脉冲时间,脉冲幅度和脉冲频率;
根据信号数据集S中的元素对决策集D输出的影响构建决策矩阵V,如表1所示:
表1
其中,vnm代表编号为n的传感器对应编号为m决策的决策因子,vij代表决策矩阵因子,i代表传感器的编号,i∈[1,2,3...,n],j代表决策输出的编号,j∈[1,2,3...,m];
S2-3、对于样本数据所在的综合环境,分别针对单一环境根据柯西分布构建对应的关系矩阵R,rij是单一环境矩阵中的元素:
其中,α、β为经验参数,si为编号为i的传感器信号数据,aij为单一环境中编号为i的传感器对应决策输出编号为j的阈值;
2.根据权利要求1所述的基于人工智能的射频消融参数优化和信息合成方法,其特征在于:该方法应用于射频消融控制器,所述射频消融控制器的信号输入端与等离子刀上各传感器的信号输出端相连,且射频消融控制器输出等离子刀的控制参数。
3.根据权利要求1所述的基于人工智能的射频消融参数优化和信息合成方法,其特征在于:所述的传感器包括电压传感器、电流传感器、阻抗传感器、温度传感器、湿度传感器和接触力传感器。
4.根据权利要求1所述的基于人工智能的射频消融参数优化和信息合成方法,其特征在于:步骤S1和S3中,预处理具体包括:
S1-1、对传感器信号数据进行放大和滤波;
S1-2、对滤波后的信号数据进行信号调节,包括线性和非线性校正。
5.根据权利要求1所述的基于人工智能的射频消融参数优化和信息合成方法,其特征在于:α=1,β=2。
6.根据权利要求1所述的基于人工智能的射频消融参数优化和信息合成方法,其特征在于:阈值aij根据目标物质所在环境的电阻率进行设置。
7.一种权利要求1-6之一所述基于人工智能的射频消融参数优化和信息合成方法所采用的***,其特征在于:该***包括射频消融控制器、等离子刀和控制脚闸;
所述等离子刀的刀头上设置有多种传感器,用于实时连续地采集目标物质及其周围环境的数据,并将数据传输至所述的射频消融控制器;
所述的控制脚闸通过有线或无线的方式连接射频消融控制器,且控制脚闸供用户控制射频信号的输出;
所述的射频消融控制器输出控制信号至等离子刀,以调整控制参数。
Priority Applications (4)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110932338.0A CN113456213B (zh) | 2021-08-13 | 2021-08-13 | 一种基于人工智能的射频消融参数优化和信息合成方法及*** |
NL2032409A NL2032409A (en) | 2021-08-13 | 2022-07-07 | Method and system for artificial intelligence-based radiofrequency ablation parameter optimization and information synthesis |
US17/812,180 US20230071658A1 (en) | 2021-08-13 | 2022-07-13 | Method and system for artificial intelligence-based radiofrequency ablation parameter optimization and information synthesis |
EP22184602.5A EP4134029A1 (en) | 2021-08-13 | 2022-07-13 | Method and system for artificial intelligence-based radiofrequency ablation parameter optimization and information synthesis |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110932338.0A CN113456213B (zh) | 2021-08-13 | 2021-08-13 | 一种基于人工智能的射频消融参数优化和信息合成方法及*** |
Publications (2)
Publication Number | Publication Date |
---|---|
CN113456213A CN113456213A (zh) | 2021-10-01 |
CN113456213B true CN113456213B (zh) | 2022-08-02 |
Family
ID=77866529
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202110932338.0A Active CN113456213B (zh) | 2021-08-13 | 2021-08-13 | 一种基于人工智能的射频消融参数优化和信息合成方法及*** |
Country Status (4)
Country | Link |
---|---|
US (1) | US20230071658A1 (zh) |
EP (1) | EP4134029A1 (zh) |
CN (1) | CN113456213B (zh) |
NL (1) | NL2032409A (zh) |
Families Citing this family (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113936520B (zh) * | 2021-10-14 | 2022-06-21 | 中国人民解放军总医院第四医学中心 | 射频消融模拟训练装置 |
CN116627774B (zh) * | 2023-07-24 | 2023-09-29 | 北京西汇环境科技有限公司 | 一种过氧化氢消毒机工作过程中的数据信息处理方法 |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102008349A (zh) * | 2009-09-04 | 2011-04-13 | 美国西门子医疗解决公司 | 使用医学诊断超声的温度预测 |
CN111429432A (zh) * | 2020-03-24 | 2020-07-17 | 聚融医疗科技(杭州)有限公司 | 基于射频处理和模糊聚类的热消融区域监测方法及*** |
Family Cites Families (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6409722B1 (en) * | 1998-07-07 | 2002-06-25 | Medtronic, Inc. | Apparatus and method for creating, maintaining, and controlling a virtual electrode used for the ablation of tissue |
CH704177A2 (de) * | 2010-09-06 | 2012-05-31 | Myles Capstick | Gruppenantennenstruktur zur Erzeugung spezifischer elektromagnetischer Feldverteilungen mit integrierten Sonden zur impliziten Korrektur von gegenseitiger Verkopplung und Fehlanpassung. |
KR101726054B1 (ko) * | 2015-07-08 | 2017-04-12 | 성균관대학교산학협력단 | 생체조직 판별 장치 및 방법, 이를 이용한 수술 장치 |
CN110891508A (zh) * | 2017-05-23 | 2020-03-17 | 波士顿科学医学有限公司 | 使用局部阻抗的损伤熟化预测 |
US20200265309A1 (en) * | 2019-02-14 | 2020-08-20 | Covidien Lp | Systems and methods for estimating tissue parameters using surgical devices |
-
2021
- 2021-08-13 CN CN202110932338.0A patent/CN113456213B/zh active Active
-
2022
- 2022-07-07 NL NL2032409A patent/NL2032409A/en unknown
- 2022-07-13 EP EP22184602.5A patent/EP4134029A1/en active Pending
- 2022-07-13 US US17/812,180 patent/US20230071658A1/en active Pending
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102008349A (zh) * | 2009-09-04 | 2011-04-13 | 美国西门子医疗解决公司 | 使用医学诊断超声的温度预测 |
CN111429432A (zh) * | 2020-03-24 | 2020-07-17 | 聚融医疗科技(杭州)有限公司 | 基于射频处理和模糊聚类的热消融区域监测方法及*** |
Non-Patent Citations (1)
Title |
---|
腔***频消融优化参数设置的离体猪肝实验研究;梁惠宏、谢维杭、杨田嫒、邵子力;《临床医学工程》;20140915;第21卷(第09期);1105-1107 * |
Also Published As
Publication number | Publication date |
---|---|
NL2032409A (en) | 2023-02-24 |
EP4134029A1 (en) | 2023-02-15 |
CN113456213A (zh) | 2021-10-01 |
US20230071658A1 (en) | 2023-03-09 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN113456213B (zh) | 一种基于人工智能的射频消融参数优化和信息合成方法及*** | |
Vujaklija et al. | Online mapping of EMG signals into kinematics by autoencoding | |
Pancholi et al. | Electromyography-based hand gesture recognition system for upper limb amputees | |
CN109394476A (zh) | 脑肌信息自动意图识别与上肢智能控制方法及*** | |
CN108413588B (zh) | 一种基于热成像及bp神经网络的个性化空调控制***及方法 | |
CN110720900B (zh) | 一种脑状态监测与调控装置、方法、处理器及终端设备 | |
CN116313029B (zh) | 一种数字针灸动态控制优化的方法、***和装置 | |
Jaber et al. | HD-sEMG gestures recognition by SVM classifier for controlling prosthesis | |
Qu et al. | Force perception and bone recognition of vertebral lamina milling by robot-assisted ultrasonic bone scalpel based on backpropagation neural network | |
Zhang et al. | Novel approach for electromyography-controlled prostheses based on facial action | |
CN109395245A (zh) | 一种基于移动终端和云技术的低中频调制治疗仪*** | |
CN111563932B (zh) | 一种交叠共轴外科手术控制方法、***及可读存储介质 | |
CN111939479A (zh) | 一种相控阵热疗机及其控制方法 | |
CN116974181A (zh) | 针对可穿戴设备电刺激***的自适应pid算法 | |
NL2032677B1 (en) | A method and device of adaptive emc-emi radio frequency signal data processing | |
US20220265443A1 (en) | Peripheral brain-machine interface system via volitional control of individual motor units | |
CN113921005A (zh) | 一种人工智能语音程控射频仪工作*** | |
Webb et al. | Closed-loop control of depth of anaesthesia | |
CN112164436A (zh) | 一种基于人脸识别的人工智能实时医疗方案调整***及其方法 | |
CN118058805B (zh) | 一种高频超声手术的双输出管理*** | |
CN113456449B (zh) | 一种温热低周波智慧推拿装置及其方法 | |
CN215984971U (zh) | 一种用于脊椎手术的关节刮刀扭矩监测*** | |
CN116173407B (zh) | 基于肌电信号采集和中频电刺激的镇痛仪 | |
CN117653320B (zh) | 脑肿瘤手术监测设备 | |
Wang et al. | An eye tracking and EEG based human-robotic interactive system for motion impaired patients |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |