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1. 发明申请

US20150230721A1 ACCURATELY INDETIFYING CRITCAL REGIONS IN ATRIAL FIBRILLATION BY IDENTIFYING ROTORS IN DIRECTIONAL SIMILARITY VECTOR FIELD 审中-公开
标题翻译：通过在方向相似矢量场中识别转子来精确地识别ATRIAL FIBRILLATION中的CRITCAL区域
公开(公告)号：US20150230721A1
公开(公告)日：2015-08-20
申请号：US14699171
申请日：2015-04-29
申请人： Yenn-jiang Lin , Men-Tzung Lo
发明人： Men-Tzung Lo , Yenn-Jiang Lin , Huan-Yu Kuo , Yi-Chung Chang , Chen Lin , Hsiang-Chih Chang , Fa-Po Chung , Shih-Ann Chen
IPC分类号： A61B5/04 , A61B5/046
CPC分类号： A61B5/04011 , A61B5/04012 , A61B5/04085 , A61B5/046 , A61B5/4836 , A61B5/7246 , A61B18/1492 , A61B2018/00351 , A61B2018/00577 , A61B2018/00839
摘要： A computer-assisted method for quantitatively characterizing atrial fibrillation in a patient includes recording time series of bipolar atrial fibrillation signals at multiple sites in a patient's atria using two or more electrodes, calculating a similarity index vector by a computer system based on the bipolar atrial fibrillation signal between a first site and its neighboring sites, constructing an similarity-index vector field based on similarity-index vectors at different sites, calculating Curl and Divergence of the similarity-index vector field, calculating Rotor Identification using Curl and Divergence, calculating Focal Identification using Divergence, and determining one or more critical regions in the patient's atria if Rotor Identification is above a first predetermined threshold and Focal Identification is above a second predetermined threshold.
摘要翻译：用于定量表征患者心房颤动的计算机辅助方法包括使用两个或多个电极记录患者心房多个部位的双相心房颤动信号的时间序列，基于双相心房颤动计算计算机系统的相似性指数矢量信号在第一站点及其相邻站点之间，基于相似度指数向量在不同位置构建相似性指数向量域，计算相似度指数向量域的卷曲和发散，使用Curl和Divergence计算转子识别，计算焦点识别使用发散，并且如果转子识别高于第一预定阈值并且焦点识别高于第二预定阈值，则确定患者心房中的一个或多个关键区域。

2. 发明申请

US20140031708A1 SYSTEM AND METHOD FOR IMPROVED COMPLEX FRACTIONATED ELECTROGRAM ABLATION 有权
标题翻译：用于改进复合分离电沉积的系统和方法
公开(公告)号：US20140031708A1
公开(公告)日：2014-01-30
申请号：US13558616
申请日：2012-07-26
申请人： Men-Tzung Lo , Yenn-Jiang Lin , Shih-Ann Chen , Yi-Chung Chang , Chen Lin , Ke-Hsin Hsu , Wan-Hsin Hsieh , Hung-Yi Lee , Norden E. Huang
发明人： Men-Tzung Lo , Yenn-Jiang Lin , Shih-Ann Chen , Yi-Chung Chang , Chen Lin , Ke-Hsin Hsu , Wan-Hsin Hsieh , Hung-Yi Lee , Norden E. Huang
IPC分类号： A61B5/046
CPC分类号： A61B5/046 , A61B5/7246 , A61B5/725 , A61B5/7282
摘要： A computer-assisted method for quantitative characterization and treatment of ventricular fibrillation includes preprocessing a time series of an atrial fibrillation signal obtained from a patient, segmenting the time series of the AF signal into activation segments by the computer system, obtaining local activation waveforms (LAW) from the activation segments, determining degrees of similarity between the LAWs, and identifying one or more critical regions in the patient's atria if the LAWs have degrees of similarity exceeding a first threshold value.
摘要翻译：用于定量表征和治疗心室颤动的计算机辅助方法包括预处理从患者获得的心房颤动信号的时间序列，通过计算机系统将AF信号的时间序列分解成激活区段，获得局部激活波形（LAW ）确定所述LAW之间的相似度，以及如果所述LAW具有超过第一阈值的相似度，则识别所述患者心房中的一个或多个关键区域。

3. 发明授权

US09545210B2 Accurately indetifying critcal regions in atrial fibrillation by identifying rotors in directional similarity vector field 有权
标题翻译：通过在方向相似矢量场中识别转子来准确地标记心房颤动中的临界区域
公开(公告)号：US09545210B2
公开(公告)日：2017-01-17
申请号：US14699171
申请日：2015-04-29
申请人： Yenn-jiang Lin , Men-Tzung Lo
发明人： Men-Tzung Lo , Yenn-Jiang Lin , Huan-Yu Kuo , Yi-Chung Chang , Chen Lin , Hsiang-Chih Chang , Fa-Po Chung , Shih-Ann Chen
IPC分类号： A61B5/046 , A61B5/04 , A61B5/00 , A61B5/0408 , A61B18/14 , A61B18/00
CPC分类号： A61B5/04011 , A61B5/04012 , A61B5/04085 , A61B5/046 , A61B5/4836 , A61B5/7246 , A61B18/1492 , A61B2018/00351 , A61B2018/00577 , A61B2018/00839
摘要： A computer-assisted method for quantitatively characterizing atrial fibrillation in a patient includes recording time series of bipolar atrial fibrillation signals at multiple sites in a patient's atria using two or more electrodes, calculating a similarity index vector by a computer system based on the bipolar atrial fibrillation signal between a first site and its neighboring sites, constructing an similarity-index vector field based on similarity-index vectors at different sites, calculating Curl and Divergence of the similarity-index vector field, calculating Rotor Identification using Curl and Divergence, calculating Focal Identification using Divergence, and determining one or more critical regions in the patient's atria if Rotor Identification is above a first predetermined threshold and Focal Identification is above a second predetermined threshold.
摘要翻译：用于定量表征患者心房颤动的计算机辅助方法包括使用两个或多个电极记录患者心房多个部位的双相心房颤动信号的时间序列，基于双相心房颤动计算计算机系统的相似性指数矢量信号在第一站点及其相邻站点之间，基于相似度指数向量在不同位置构建相似性指数向量域，计算相似度指数向量域的卷曲和发散，使用Curl和Divergence计算转子识别，计算焦点识别使用发散，并且如果转子识别高于第一预定阈值并且焦点识别高于第二预定阈值，则确定患者心房中的一个或多个关键区域。

4. 发明授权

US08862213B2 System and method for improved complex fractionated electrogram ablation 有权
$System and method for improved complex fractionated electrogram ablation$
标题翻译：用于改进复合分级电描记术消融的系统和方法
公开(公告)号：US08862213B2
公开(公告)日：2014-10-14
申请号：US13558616
申请日：2012-07-26
申请人： Men-Tzung Lo , Yenn-Jiang Lin , Shih-Ann Chen , Yi-Chung Chang , Chen Lin , Ke-Hsin Hsu , Wan-Hsin Hsieh , Hung-Yi Lee , Norden E. Huang
发明人： Men-Tzung Lo , Yenn-Jiang Lin , Shih-Ann Chen , Yi-Chung Chang , Chen Lin , Ke-Hsin Hsu , Wan-Hsin Hsieh , Hung-Yi Lee , Norden E. Huang
IPC分类号： A61B5/046
CPC分类号： A61B5/046 , A61B5/7246 , A61B5/725 , A61B5/7282
摘要： A computer-assisted method for quantitative characterization and treatment of ventricular fibrillation includes preprocessing a time series of an atrial fibrillation signal obtained from a patient, segmenting the time series of the AF signal into activation segments by the computer system, obtaining local activation waveforms (LAW) from the activation segments, determining degrees of similarity between the LAWs, and identifying one or more critical regions in the patient's atria if the LAWs have degrees of similarity exceeding a first threshold value.
摘要翻译：用于定量表征和治疗心室颤动的计算机辅助方法包括预处理从患者获得的心房颤动信号的时间序列，通过计算机系统将AF信号的时间序列分解成激活区段，获得局部激活波形（LAW ）确定所述LAW之间的相似度，以及如果所述LAW具有超过第一阈值的相似度，则识别所述患者心房中的一个或多个关键区域。

5. 发明授权

US09380948B1 System and method for quantitative analysis of respiratory sinus arrhythmia 有权
标题翻译：呼吸窦性心律失常定量分析系统及方法
公开(公告)号：US09380948B1
公开(公告)日：2016-07-05
申请号：US13950702
申请日：2013-07-25
申请人： Men-Tzung Lo , Yung-Hung Wang
发明人： Men-Tzung Lo , Chen Lin , Cheng-Yen Wang , Yung-Hung Wang , Yi-Chung Chang , Han-Hwa Hu , Kun Hu
IPC分类号： A61B5/00 , A61B5/0205
CPC分类号： A61B5/0205 , A61B5/024 , A61B5/0816 , A61B5/486 , A61B5/7253 , A61B5/7278
摘要： A computer-assisted method for quantitative analysis of respiratory sinus arrhythmia (RSA) includes obtaining a time series of a cardiac interval signal from an individual, obtaining a time series of a respiratory signal from the individual; decomposing the cardiac interval signal into a first group of ensemble empirical modes; obtaining, by a computer system, a time series of RSA instantaneous amplitude from at least one of the first group of ensemble empirical modes; decomposing the respiratory signal into a second group of ensemble empirical modes; obtaining a time series of respiratory instantaneous phase from the one of the second group of ensemble empirical modes; determining respiratory period from the time series of the respiratory instantaneous phase; and quantifying RSA in the individual according to a dependence of the RSA instantaneous amplitude on the respiratory period.
摘要翻译：用于定量分析呼吸窦性心律失常（RSA）的计算机辅助方法包括获得来自个体的心脏间隔信号的时间序列，获得来自个体的呼吸信号的时间序列; 将心脏间隔信号分解为第一组综合经验模式; 通过计算机系统从第一组整体经验模式中的至少一个获得RSA瞬时振幅的时间序列; 将呼吸信号分解成第二组综合经验模式; 从第二组综合经验模式中的一个获得呼吸瞬时相位的时间序列; 从呼吸瞬时相的时间序列确定呼吸周期; 并根据RSA瞬时振幅对呼吸周期的依赖性量化个体中的RSA。

6. 发明授权

US08103483B2 Accurate detection of sleep-disordered breathing 有权
标题翻译：准确检测睡眠呼吸障碍
公开(公告)号：US08103483B2
公开(公告)日：2012-01-24
申请号：US12248024
申请日：2008-10-08
申请人： Men-Tzung Lo , Yanhui Liu
发明人： Men-Tzung Lo , Yanhui Liu
IPC分类号： G06F17/14
CPC分类号： A61B5/0205 , A61B5/0456 , A61B5/08 , A61B5/4806 , A61B5/4818
摘要： A method for detecting sleep-disordered breathing (SDB) includes acquiring a time sequence of a physiological signal from an individual, wherein the time sequence of the physiological signal includes a oscillatory pattern, computing an oscillatory interval signal using the time sequence of the physiological signal, decomposing the oscillatory interval signal into a plurality of ensemble empirical modes, selecting one of the plurality of ensemble empirical modes, calculating at least one of average amplitude or standard deviation of the instantaneous frequency in the selected ensemble empirical mode; and identifying SDB using at least one of the average amplitude or the standard deviation of the instantaneous frequency.
摘要翻译：一种用于检测睡眠呼吸障碍（SDB）的方法包括获取来自个人的生理信号的时间序列，其中生理信号的时间序列包括振荡模式，使用生理信号的时间序列计算振荡间隔信号将所述振荡间隔信号分解为多个整体经验模式，选择所述多个集合经验模式中的一个，计算所选集合经验模式中瞬时频率的平均幅度或标准偏差中的至少一个; 以及使用瞬时频率的平均幅度或标准偏差中的至少一个来识别SDB。

7. 发明申请

US20120004693A1 SYSTEM AND METHOD FOR PREDICTING SUCCESSFUL DEFIBRILLATION FOR VENTRICULAR FIBRILLATION CARDIAC ARREST 有权
标题翻译：用于预测心脏纤维化心脏衰竭的成功定位的系统和方法
公开(公告)号：US20120004693A1
公开(公告)日：2012-01-05
申请号：US12829286
申请日：2010-07-01
申请人： Men-Tzung Lo , Lian-Yu Lin , Patrick Chow-In Ko , Chen Lin , Matthew Huei-Ming Ma
发明人： Men-Tzung Lo , Lian-Yu Lin , Patrick Chow-In Ko , Chen Lin , Matthew Huei-Ming Ma
IPC分类号： A61N1/39
CPC分类号： A61N1/3925 , A61H31/005 , A61H2230/04 , A61N1/3702
摘要： A computer-assisted method for quantitative characterization and treatment of ventricular fibrillation includes acquiring a time series of a ventricular fibrillation (VF) signal using a probe from a patient experiencing VF, subtracting the mean from the time series of the VF signal, calculating a cumulative VF signal after the mean is subtracted from the time series of the VF signal, segmenting the cumulative VF signal by a plurality of sampling boxes, calculating the root-mean-square of the cumulative VF signal as a function of the sampling box size , extracting an exponent of the root-mean-square of the cumulative VF signal as a function of the sampling box size, applying electrical defibrillation to the patient if the exponent is below a predetermined value, and applying cardiopulmonary resuscitation (CPR) to the patient if the exponent is above a predetermined value.
摘要翻译：用于定量表征和治疗心室颤动的计算机辅助方法包括使用来自经历VF的患者的探针获取心室颤动（VF）信号的时间序列，从VF信号的时间序列中减去平均值，计算累积从VF信号的时间序列中减去平均值之后的VF信号，通过多个采样盒分割累积VF信号，计算作为采样箱大小的函数的累积VF信号的均方根，提取累积VF信号的均方根的指数作为采样箱尺寸的函数，如果指数低于预定值，则向患者施加电除颤，并且如果所述指数低于预定值则应用心肺复苏（CPR）指数高于预定值。

8. 发明申请

US20100125213A1 SYSTEMS AND METHODS FOR ASSESSING DYNAMIC CEREBRAL AUTOREGULATION 有权
标题翻译：用于评估动态胚胎自动化的系统和方法
公开(公告)号：US20100125213A1
公开(公告)日：2010-05-20
申请号：US12273386
申请日：2008-11-18
申请人： Men-Tzung Lo , Yanhui Liu
发明人： Men-Tzung Lo , Yanhui Liu
IPC分类号： A61B5/02
CPC分类号： A61B8/06 , A61B5/02028 , A61B5/021 , A61B5/026 , A61B5/1455 , A61B5/4064 , A61B8/0808
摘要： A method for dynamic cerebral autoregulation (CA) assessment includes acquiring a blood pressure (BP) signal having a first oscillatory pattern from a first individual, acquiring a blood flow velocity (BFV) signal having a second oscillatory pattern from the first individual, decomposing the BP signal into a first group of intrinsic mode functions (IMFs), decomposing the BFV signal into a second group of IMFs, determining dominant oscillatory frequencies in the first group of IMFs, automatically selecting a first characteristic IMF from the first group of IMFs that has its associated dominant oscillatory frequency in a predetermined frequency range, automatically selecting a second characteristic IMF from the second group of IMFs, calculating a time sequence of instantaneous phase difference between the first characteristic IMF and the second characteristic IMF, computing an average of the instantaneous phase difference in the time sequence, and identifying a pathological condition in the first individual.
摘要翻译：用于动态脑自动调节（CA）评估的方法包括从第一个体获取具有第一振荡模式的血压（BP）信号，从第一个体获取具有第二振荡模式的血流速度（BFV）信号，分解 BP信号转换成第一组固有模式函数（IMF），将BFV信号分解成第二组IMF，确定第一组IMF中的主要振荡频率，从具有第一组IMF的第一组IMF中自动选择第一特征IMF 其在预定频率范围内的相关主导振荡频率，自动从第二组IMF中选择第二特征IMF，计算第一特征IMF和第二特征IMF之间的瞬时相位差的时间序列，计算瞬时相位的平均值时间序列差异，并鉴定病理状况第一个人。

9. 发明授权

US08380305B2 System and method for predicting successful defibrillation for ventricular fibrillation cardiac arrest 有权
标题翻译：用于预测心室颤动心脏骤停的成功除颤的系统和方法
公开(公告)号：US08380305B2
公开(公告)日：2013-02-19
申请号：US12829286
申请日：2010-07-01
申请人： Men-Tzung Lo , Lian-Yu Lin , Patrick Chow-In Ko , Chen Lin , Matthew Huei-Ming Ma
发明人： Men-Tzung Lo , Lian-Yu Lin , Patrick Chow-In Ko , Chen Lin , Matthew Huei-Ming Ma
IPC分类号： A61N1/362
CPC分类号： A61N1/3925 , A61H31/005 , A61H2230/04 , A61N1/3702
摘要： A computer-assisted method for quantitative characterization and treatment of ventricular fibrillation includes acquiring a time series of a ventricular fibrillation (VF) signal using a probe from a patient experiencing VF, subtracting the mean from the time series of the VF signal, calculating a cumulative VF signal after the mean is subtracted from the time series of the VF signal, segmenting the cumulative VF signal by a plurality of sampling boxes, calculating the root-mean-square of the cumulative VF signal as a function of the sampling box size , extracting an exponent of the root-mean-square of the cumulative VF signal as a function of the sampling box size, applying electrical defibrillation to the patient if the exponent is below a predetermined value, and applying cardiopulmonary resuscitation (CPR) to the patient if the exponent is above a predetermined value.
摘要翻译：用于定量表征和治疗心室颤动的计算机辅助方法包括使用来自经历VF的患者的探针获取心室颤动（VF）信号的时间序列，从VF信号的时间序列中减去平均值，计算累积从VF信号的时间序列中减去平均值之后的VF信号，通过多个采样盒分割累积VF信号，计算作为采样箱大小的函数的累积VF信号的均方根，提取累积VF信号的均方根的指数作为采样箱尺寸的函数，如果指数低于预定值，则向患者施加电除颤，并且如果所述指数低于预定值则应用心肺复苏（CPR）指数高于预定值。

10. 发明授权

US08211022B2 Systems and methods for assessing dynamic cerebral autoregulation 有权
标题翻译：评估动态脑自动调节的系统和方法
公开(公告)号：US08211022B2
公开(公告)日：2012-07-03
申请号：US12273386
申请日：2008-11-18
申请人： Men-Tzung Lo , Yanhui Liu
发明人： Men-Tzung Lo , Yanhui Liu
IPC分类号： A61B8/00 , A61B8/14 , A61B6/00
CPC分类号： A61B8/06 , A61B5/02028 , A61B5/021 , A61B5/026 , A61B5/1455 , A61B5/4064 , A61B8/0808
摘要： A method for dynamic cerebral autoregulation (CA) assessment includes acquiring a blood pressure (BP) signal having a first oscillatory pattern from a first individual, acquiring a blood flow velocity (BFV) signal having a second oscillatory pattern from the first individual, decomposing the BP signal into a first group of intrinsic mode functions (IMFs), decomposing the BFV signal into a second group of IMFs, determining dominant oscillatory frequencies in the first group of IMFs, automatically selecting a first characteristic IMF from the first group of IMFs that has its associated dominant oscillatory frequency in a predetermined frequency range, automatically selecting a second characteristic IMF from the second group of IMFs, calculating a time sequence of instantaneous phase difference between the first characteristic IMF and the second characteristic IMF, computing an average of the instantaneous phase difference in the time sequence, and identifying a pathological condition in the first individual.
摘要翻译：用于动态脑自动调节（CA）评估的方法包括从第一个体获取具有第一振荡模式的血压（BP）信号，从第一个体获取具有第二振荡模式的血流速度（BFV）信号，分解 BP信号转换成第一组固有模式函数（IMF），将BFV信号分解成第二组IMF，确定第一组IMF中的主要振荡频率，从具有第一组IMF的第一组IMF中自动选择第一特征IMF 其在预定频率范围内的相关主导振荡频率，自动从第二组IMF中选择第二特征IMF，计算第一特征IMF和第二特征IMF之间的瞬时相位差的时间序列，计算瞬时相位的平均值时间序列差异，并鉴定病理状况第一个人。

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