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1. 发明申请

WO2017220353A1 TEMPLATE-BASED ANALYSIS AND CLASSIFICATION OF CARDIOVASCULAR WAVEFORMS 审中-公开
标题翻译：基于模板的心血管波形分析与分类
公开(公告)号：WO2017220353A1
公开(公告)日：2017-12-28
申请号：PCT/EP2017/064218
申请日：2017-06-12
申请人： KONINKLIJKE PHILIPS N.V.
发明人： GHOSH, Erina , POTES BLANDON, Cristhian Mauricio , GREGG, Richard Earl
IPC分类号： A61B5/0456 , A61B5/0452 , A61B5/00 , A61B5/04 , A61B5/0215 , A61B5/0295 , A61B5/0468 , A61B5/0472
摘要： In various embodiments, a first classification assigned to a periodic component of an electrical waveform that represents electrical activity in a patient's heart may be identified (302). A corresponding periodic component of a hemodynamic waveform that represents hemodynamic activity in the patient's cardiovascular system may be analyzed (306, 318, 328). The corresponding periodic component may be causally related to the periodic component of the electrical waveform. Based on the analysis, the previously-assigned classification may be assigned (312, 324) to the corresponding periodic component of the hemodynamic waveform in response to a determination, based on the analyzing, that the previously-assigned classification also applies to the corresponding periodic component. In a database (130) of hemodynamic templates, a hemodynamic template associated with the previously-assigned classification may be updated (314) to include one or more features of the corresponding periodic component of the hemodynamic waveform.
摘要翻译：在各种实施例中，可以识别（302）分配给表示患者心脏中的电活动的电波形的周期性分量的第一分类。可以分析代表患者心血管系统中血液动力学活性的血液动力学波形的相应周期分量（306,318,328）。相应的周期性分量可能与电波形的周期性分量有因果关系。基于该分析，响应于基于该分析的确定，先前分配的分类可以被分配（312,324）到血液动力波形的对应周期分量，即先前分配的分类也适用于相应的周期零件。在血液动力学模板的数据库（130）中，与先前分配的分类相关联的血液动力学模板可以被更新（314）以包括血液动力学波形的对应周期性分量的一个或多个特征。

2. 发明申请

WO2017141131A1 SYSTEM AND METHOD FOR DETERMINING A HEMODYNAMIC INSTABILITY RISK SCORE FOR PEDIATRIC SUBJECTS 审中-公开
标题翻译：用于确定小儿对象的血流动力学不稳定性风险分数的系统和方法
公开(公告)号：WO2017141131A1
公开(公告)日：2017-08-24
申请号：PCT/IB2017/050620
申请日：2017-02-04
申请人： KONINKLIJKE PHILIPS N.V.
发明人： POTES BLANDON, Cristhian Mauricio , XU, Minnan , CONROY, Bryan
IPC分类号： A61B5/02 , G06F19/00 , A61B5/00 , A61B5/08 , A61B5/145 , A61B5/20 , A61B5/107
CPC分类号： A61B5/02028 , A61B5/02 , A61B5/08 , A61B5/1072 , A61B5/145 , A61B5/208 , A61B5/7275 , A61B2503/06 , G06F19/00 , G16H50/30
摘要： The present disclosure pertains to a system configured to determine a hemodynamic instability risk score for a pediatric subject. The system is configured to: obtain an age of the subject; obtain feature values for one or more features associated with physiological characteristics of the subject; determine one or more feature value thresholds for individual features that indicate risk of hemodynamic instability in the subject, the feature value thresholds determined based on the age of the subject; determine feature contribution prediction scores for the individual features based on whether the obtained feature values breach one or more of the determined feature value thresholds for the individual features; and aggregate the feature contribution prediction scores to determine the hemodynamic instability risk score for the subject.
摘要翻译：本公开涉及被配置成确定儿科患者的血液动力学不稳定风险评分的系统。该系统被配置为：获得对象的年龄; 获得与所述对象的生理特征相关联的一个或多个特征的特征值; 确定指示所述对象中血液动力学不稳定性的风险的各个特征的一个或多个特征值阈值，所述特征值阈值基于所述对象的年龄确定; 基于获得的特征值是否违反针对各个特征的一个或多个所确定的特征值阈值来确定各个特征的特征贡献预测分数; 并汇总特征贡献预测分数以确定受试者的血流动力学不稳定风险评分。

3. 发明申请

WO2017089921A1 METHOD TO QUANTIFY PHOTOPLETHYSMOGRAM (PPG) SIGNAL QUALITY 审中-公开
标题翻译：量化光电图（PPG）信号质量的方法
公开(公告)号：WO2017089921A1
公开(公告)日：2017-06-01
申请号：PCT/IB2016/056762
申请日：2016-11-10
申请人： KONINKLIJKE PHILIPS N.V.
发明人： GHOSH, Erina , POTES BLANDON, Cristhian Mauricio
IPC分类号： A61B5/00 , A61B5/024 , A61B5/0245 , A61B5/0456 , A61B5/021 , G06K9/00
CPC分类号： A61B5/7203 , A61B5/02116 , A61B5/02125 , A61B5/02416 , A61B5/0245 , A61B5/0456 , A61B5/7221 , A61B5/7246 , A61B5/7264 , G06K9/0053 , G06K9/00543
摘要： When evaluating the quality of photoplethysmography (PPG) signal (52) measured from a patient monitor (e.g., a finger sensor or the like), multiple features of the PPG signal are extracted and analyzed to facilitate assigning a score to the PPG signal or portions (e.g., heartbeats) thereof. Heartbeats in the PPG signal are segmented out using concurrently captured electrocardiograph (ECG) signal (50), and for each heartbeat, a plurality of extracted features are analyzed. If all extracted features satisfy one or more predetermined criteria for each feature, then the heartbeat waveform is compared to a predefined heartbeat template. If the waveform matches the template (e.g., within a predetermined match percentage or the like), then the heartbeat is classified as "clean." If the heartbeat does not patch the template, or if one or more of the extracted features fails to satisfy its one or more predetermined criteria, the heartbeat is classified as "noisy."
摘要翻译：当评估从患者监测器（例如，手指传感器等）测量的光电容积脉搏波图（PPG）信号（52）的质量时，提取并分析PPG信号的多个特征以便于指派对PPG信号或其部分（例如，心跳）的评分。使用同时捕获的心电图（ECG）信号（50）分割出PPG信号中的心跳，并且对于每个心跳，分析多个提取的特征。如果所有提取的特征满足每个特征的一个或多个预定标准，则将心跳波形与预定义的心跳模板进行比较。如果波形与模板匹配（例如，在预定的匹配百分比等内），则心跳被分类为“干净”。如果心跳不修补模板，或者如果一个或多个提取的特征不能满足其一个或多个预定标准，则心跳被分类为“嘈杂”。

4. 发明申请

WO2018234427A1 HYPOXIA DETECTION 审中-公开
公开(公告)号：WO2018234427A1
公开(公告)日：2018-12-27
申请号：PCT/EP2018/066531
申请日：2018-06-21
申请人： KONINKLIJKE PHILIPS N.V.
发明人： POTES BLANDON, Cristhian Mauricio , MILOSEVIC, Mladen , PARVANEH, Saman , GHOSH, Erina
IPC分类号： A61B5/024 , A61B5/0245 , A61B5/0295 , A61B5/0402 , A61B5/04 , A61B5/0404 , A61B5/0452 , A61B5/1455 , A61B5/00
CPC分类号： A61B5/0402 , A61B5/02416 , A61B5/04012 , A61B5/0404 , A61B5/0452 , A61B5/14551 , A61B5/681 , A61B5/7275 , G16H40/63 , G16H50/20 , G16H50/30
摘要： Methods and systems for hypoxia detection based on baroreflex sensitivity (BRS). The system in accordance with various embodiments described herein may include wearable sensor devices to gather electrocardiography data and plethysmography data of a user. The system may then generate one or more baroreflex sensitivity features based on the gathered data. A hypoxia detection module may consider the generated baroreflex sensitivity features and the user's context to determine whether the user is at risk of hypoxia.

5. 发明申请

WO2018192831A1 LEARNING AND APPLYING CONTEXTUAL SIMILARITIES BETWEEN ENTITIES 审中-公开
公开(公告)号：WO2018192831A1
公开(公告)日：2018-10-25
申请号：PCT/EP2018/059358
申请日：2018-04-12
申请人： KONINKLIJKE PHILIPS N.V.
发明人： CONROY, Bryan , XU, Minnan , RAHMAN, Asif , POTES BLANDON, Cristhian Mauricio
IPC分类号： G16H50/70
摘要： Techniques disclosed herein relate to learning and applying contextual patient similarities. Multiple template similarity functions (118) may be provided (602). Each template similarity function may compare a respective subset of features of a query entity feature vector with a corresponding subset of features of a candidate entity feature vector. A composite similarity function (120) may be provided (604) as a weighted combination of respective outputs of the template similarity functions. A plurality of labeled entity vectors may be provided (606) as context training data. An approximation function may be applied (608) to approximate a first context label for each respective labeled entity vector. A first context specific composite similarity function may be trained (610) based on the composite similarity function by learning first context weights for the template similarity functions using a first loss function based on output of application of the approximation function to the first context training data.

6. 发明申请

WO2018029028A1 ELECTRONIC CLINICAL DECISION SUPPORT DEVICE BASED ON HOSPITAL DEMOGRAPHICS 审中-公开
标题翻译：基于医院人口统计的电子临床决策支持装置
公开(公告)号：WO2018029028A1
公开(公告)日：2018-02-15
申请号：PCT/EP2017/069365
申请日：2017-08-01
申请人： KONINKLIJKE PHILIPS N.V.
发明人： CONROY, Bryan , POTES BLANDON, Cristhian Mauricio , XU, Minnan
IPC分类号： G06F19/00
摘要： An electronic clinical decision support (CDS) device (10) employs a trained CDS algorithm (30) that operates on values of a set of covariates to output a prediction of a medical condition. The CDS algorithm was trained on a training data set (22). The CDS device includes a computer (12) that is programmed to provide a user interface (62) for completing clinical survey questions using the display and the one or more user input devices. Marginal probability distributions (42) for the covariates of the set of covariates are generated from the completed clinical survey questions. The trained CDS algorithm is adjusted for covariate shift using the marginal probability distributions. A prediction of the medical condition is generated for a medical subject using the trained CDS algorithm adjusted for covariate shift (50) operating on values for the medical subject of the covariates of the set of covariates.
摘要翻译：电子临床决策支持（CDS）设备（10）采用训练的CDS算法（30），其对一组协变量的值进行操作以输出医学病症的预测。 CDS算法在训练数据集上训练（22）。 CDS装置包括计算机（12），其被编程为提供用于使用显示器和一个或多个用户输入装置完成临床调查问题的用户界面（62）。完成的临床调查问题产生协变量组的协变量的边际概率分布（42）。使用边际概率分布对训练后的CDS算法进行协变量调整。使用训练后的CDS算法针对协变量（50）进行调整以针对协变量集合的协变量的医学主题的值进行操作，为医学对象生成医学状况的预测。

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