会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 2. 发明申请
    • SYSTEM AND METHOD FOR IDENTIFYING POSTURE DETAILS AND EVALUATING ATHLETES' PERFORMANCE
    • 识别姿势细节的系统和方法和评估运动员的表现
    • WO2017025979A1
    • 2017-02-16
    • PCT/IN2016/000205
    • 2016-08-10
    • ANSHUMAN KUMAR SINGH
    • ANSHUMAN KUMAR SINGH
    • G06F19/30A61B5/00G06N7/00
    • A61B5/00A61B5/0002A61B5/1116A61B5/1118A61B5/1128A61B2503/10G06N7/00
    • The embodiments herein provide a system and method for collecting specific form and posture related visual data from an athlete for analysis. The form-related diagnosis is extracted from an athlete's video recording to establish a correlation between predicted analysis and actual observation. The data related to specific form and posture are collected from a person's pictures taken at specific angles and videos of a person performing a predefined activity for the review by experts. The picture or video of user while performing an exercise/a sport activity is captured. The posture, symmetry and body structure details are identified through visual recognition of bones, muscles or preset points. A quantitative identification/estimation of load-bearing and stress-bearing capability of a body part is done. A personalized grade sensitivity matrix is calculated/computed to provide an intuitive representation of data and multiple outputs with different renderings of data.
    • 本文的实施例提供了用于从运动员收集特定形式和姿势的视觉数据以进行分析的系统和方法。 从运动员的视频录像中提取形式相关的诊断,以建立预测分析与实际观察之间的相关性。 与特定形式和姿势有关的数据是从一个人的特定角度拍摄的照片和执行预定义活动的人的视频从专家的审查中收集的。 捕获在执行锻炼/运动活动时用户的图片或视频。 通过视觉识别骨骼,肌肉或预设点来识别姿势,对称性和身体结构细节。 完成身体部位的承载能力和应力承载能力的定量识别/估计。 计算/计算个性化级灵敏度矩阵,以提供具有不同渲染数据的数据和多个输出的直观表示。
    • 4. 发明申请
    • VESSEL ANNOTATOR.
    • VESSEL AN AN。
    • WO2013038290A1
    • 2013-03-21
    • PCT/IB2012/054430
    • 2012-08-29
    • KONINKLIJKE PHILIPS ELECTRONICS N.V.BARLEY, Maya EllaELENBAAS, ThijsFLORENT, Raoul
    • BARLEY, Maya EllaELENBAAS, ThijsFLORENT, Raoul
    • G06F19/30
    • G06F17/241G06F3/04812G06F3/04842G06F19/00G06F19/321
    • The present invention relates to annotating a medical image. For an improved manual insertion of information in a medical image, it is provided to display an image (130) of a tubular structure; and to display a graphical representation (132) of at least one segmented portion of the tubular structure; wherein the graphical representation comprises at least one indicator line representing the portion's shape and/or extension; and wherein the graphical representation is displayed in combination with the image of the tubular structure; and to generate and display at least one marker (128) overlaid to the image of the tubular structure; wherein the marker is movable (134) along the graphical representation; and to position the marker at a location along the graphical representation to indicate a predetermined feature of the tubular structure.
    • 本发明涉及注释医学图像。 为了在医学图像中改进手动插入信息,提供用于显示管状结构的图像(130); 并且显示管状结构的至少一个分段部分的图形表示(132); 其中所述图形表示包括表示所述部分的形状和/或延伸的至少一个指示线; 并且其中所述图形表示与所述管状结构的图像结合显示; 并且产生和显示覆盖在管状结构的图像上的至少一个标记(128); 其中所述标记物沿着所述图形表示是可移动的(134); 并且将标记定位在沿着图形表示的位置处以指示管状结构的预定特征。
    • 7. 发明申请
    • PATIENT CONDITION DETECTION AND MORTALITY
    • 患者状况检测和死亡率
    • WO2012085750A1
    • 2012-06-28
    • PCT/IB2011/055610
    • 2011-12-12
    • KONINKLIJKE PHILIPS ELECTRONICS N.V.CHBAT, Nicolas, Wadih
    • CHBAT, Nicolas, Wadih
    • G06F19/30
    • G06F19/345G06F19/00G16H50/20
    • When prediction onset of a medical condition for a patient, multiple sources of knowledge (112) are aggregated and modeled into a format that is usable by multiple algorithms including an inference algorithm (134), a Bayesian network (136), and a state machine (138). The outputs (116) of the multiple algorithms are then combined to more accurately predict condition onset. For instance, several knowledge sources can be input to each of the inference algorithm, the Bayesian network, and the finite state machine, and the outputs of each algorithm are combined, optionally weighted, etc., to make a final determination of the likelihood that the patient has or will imminently have the specified medical condition.
    • 当患者的医疗状况的预测开始时,多个知识源(112)被聚合并被建模为可由多种算法使用的格式,包括推理算法(134),贝叶斯网络(136)和状态机 (138)。 然后将多个算法的输出(116)组合以更准确地预测条件发作。 例如,可以向每个推理算法,贝叶斯网络和有限状态机输入几个知识源,并且将每个算法的输出组合,可选地加权等,以最终确定可能性 患者已经或将会立即具有指定的医疗状况。
    • 10. 发明申请
    • A METHOD FOR EVALUATING MEDICAL CONDITION INSURABILITY RISK
    • 一种评估医疗条件不可避免风险的方法
    • WO2015041974A1
    • 2015-03-26
    • PCT/US2014/055596
    • 2014-09-15
    • INNODATA SYNODEX, LLC
    • KEMP, Richard, D.JENSEN, Sam
    • G06Q40/08G06Q50/24G06F19/30
    • G06Q40/08G06F19/00G06Q50/22G16H10/60G16H50/30
    • Methods, apparatuses, and computer readable media for evaluating medical condition insurability risk are provided. A digital communication including an indication of a medical condition associated with an individual is received. A presumptive medical condition risk score is generated for the individual based on the indication of the medical condition and presumptive medical condition risk criteria. One or more medical records associated with the individual are retrieved via a data storage device. A composite medical condition risk score for the individual is generated based on the one or more medical records, and a correlation between the presumptive medical condition risk score and the composite medical condition risk score is determined.
    • 提供了用于评估医疗状况可靠性风险的方法,装置和计算机可读介质。 接收包括与个人相关联的医疗状况的指示的数字通信。 根据医疗条件和推定医疗状况风险标准的指示,为个人产生推定的医疗状况风险评分。 通过数据存储装置检索与个人相关联的一个或多个病历。 基于一个或多个医疗记录生成个体的复合医疗状况风险评分,并且确定推定医疗状况风险评分与综合医疗状况风险评分之间的相关性。