公开(公告)号：US10420516B2

公开(公告)日：2019-09-24

申请号：US15035632

申请日：2014-09-15

Applicant: GENERAL ELECTRIC COMPANY

Inventor： Gokul Swamy ,  Sahika Genc ,  Ashish Anil Rao ,  Abhijit Vishwas Patil ,  Amod Jai Ganesh Anandkumar

IPC: A61B5/0402 ,  A61B5/08 ,  A61B5/053 ,  A61B5/00 ,  A61B5/0205 ,  A61B5/021

Abstract: A method for determining a respiration rate of a subject, includes receiving a first signal and a second signal, each signal being representative of a physiological parameter of the subject. The method includes removing a cardiac artifact signal from the first signal and the second signal to generate a first processed signal and a second processed signal respectively. The method includes removing a motion artifact signal from the first processed signal and the second processed signal to generate a first periodic signal and the second processed signal respectively. The method further includes removing a residual noise signal from the first periodic signal and the second periodic signal to generate a first noise free signal and the second noise free signal respectively. The method includes generating a combined value from a first value and a second value based on the first noise free signal and the second noise free signal respectively.

公开(公告)号：US20160262705A1

公开(公告)日：2016-09-15

申请号：US15035632

申请日：2014-09-15

Applicant: GENERAL ELECTRIC COMPANY

Inventor： Gokul Swamy ,  Sahika Genc ,  Ashish Anil Rao ,  Abhijit Vishwas Patil ,  Amod Jai Ganesh Anandkumar

IPC: A61B5/00 ,  A61B5/021 ,  A61B5/0402 ,  A61B5/08 ,  A61B5/053

Abstract: A method for determining a respiration rate of a subject, includes receiving a first signal and a second signal, each signal being representative of a physiological parameter of the subject. The method includes removing a cardiac artifact signal from the first signal and the second signal to generate a first processed signal and a second processed signal respectively. The method includes removing a motion artifact signal from the first processed signal and the second processed signal to generate a first periodic signal and the second processed signal respectively. The method further includes removing a residual noise signal from the first periodic signal and the second periodic signal to generate a first noise free signal and the second noise free signal respectively. The method includes generating a combined value from a first value and a second value based on the first noise free signal and the second noise free signal respectively.

Abstract translation: 一种用于确定对象的呼吸速率的方法，包括接收第一信号和第二信号，每个信号代表所述对象的生理参数。 该方法包括从第一信号和第二信号中去除心脏假象信号以分别产生第一处理信号和第二处理信号。 该方法包括从第一处理信号和第二经处理信号中去除运动假象信号以分别产生第一周期信号和第二处理信号。 该方法还包括从第一周期信号和第二周期信号中去除残留噪声信号，分别产生第一无噪声信号和第二无噪声信号。 该方法包括分别基于第一无噪声信号和第二无噪声信号从第一值和第二值产生组合值。

公开(公告)号：US09750463B2

公开(公告)日：2017-09-05

申请号：US14101663

申请日：2013-12-10

Applicant: General Electric Company

Inventor： Gokul Swamy ,  Sahika Genc ,  Hariharan Ravishankar ,  Aditya Saha

IPC: A61B5/00 ,  A61B5/08 ,  A61B5/0205 ,  A61B5/145 ,  A61B5/20 ,  A61B5/083 ,  A61B5/021 ,  A61B5/024 ,  A61B5/01

CPC classification number: A61B5/7275 ,  A61B5/002 ,  A61B5/0022 ,  A61B5/01 ,  A61B5/02055 ,  A61B5/021 ,  A61B5/024 ,  A61B5/0816 ,  A61B5/0836 ,  A61B5/14532 ,  A61B5/14542 ,  A61B5/201 ,  A61B5/202 ,  A61B5/7203 ,  A61B5/7246 ,  A61B5/7264 ,  A61B5/746 ,  G06F19/00

Abstract: Embodiments of the disclosure are directed to a system for analysis of respiratory distress in hospitalized patients. The system performs multi-parametric simultaneous analysis of respiration rate (RR) and pulse oximetry (SpO2) data trends in order to gauge patterns of patient instability pertaining to respiratory distress. Three patterns in SpO2 and RR are used along with LOWESS algorithm and Chauvenets criteria for outlier rejection to obtain robust short term and long term trends in RR and SpO2. Pattern analysis detects the presence of any one of three pattern types proposed. Further, a learning paradigm is introduced to find unknown instances of respiratory distress. This algorithm in conjunction with the learning model allows early detection of respiratory distress in hospital ward and ICU patients.

公开(公告)号：US20140185895A1

公开(公告)日：2014-07-03

申请号：US13731140

申请日：2012-12-31

Applicant: GENERAL ELECTRIC COMPANY

Inventor： Gokul Swamy ,  Rui Li

IPC: G06K9/46

CPC classification number: A61B8/5223 ,  A61B8/0866 ,  G06K2209/05 ,  G06T7/0014 ,  G06T2207/10132 ,  G06T2207/20076 ,  G06T2207/20081 ,  G06T2207/30044

Abstract: A computer-implemented method for analyzing a fetal ultrasound image includes accessing a first statistical model calculated from training data representing shapes of conforming fetal abdominal tissue exemplars and accessing image data representing a scan plane in an ultrasound image. The method further includes identifying a region of interest including an abdomen in the scan plane using the first statistical model, accessing a second statistical model calculated from training data representing shapes of conforming fetal anatomical structure exemplars, determining whether one or more anatomical structures are present within the region of interest using the second statistical model, and assigning a rating to the scan plane based on the presence of the one or more anatomical structures in the region of interest. The anatomical structures may include a stomach and/or a portal vein. The method may include calculating an estimated circumference of the abdomen.

Abstract translation: 用于分析胎儿超声图像的计算机实现的方法包括访问由表示符合胎儿腹部组织样本的形状的训练数据计算的第一统计模型，以及访问表示超声图像中的扫描平面的图像数据。 该方法还包括使用第一统计模型来识别包括扫描平面中的腹部的感兴趣区域，访问由表示符合胎儿解剖结构样本的形状的训练数据计算的第二统计模型，确定是否存在一个或多个解剖结构 使用第二统计模型的感兴趣区域，以及基于感兴趣区域中的一个或多个解剖结构的存在，将评级分配给扫描平面。 解剖结构可以包括胃和/或门静脉。 该方法可以包括计算腹部的估计周长。

公开(公告)号：US20150157275A1

公开(公告)日：2015-06-11

申请号：US14101663

申请日：2013-12-10

Applicant: General Electric Company

Inventor： Gokul Swamy ,  Sahika Genc ,  Hariharan Ravishankar ,  Aditya Saha

IPC: A61B5/00 ,  A61B5/20 ,  A61B5/145 ,  A61B5/0205 ,  A61B5/1455

CPC classification number: A61B5/7275 ,  A61B5/002 ,  A61B5/0022 ,  A61B5/01 ,  A61B5/02055 ,  A61B5/021 ,  A61B5/024 ,  A61B5/0816 ,  A61B5/0836 ,  A61B5/14532 ,  A61B5/14542 ,  A61B5/201 ,  A61B5/202 ,  A61B5/7203 ,  A61B5/7246 ,  A61B5/7264 ,  A61B5/746 ,  G06F19/00

Abstract: Embodiments of the disclosure are directed to a system for analysis of respiratory distress in hospitalized patients. The system performs multi-parametric simultaneous analysis of respiration rate (RR) and pulse oximetry (SpO2) data trends in order to gauge patterns of patient instability pertaining to respiratory distress. Three patterns in SpO2 and RR are used along with LOWESS algorithm and Chauvenets criteria for outlier rejection to obtain robust short term and long term trends in RR and SpO2. Pattern analysis detects the presence of any one of three pattern types proposed. Further, a learning paradigm is introduced to find unknown instances of respiratory distress. This algorithm in conjunction with the learning model allows early detection of respiratory distress in hospital ward and ICU patients.

Abstract translation: 本公开的实施例涉及用于分析住院患者呼吸窘迫的系统。 系统进行呼吸速率（RR）和脉搏血氧饱和度（SpO2）数据趋势的多参数同时分析，以衡量与呼吸窘迫有关的患者不稳定状态。 使用SpO2和RR中的三种模式以及LOWESS算法和Chauvenets等离子体排斥标准，以获得RR和SpO2的强大的短期和长期趋势。 模式分析检测提出的三种模式类型中的任一种的存在。 此外，引入了一种学习范例来发现呼吸窘迫的未知事例。 该算法结合学习模型，可以及早发现医院病房和ICU患者的呼吸窘迫。

公开(公告)号：US08831311B2

公开(公告)日：2014-09-09

申请号：US13731140

申请日：2012-12-31

Applicant: General Electric Company

Inventor： Gokul Swamy ,  Rui Li

IPC: G06T7/00 ,  G06K9/46

CPC classification number: A61B8/5223 ,  A61B8/0866 ,  G06K2209/05 ,  G06T7/0014 ,  G06T2207/10132 ,  G06T2207/20076 ,  G06T2207/20081 ,  G06T2207/30044

Abstract: A computer-implemented method for analyzing a fetal ultrasound image includes accessing a first statistical model calculated from training data representing shapes of conforming fetal abdominal tissue exemplars and accessing image data representing a scan plane in an ultrasound image. The method further includes identifying a region of interest including an abdomen in the scan plane using the first statistical model, accessing a second statistical model calculated from training data representing shapes of conforming fetal anatomical structure exemplars, determining whether one or more anatomical structures are present within the region of interest using the second statistical model, and assigning a rating to the scan plane based on the presence of the one or more anatomical structures in the region of interest. The anatomical structures may include a stomach and/or a portal vein. The method may include calculating an estimated circumference of the abdomen.

Abstract translation: 用于分析胎儿超声图像的计算机实现的方法包括访问由表示符合胎儿腹部组织样本的形状的训练数据计算的第一统计模型，以及访问表示超声图像中的扫描平面的图像数据。 该方法还包括使用第一统计模型来识别包括扫描平面中的腹部的感兴趣区域，访问由表示符合胎儿解剖结构样本的形状的训练数据计算的第二统计模型，确定是否存在一个或多个解剖结构 使用第二统计模型的感兴趣区域，以及基于感兴趣区域中的一个或多个解剖结构的存在，将评级分配给扫描平面。 解剖结构可以包括胃和/或门静脉。 该方法可以包括计算腹部的估计周长。