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    Automatic cardiac therapy advisor with hidden markov model processing
    2.
    发明授权
    Automatic cardiac therapy advisor with hidden markov model processing 有权
    自动心脏治疗顾问与隐马尔可夫模型处理

    公开(公告)号：US09339436B2

    公开(公告)日：2016-05-17

    申请号：US13454061

    申请日：2012-04-23

    申请人： Gary A. Freeman ,  James E. Brewer

    发明人： Gary A. Freeman ,  James E. Brewer

    IPC分类号： A61B5/02 ,  A61H31/00 ,  A61B5/0464 ,  A61N1/39 ,  G09B23/28 ,  A61B5/00

    CPC分类号： A61B5/7264 ,  A61B5/0464 ,  A61B5/7207 ,  A61B5/7257 ,  A61B5/726 ,  A61H31/005 ,  A61H2201/5015 ,  A61H2230/04 ,  A61N1/3925 ,  G06F19/00 ,  G09B23/288 ,  Y10S128/92 ,  Y10S128/923 ,  Y10S128/924 ,  Y10S706/924

    摘要： A method of automatically determining which type of treatment is most appropriate for (or the physiological state of) a patient. The method comprises transforming one or more time domain measurements from the patient into frequency domain data representative of the frequency content of the time domain measurements; processing the frequency domain data to form a plurality of spectral bands, the content of a spectral band representing the frequency content of the measurements within a frequency band; forming a weighted sum of the content of the spectral bands, with different weighting coefficients applied to at least some of the spectral bands; determining the type of treatment (or physiological state) based on the weighted sum.

    摘要翻译： 一种自动确定哪种类型的治疗最适合患者的（或生理状态）的方法。 该方法包括将来自患者的一个或多个时域测量值转换为表示时域测量的频率内容的频域数据; 处理频域数据以形成多个频谱带，表示频带内的测量的频率内容的频谱带的内容; 形成对频谱带的内容的加权和，其中加权系数应用于至少一些频谱带; 基于加权和确定治疗类型（或生理状态）。

    Method, system and apparatus for encouraging frequent and purposeful electronic communications from caregivers to individuals with impaired memory
    5.
    发明申请
    Method, system and apparatus for encouraging frequent and purposeful electronic communications from caregivers to individuals with impaired memory 有权
    方法，系统和设备，用于鼓励从护理人员到记忆受损的个人频繁和有目的的电子通信

    公开(公告)号：US20100191824A1

    公开(公告)日：2010-07-29

    申请号：US12583107

    申请日：2009-08-13

    申请人： Ted Lindsay

    发明人： Ted Lindsay

    IPC分类号： G06F3/01 ,  G06F15/16

    CPC分类号： H04M1/72588 ,  G06F19/00 ,  G06F19/3456 ,  G06Q50/22 ,  G06Q50/24 ,  G16H40/63 ,  Y10S706/924

    摘要： A computer implemented system and method for encouraging frequent and purposeful electronic communications from caregivers to individuals with impaired memory to, inter alia, alleviate feelings of isolation and improve memory. The system includes a Web-based application through which caregivers send text, image, voice and other forms of data for receipt by the sufferer on a PDA having a simple user interface. The Web application records the dates and nature (i.e., text, audio, photograph, video) of communications sent by each caregiver, processes the data in order to display it in a variety of meaningful ways to all caregivers, thus creating a peer-pressure environment to encourage more frequent communication. The Web application can also be programmed to send electronic reminders to all caregivers who opt-in to the service requesting that they send a communication to the sufferer, and more particularly to individual caregivers whose frequency of communication has been inadequate relative to a group of caregivers or to predefined expectations.

    摘要翻译： 一种计算机实施的系统和方法，用于鼓励从照顾者到具有受损记忆的个体的频繁和有目的的电子通信，以特别地减轻隔离感和改善记忆。 该系统包括基于Web的应用程序，通过该应用程序，护理人员发送文本，图像，语音和其他形式的数据，以便患者在具有简单用户界面的PDA上接收。 Web应用程序记录每个护理人员发送的通信的日期和性质（即文本，音频，照片，视频），处理数据，以便以各种有意义的方式向所有护理人员显示数据，从而创建对等压力 鼓励环境更频繁的沟通。 Web应用程序还可以被编程为向选择服务的所有照顾者发送电子提醒，要求他们向受害者发送通信，更具体地，涉及相对于一组照顾者的通信频率不足的个人照顾者 或预定的期望。

    Individual system performance management
    7.
    发明授权
    Individual system performance management 有权
    个人系统绩效管理

    公开(公告)号：US07701353B1

    公开(公告)日：2010-04-20

    申请号：US11618133

    申请日：2006-12-29

    申请人： Carlos W. Moreno

    发明人： Carlos W. Moreno

    IPC分类号： G08B23/00

    CPC分类号： G16H50/50 ,  A61B5/14532 ,  A61B5/7267 ,  G06F19/00 ,  G16H50/20 ,  Y10S706/924

    摘要： Individual System Performance Management apparatus employs in one manifestation Sequential Empirical Optimization (SEO) in its illustrative version to manage a sequence of periodic readjustment to adjust inputs of an input/output system with the aim to maximize the cumulative sequence of overall value delivered by the system. SEO continually updates its learning from the stored run data. In this discussion, the term “adjusting” control inputs is used the same as “setting” control inputs, including adjusting or setting things by hand.

    摘要翻译： 单个系统性能管理装置在其说明性版本中采用一种表现型顺序经验优化（SEO）来管理一系列周期性重新调整以调整输入/输出系统的输入，目的是最大化系统传递的总体值的累积序列 。 SEO不断更新其存储的运行数据的学习。 在本次讨论中，术语“调整”控制输入与“设置”控制输入相同，包括手动调整或设置。

    DIALYSIS SYSTEM HAVING REGIMEN GENERATION METHODOLOGY
    8.
    发明申请
    DIALYSIS SYSTEM HAVING REGIMEN GENERATION METHODOLOGY 有权
    具有计量生成方法的透析系统

    公开(公告)号：US20100010424A1

    公开(公告)日：2010-01-14

    申请号：US12170184

    申请日：2008-07-09

    申请人： Anping Yu ,  Robert W. Childers ,  Edward F. Vonesh ,  Borut Cizman

    发明人： Anping Yu ,  Robert W. Childers ,  Edward F. Vonesh ,  Borut Cizman

    IPC分类号： A61M1/28

    CPC分类号： A61M1/28 ,  A61M1/281 ,  A61M1/282 ,  A61M1/287 ,  A61M2205/502 ,  G06F19/00 ,  G06F19/3418 ,  G06F19/3481 ,  G16H10/60 ,  G16H50/50 ,  Y10S706/924

    摘要： A peritoneal dialysis system includes a logic implementer configured to: (i) accept at least one therapy target input; (ii) accept at least one patient transport characteristic input; (iii) accept at least one solution input; (iv) accept at least one fluid volume input; (v) accept at least one therapy time input, at least one of the inputs (ii) to (v) including an input range; and (vi) generate each therapy regimen using the inputs of (ii), (iii), (iv) and (v), including each of the possibilities within the at least one input range, that satisfy the at least one therapy target input.

    摘要翻译： 腹膜透析系统包括逻辑实现器，其被配置为：（i）接受至少一个治疗目标输入; （ii）接受至少一个患者运输特征输入; （iii）接受至少一个解决方案输入; （iv）接受至少一个流体体积输入; （v）接受至少一个治疗时间输入，所述输入（ii）至（v）中的至少一个包括输入范围; 和（vi）使用（ii），（iii），（iv）和（v）的输入产生每种治疗方案，包括满足至少一种治疗目标输入的至少一个输入范围内的每种可能性 。

    Neural Network for Processing Arrays of Data with Existent Topology, Such as Images and Application of the Network
    9.
    发明申请
    Neural Network for Processing Arrays of Data with Existent Topology, Such as Images and Application of the Network 有权
    用于处理具有一般拓扑的数据数组的神经网络，如图像和网络的应用

    公开(公告)号：US20070233624A1

    公开(公告)日：2007-10-04

    申请号：US10569354

    申请日：2004-08-18

    申请人： Paolo Buscema

    发明人： Paolo Buscema

    IPC分类号： G06F15/18

    CPC分类号： G06K9/4609 ,  G06N3/02 ,  G06T5/20 ,  G06T2207/20084 ,  Y10S706/924

    摘要： A neural network for processing arrays of data with pertinent topology comprises a n-dimensional array of cells (Ki) corresponding to the knots of the neural network! each cell having connections to the directly adjacent cells (Kj) forming the neighbourhood of a cell (Ki); Each cell (Ki) having inputs for each connection to directly adjacent cells; an output for the connection to one or more of the directly adjacent cells (Kj); the connection between the cells being determined by weights (wij); each cell being characterised by an internal value and being able to carry out signal processing for generating a cell output signal (ui); the output signal (ui) of a cell (Ki) being a function of its internal value and of the input signals form the neighbouring cells; each cell being associated univoquely to a record of a n-dimensional database (Pi) with pertinent topology and the value of each data record being the starting value of the corresponding cell. Processing is carried out by considering the internal value or the output value (ui) of each cell (Ki) after a certain number of iterative processing steps of the neural network as the new obtained value (Ui) for the said univocally associated data records (Pi).

    摘要翻译： 用于处理具有相关拓扑的数据阵列的神经网络包括与神经网络的结相对应的细胞的n维阵列（Ki）！ 每个单元具有连接到形成单元（Ki）附近的直接相邻单元（Kj）的连接; 每个单元（Ki）具有与直接相邻单元的每个连接的输入; 用于连接到一个或多个直接相邻单元（Kj）的输出; 单元之间的连接由权重（wij）确定; 每个单元的特征在于内部值，并且能够执行用于产生单元输出信号（ui）的信号处理; 作为其内部值和输入信号的函数的单元（Ki）的输出信号（ui）形成相邻单元; 每个单元被非正式地关联到具有相关拓扑的n维数据库（Pi）的记录，并且每个数据记录的值是相应单元的起始值。 通过考虑在神经网络的一定数量的迭代处理步骤之后的每个单元格（Ki）的内部值或输出值（ui）作为所述单向相关联的数据记录的新获得值（Ui）来进行处理（ Pi）。

    METHOD AND APPARATUS FOR MULTIVARIABLE ANALYSIS OF BIOLOGICAL MEASUREMENTS
    10.
    发明申请
    METHOD AND APPARATUS FOR MULTIVARIABLE ANALYSIS OF BIOLOGICAL MEASUREMENTS 有权
    生物测量多元分析的方法与装置

    公开(公告)号：US20070226157A1

    公开(公告)日：2007-09-27

    申请号：US11754516

    申请日：2007-05-29

    申请人： Zvi KAM

    发明人： Zvi KAM

    IPC分类号： G06N3/02

    CPC分类号： G06N3/02 ,  G06F19/12 ,  G06F19/20 ,  G06F19/24 ,  G06F19/26 ,  Y10S706/924

    摘要： In a method and apparatus for analyzing multivariable data sets, a general computerized platform is provided for evaluating the relationship between large number of measurements of sets of variables characterizing components of complex states of a system under induced stimulation or controlled conditions. The linked responses of variables and their temporal relations tell about the network of interactions and their hierarchy. Processing of data sets by a simple neural network gives a matrix of weight parameters, that allow to identify fingerprints of complex states characterized by patterns of measured variable and estimate the interactions between the components characterized by the measured variables. The results are provided numerically and by color-coded presentation indicating dominating relations between variables and strongly responding variables. When applied to dynamic responses of a system, the analysis can construct a schematic hierarchical architecture of the network of interaction between the components of the studied system. Applications in biology include analysis of measurements characterizing responses of molecular components in cells under changes induced by stimuli (e.g. drugs, growth factors, hormones, mutations or forced expression of a proteins), and identification of complex cellular states (e.g. proliferation, differentiation, transformation, starvation, necrosis, apoptosis, and the time dependencies of the above effects).

    摘要翻译： 在用于分析多变量数据集的方法和装置中，提供通用计算机化平台，用于评估在诱导刺激或受控条件下表征系统的复杂状态的分量的变量集合的大量测量之间的关系。 变量的连接响应及其时间关系说明了互动网络及其层次结构。 通过简单神经网络对数据集进行处理给出了权重参数矩阵，允许识别以测量变量的模式为特征的复杂状态的指纹，并估计由测量变量表征的分量之间的相互作用。 结果以数字方式提供，并通过颜色编码表示，指示变量和强烈响应变量之间的主导关系。 当应用于系统的动态响应时，分析可以构建所研究的系统的组件之间的相互作用网络的示意性层次结构。 生物学中的应用包括分析表征刺激（例如药物，生长因子，激素，突变或强制表达蛋白质）诱导的变化下细胞中分子组分的反应的测量结果，以及复杂细胞状态的鉴定（例如增殖，分化，转化 ，饥饿，坏死，凋亡和上述效应的时间依赖性）。