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1.发明申请公开(公告)号：US20130254141A1
公开(公告)日：2013-09-26
申请号：US13704153
申请日：2011-06-16
CPC分类号： A61F13/42 , G06N5/04 , G06N7/005 , G06N99/005
摘要： The present invention relates to sensor signal analysis. It relates particularly, but not exclusively, to methods, systems and devices for monitoring and processing the sensor signals to determine automatically characteristics of events represented by the sensor signals. The present invention is particularly, but not exclusively, related to methods, systems and devices for monitoring moisture in absorbent articles such as diapers, incontinence garments, dressings and pads resulting from wetness events caused by, for example, urinary and/or faecal incontinence. In an embodiment, the invention includes a method for processing sensor signals representing an event in an absorbent article. The method comprises: receiving sensor signals from a sensor representing one or more events in an absorbent article; and processing the sensor signals to determine a characteristic of at least one event in the absorbent article. One such characteristic can include the volume of a voiding event such as a urinary incontinence event. In another embodiment, the method includes carrying out a learning phase including the steps of: receiving sensor signals representing one or more events in each of one or more absorbent articles; receiving observation data indicative of a cumulative characteristic of the one or more events in each absorbent article; and identifying an optimal mathematical model describing a relationship between the sensor signals and the observation data. Such events can include urinary incontinence events occurring in absorbent articles such as diapers. Observation data can be measured cumulative volume of a cycle of voiding events occurring in a diaper.
摘要翻译： 本发明涉及传感器信号分析。 它特别涉及但不排他地涉及用于监视和处理传感器信号以自动确定由传感器信号表示的事件特征的方法，系统和装置。 本发明特别但并非排他地涉及用于监测吸收制品中的水分的方法，系统和装置，例如由例如尿和/或粪便失禁引起的湿度事件导致的尿布，失禁衣服，敷料和垫片。 在一个实施例中，本发明包括一种用于处理代表吸收制品中事件的传感器信号的方法。 该方法包括：从代表吸收制品中的一个或多个事件的传感器接收传感器信号; 以及处理所述传感器信号以确定所述吸收制品中至少一个事件的特征。 一个这样的特征可以包括排尿事件的体积，例如尿失禁事件。 在另一个实施例中，该方法包括执行学习阶段，包括以下步骤：接收表示一个或多个吸收制品中的每一个中的一个或多个事件的传感器信号; 接收指示每个吸收制品中的一个或多个事件的累积特性的观测数据; 并且识别描述传感器信号和观测数据之间的关系的最佳数学模型。 这种事件可以包括发生在诸如尿布的吸收制品中的尿失禁事件。 观察数据可以测量在尿布中发生的排尿事件的循环的累积体积。
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公开(公告)号：US09646073B2
公开(公告)日：2017-05-09
申请号：US14130833
申请日：2012-07-05
CPC分类号： G06F17/30595 , A61F13/42 , G06Q50/22
摘要： A method for analyzing incoming data, comprising the steps of processing the incoming data in segments to output a sequence of segment types by extracting one or more properties of an incoming data segment and forming an Unknown Property Vector for each segment of data in the incoming data, and processing the sequence of segment types to identify events in the incoming data. The sequence of segment types is determined, for each segment, by reference to a set of Reference Property Vectors that are relevant to the Unknown Property Vector. This may involve application of first and/or second and/or further functions to identify at least a first subset of Reference Property Vectors that are relevant to the Unknown Property Vector. Alternatively, a logistic regression algorithm, derived using clustering or classification methods for identifying candidate vectors, may be used.
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3.发明授权公开(公告)号：US09224102B2
公开(公告)日：2015-12-29
申请号：US13704153
申请日：2011-06-16
CPC分类号： A61F13/42 , G06N5/04 , G06N7/005 , G06N99/005
摘要： The present invention relates to sensor signal analysis. It relates particularly, but not exclusively, to methods, systems and devices for monitoring and processing the sensor signals to determine automatically characteristics of events represented by the sensor signals. The present invention is particularly, but not exclusively, related to methods, systems and devices for monitoring moisture in absorbent articles such as diapers, incontinence garments, dressings and pads resulting from wetness events caused by, for example, urinary and/or faecal incontinence. In an embodiment, the invention includes a method for processing sensor signals representing an event in an absorbent article. The method comprises: receiving sensor signals from a sensor representing one or more events in an absorbent article; and processing the sensor signals to determine a characteristic of at least one event in the absorbent article. One such characteristic can include the volume of a voiding event such as a urinary incontinence event. In another embodiment, the method includes carrying out a learning phase including the steps of: receiving sensor signals representing one or more events in each of one or more absorbent articles; receiving observation data indicative of a cumulative characteristic of the one or more events in each absorbent article; and identifying an optimal mathematical model describing a relationship between the sensor signals and the observation data. Such events can include urinary incontinence events occurring in absorbent articles such as diapers. Observation data can be measured cumulative volume of a cycle of voiding events occurring in a diaper.
摘要翻译： 本发明涉及传感器信号分析。 它特别涉及但不排他地涉及用于监视和处理传感器信号以自动确定由传感器信号表示的事件特征的方法，系统和装置。 本发明特别但并非排他地涉及用于监测吸收制品中的水分的方法，系统和装置，例如由例如尿和/或粪便失禁引起的湿度事件导致的尿布，失禁衣服，敷料和垫片。 在一个实施例中，本发明包括一种用于处理代表吸收制品中事件的传感器信号的方法。 该方法包括：从代表吸收制品中的一个或多个事件的传感器接收传感器信号; 以及处理所述传感器信号以确定所述吸收制品中至少一个事件的特征。 一个这样的特征可以包括排尿事件的体积，例如尿失禁事件。 在另一个实施例中，该方法包括执行学习阶段，包括以下步骤：接收表示一个或多个吸收制品中的每一个中的一个或多个事件的传感器信号; 接收指示每个吸收制品中的一个或多个事件的累积特性的观测数据; 并且识别描述传感器信号和观测数据之间的关系的最佳数学模型。 这种事件可以包括发生在诸如尿布的吸收制品中的尿失禁事件。 观察数据可以测量在尿布中发生的排尿事件的循环的累积体积。
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公开(公告)号：US20140244644A1
公开(公告)日：2014-08-28
申请号：US14130833
申请日：2012-07-05
IPC分类号： G06F17/30
CPC分类号： G06F17/30595 , A61F13/42 , G06Q50/22
摘要： A method for analysing incoming data, comprising the steps of processing the incoming data in segments to output a sequence of segment types by extracting one or more properties of an incoming data segment and forming an Unknown Property Vector for each segment of data in the incoming data, and processing the sequence of segment types to identify events in the incoming data. The sequence of segment types is determined, for each segment, by reference to a set of Reference Property Vectors that are relevant to the Unknown Property Vector. This may involve application of first and/or second and/or further functions to identify at least a first subset of Reference Property Vectors that are relevant to the Unknown Property Vector. Alternatively, a logistic regression algorithm, derived using clustering or classification methods for identifying candidate vectors, may be used.
摘要翻译： 一种用于分析输入数据的方法，包括以下步骤：通过提取输入数据段的一个或多个属性并为输入数据中的每个数据段形成未知属性向量来处理段中的输入数据以输出段类型序列 ，并处理段类型序列以识别传入数据中的事件。 通过参考与“未知属性向量”相关的一组参考属性向量，为每个段确定段类型的序列。 这可以涉及应用第一和/或第二和/或其他功能来识别与未知属性向量相关的至少第一参考属性向量子集。 或者，可以使用使用用于识别候选向量的聚类或分类方法导出的逻辑回归算法。
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