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公开(公告)号：US20140088373A1
公开(公告)日：2014-03-27
申请号：US14031553
申请日：2013-09-19
发明人： Paul Phillips , Conor Heneghan , Trevor Murray
CPC分类号： A61B5/4812 , A61B5/05 , A61B5/0507 , A61B5/0816 , A61B5/1118 , A61B5/113 , A61B5/726 , A61B5/7264 , A61B5/7278 , A61B2562/0228 , A61M16/0069 , A61M2205/3303 , A61M2230/63
摘要： Methods and apparatus monitor health by detection of sleep stage. For example, a sleep stage monitor may access sensor data signals related to bodily movement and respiration movements. At least a portion of the detected signals may be analyzed to calculate respiration variability. The respiration variability may include variability of respiration rate or variability of respiration amplitude. A processor may then determine a sleep stage based on a combination bodily movement and respiration variability. The determination of sleep stages may distinguish between deep sleep and other stages of sleep, or may differentiate between deep sleep, light sleep and REM sleep. The bodily movement and respiration movement signals may be derived from one or more sensors, such as non-invasive sensor (e.g., a non-contact radio-frequency motion sensor or a pressure sensitive mattress).
摘要翻译： 方法和设备通过睡眠阶段的检测来监测健康。 例如，睡眠阶段监视器可以访问与身体运动和呼吸运动相关的传感器数据信号。 可以分析至少一部分检测到的信号以计算呼吸变异性。 呼吸变异性可能包括呼吸频率的变化或呼吸振幅的变化。 处理器然后可以基于组合运动和呼吸变异性来确定睡眠阶段。 睡眠阶段的确定可以区分深睡眠和其他睡眠阶段，或者可以区分深度睡眠，轻睡眠和REM睡眠。 身体运动和呼吸运动信号可以从一个或多个传感器（例如非侵入式传感器（例如，非接触式射频运动传感器或压敏床垫））导出。
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公开(公告)号：US20200337634A1
公开(公告)日：2020-10-29
申请号：US16846959
申请日：2020-04-13
发明人： Gareth McDarby , Erner O'Hare , Paul Phillips , Conor Heneghan , Trevor Murray
摘要： Methods and apparatus monitor health by detection of sleep stage. For example, a sleep stage monitor (100) may access sensor data signals related to bodily movement and/or respiration movements. At least a portion of the detected signals may be analyzed to calculate respiration variability. The respiration variability may include one or more of variability of respiration rate and variability of respiration amplitude. A processor may then determine a sleep stage based on one or more of respiration variability and bodily movement, such as with a combination of both. The determination of sleep stages may distinguish between deep sleep and other stages of sleep, or may differentiate between deep sleep, light sleep and REM sleep. The bodily movement and respiration movement signals may be derived from one or more sensors, such as non-invasive sensor (e.g., a non-contact radio-frequency motion sensor or a pressure sensitive mattress).
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公开(公告)号：US10660563B2
公开(公告)日：2020-05-26
申请号：US14429589
申请日：2013-09-19
发明人： Gareth McDarby , Emer O'Hare , Paul Phillips , Conor Heneghan , Trevor Murray
摘要： Methods and apparatus monitor health by detection of sleep stage. For example, a sleep stage monitor (100) may access sensor data signals related to bodily movement and/or respiration movements. At least a portion of the detected signals may be analyzed to calculate respiration variability. The respiration variability may include one or more of variability of respiration rate and variability of respiration amplitude. A processor may then determine a sleep stage based on one or more of respiration variability and bodily movement, such as with a combination of both. The determination of sleep stages may distinguish between deep sleep and other stages of sleep, or may differentiate between deep sleep, light sleep and REM sleep. The bodily movement and respiration movement signals may be derived from one or more sensors, such as non-invasive sensor (e.g., a non-contact radio-frequency motion sensor or a pressure sensitive mattress).
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公开(公告)号：US20150230750A1
公开(公告)日：2015-08-20
申请号：US14429589
申请日：2013-09-19
发明人： Gareth McDarby , Emer O'Hare , Paul Phillips , Conor Heneghan , Trevor Murray
摘要： Methods and apparatus monitor health by detection of sleep stage. For example, a sleep stage monitor (100) may access sensor data signals related to bodily movement and/or respiration movements. At least a portion of the detected signals may be analyzed to calculate respiration variability. The respiration variability may include one or more of variability of respiration rate and variability of respiration amplitude. A processor may then determine a sleep stage based on one or more of respiration variability and bodily movement, such as with a combination of both. The determination of sleep stages may distinguish between deep sleep and other stages of sleep, or may differentiate between deep sleep, light sleep and REM sleep. The bodily movement and respiration movement signals may be derived from one or more sensors, such as non-invasive sensor (e.g., a non-contact radio-frequency motion sensor or a pressure sensitive mattress).
摘要翻译： 方法和设备通过睡眠阶段的检测来监测健康。 例如，睡眠阶段监视器（100）可以访问与身体运动和/或呼吸运动相关的传感器数据信号。 可以分析至少一部分检测到的信号以计算呼吸变异性。 呼吸变异性可以包括呼吸频率的变化性和呼吸振幅的变化性中的一种或多种。 然后，处理器可以基于呼吸变异性和身体运动中的一种或多种来确定睡眠阶段，例如两者的组合。 睡眠阶段的确定可以区分深睡眠和其他睡眠阶段，或者可以区分深度睡眠，轻睡眠和REM睡眠。 身体运动和呼吸运动信号可以从一个或多个传感器（例如非侵入式传感器（例如，非接触式射频运动传感器或压敏床垫））导出。
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公开(公告)号：US11801009B2
公开(公告)日：2023-10-31
申请号：US16846959
申请日：2020-04-13
发明人： Gareth McDarby , Emer O'Hare , Paul Phillips , Conor Heneghan , Trevor Murray
CPC分类号： A61B5/4812 , A61B5/05 , A61B5/0507 , A61B5/0816 , A61B5/113 , A61B5/726 , A61B5/7264 , A61B5/7278 , A61M16/0069 , A61B5/1118 , A61B2562/0228 , A61M2205/3303 , A61M2230/63
摘要： Methods and apparatus monitor health by detection of sleep stage. For example, a sleep stage monitor (100) may access sensor data signals related to bodily movement and/or respiration movements. At least a portion of the detected signals may be analyzed to calculate respiration variability. The respiration variability may include one or more of variability of respiration rate and variability of respiration amplitude. A processor may then determine a sleep stage based on one or more of respiration variability and bodily movement, such as with a combination of both. The determination of sleep stages may distinguish between deep sleep and other stages of sleep, or may differentiate between deep sleep, light sleep and REM sleep. The bodily movement and respiration movement signals may be derived from one or more sensors, such as non-invasive sensor (e.g., a non-contact radio-frequency motion sensor or a pressure sensitive mattress).
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