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    • 1. 发明申请
    • DIAGNOSIS OF SLEEP APNEA
    • 诊断APNEA诊断
    • US20080051669A1
    • 2008-02-28
    • US11771026
    • 2007-06-29
    • Wolfgang MEYERManuel EbertJochen Proff
    • Wolfgang MEYERManuel EbertJochen Proff
    • A61B5/0205A61B5/04
    • A61B5/0456A61B5/02405A61B5/4818
    • The present invention relates to methods and apparatuses for detecting sleep apnea by analyzing characteristic physiological oscillations of the heart rate variability (HRV). Starting from recorded ECG data of the patient, for example, as a long-term sequence of the changing RR intervals, the heart rate variability is examined using autocorrelation calculations for the occurrence of rhythmic oscillations of various frequencies. If oscillations typical for apnea occur having very long period durations in the range of 20 to 80 seconds, these are detected as a maximum of the autocorrelation function. If a pathological sleep apnea accordingly exists, individual apnea events may be identified by prompt analysis of short recorded RR sequences, e.g., in the minute interval.
    • 本发明涉及通过分析心率变异性(HRV)的特征性生理振荡来检测睡眠呼吸暂停的方法和装置。 从患者的记录的ECG数据开始,例如,作为RR间期变化的长期序列,使用用于各种频率的节奏振荡的发生的自相关计算来检查心率变异性。 如果发生呼吸暂停典型的振荡发生在20至80秒范围内具有非常长的持续时间,则将其视为自相关函数的最大值。 如果相应地存在病理性睡眠呼吸暂停,可以通过快速分析短记录的RR序列来识别个体呼吸暂停事件,例如在分钟间隔内。
    • 2. 发明授权
    • Diagnosis of sleep apnea
    • 睡眠呼吸暂停诊断
    • US07909771B2
    • 2011-03-22
    • US11771026
    • 2007-06-29
    • Wolfgang MeyerManuel EbertJochen Proff
    • Wolfgang MeyerManuel EbertJochen Proff
    • A61B5/0402
    • A61B5/0456A61B5/02405A61B5/4818
    • Methods and apparatuses for detecting sleep apnea by analyzing characteristic physiological oscillations of the heart rate variability (HRV). Starting from recorded ECG data of the patient, for example, as a long-term sequence of the changing RR intervals, the heart rate variability is examined using autocorrelation calculations for the occurrence of rhythmic oscillations of various frequencies. If oscillations typical for apnea occur having very long period durations in the range of 20 to 80 seconds, these are detected as a maximum of the autocorrelation function. If a pathological sleep apnea accordingly exists, individual apnea events may be identified by prompt analysis of short recorded RR sequences, e.g., in the minute interval.
    • 通过分析心率变异性(HRV)的特征性生理振荡来检测睡眠呼吸暂停的方法和装置。 从患者的记录的ECG数据开始,例如,作为RR间期变化的长期序列,使用用于各种频率的节奏振荡的发生的自相关计算来检查心率变异性。 如果发生呼吸暂停典型的振荡发生在20至80秒范围内具有非常长的持续时间,则将其视为自相关函数的最大值。 如果相应地存在病理性睡眠呼吸暂停,可以通过快速分析短记录的RR序列来识别个体呼吸暂停事件,例如在分钟间隔内。