ABNORMALITY NOTIFICATION DEVICE AND PROGRAM

To provide an abnormality notification device and the like, enabling the abnormality notification accuracy thereof to be improved by presuming a future condition of an object person being a patient depending on a personal characteristic and daily rhythm of the object person.SOLUTION: The abnormality...

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Bibliographic Details
Main Author KOGURE TAKAMASA
Format Patent
LanguageEnglish
Japanese
Published 24.06.2019
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Summary:To provide an abnormality notification device and the like, enabling the abnormality notification accuracy thereof to be improved by presuming a future condition of an object person being a patient depending on a personal characteristic and daily rhythm of the object person.SOLUTION: The abnormality notification device comprises: biological signal acquisition means acquiring a biological signal of an object person on a bed; biological information value calculation means calculating a biological information value using the acquired biological signal; presumption means presuming a condition of the object person after the lapse of a presumption time on the basis of the biological information value; notification means performing notification when it is determined by the presumption means that the condition of the object person is abnormal; and condition determination means determining the current condition of the present object person on the basis of the biological information value. On the basis of a result learned from the current condition of the present object person determined by the condition determination means, the presumption means presumes the condition of the object person.SELECTED DRAWING: Figure 1 【課題】患者である対象者の個人的特性や日内リズムに応じて、未来の状態を推測して異常を報知する精度を向上させることが可能な異常報知装置等を提供すること。【解決手段】対象者の寝床における生体信号を取得する生体信号取得手段と、前記取得された生体信号から生体情報値を算出する生体情報値算出手段と、前記生体情報値に基づいて、推測時間経過後の前記対象者の状態を推測する推測手段と、前記推測手段により前記対象者の状態が異常と判定された場合に報知を行う報知手段と、前記生体情報値に基づいて、現在の対象者の状態を判定する状態判定手段と、を備え、前記推測手段は、前記状態判定手段により判定された現在の対象者の状態から学習された結果に基づいて、前記対象者の状態を推測することを特徴とする。【選択図】図1
Bibliography:Application Number: JP20170231223