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Kalman-Based Approach to Bladder Volume Estimation for People with Neurogenic Dysfunction of the Urinary Bladder

机译:基于卡尔曼的膀胱体积估计方法对膀胱神经源性功能障碍的膀胱体积估计

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People with neurogenic dysfunction of urinary bladder often require daily catheterism because of their impairment. This issue is particularly critical for those that have not the urinary stimulus, because they have not the ability to understand when the bladder is full or not. Prom user's point of view, the absence of a urinary conscious stimulus can cause refluxes, damaging patient's health and his psychological status. For such necessities, most patients require professional nursing, increasing the work of the staff and the overall medical costs. Furthermore, catheterism itself applied every day for a long period can cause infection in the urinary tract. The authors propose a non-invasive bladder monitoring system based on real-time bioimpedance measurement. A Klaman filter was developed in order to estimate the bladder volume due to the intrinsic-uncertainly of the model itself and to remove the artifacts due to patient's movements by using accelerometer by monitoring it's activity. Theoretical analysis, in-system measurements and experimentations prove the effectiveness of the proposed solution.
机译:由于损伤,患有膀胱神经源性功能障碍的人通常需要每日导管。对于那些没有泌尿刺激的人来说,这个问题尤为重要,因为他们没有能够了解膀胱完整的能力。舞会用户的观点,缺乏泌尿意识刺激会导致回流,破坏患者的健康状况和心理状态。对于这种必需品,大多数患者需要职业护理,提高人员的工作和整体医疗费用。此外,导管本身每天施用长期会导致泌尿道感染。作者提出了一种基于实时生物阻抗测量的非侵入性膀胱监测系统。开发了一种克拉兰过滤器,以便由于模型本身的内在 - 不确定而估计膀胱量,并且通过使用加速度计通过监测它的活动来消除由于患者的运动而删除伪影。理论分析,体系测量和实验证明了所提出的解决方案的有效性。

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