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. From 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.
Kalman-based approach to bladder volume estimation for people with neurogenic dysfunction of the urinary bladder
PALLA, ALESSANDRO;FANUCCI, LUCA;
2016-01-01
Abstract
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. From 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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.