In this research, we propose a bladder volume monitoring system that can be effectively applied for various voiding dysfunctions. Whereas conventional systems lack consecutive measurements, the proposed system can continuously monitor a user's status even during unconscious sleep. For the convenience, we design a simple and comfortable waist-belt-type device by using the body impedance analysis (BIA) technique. To support various measurement scenarios, we develop applications by connecting the device to a smartphone. To minimize motion noises, which are inevitable when monitoring over an extended period, we propose a motion artifact reduction algorithm that exploits multiple frequency sources. The experimental results show a strong relationship between the impedance variation and the bladder volume; this confirms the feasibility of our system.

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The nocturnal enuresis is challenging due to the increased social activities of the children. This disorder significantly bothers both the children and their parents in psychological, behavioral, social, and financial manners. However, the primary treatments have limitations and further are not able to completely cure the disorder. In order to reduce pain and burdens of patients and their parents, it is important to accurately estimate when the enuretic incident occurs in advance. For the estimation, we have comprehensively investigated various studies of the nocturnal enuresis in the diverse fields. Through the investigations, we have summarized four hypotheses of the physiological signals related to the enuretic moment. In order to conquer the nocturnal enuresis, we design a preliminary framework sensing and investigating the physiological signals with the sensors. Our synthesized approach to understand and estimate the moments of the enuretic incidents can establish a foothold to complete the promising prediction system.

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