Model of Urine Accumulation in the Bladder and Method for Predicting Unconstrained Urine Volume Based on Absorption Spectrum of Urine

Abstract

As part of their excretion care protocol, many of the senior citizens living in nursing homes are required to wear a diaper for urinary incontinence. However, the diaper must be changed by the caregiver after each incontinence episode, and some of the elderly affected may be unable to inform the caregiver about an episode because of cognitive problems or owing to a sense a shame. Being able to predict the volume of urine in the bladder without having to attach any sensors to the body would make it possible for the caregiver to take the residents to the toilet before they have an incontinence episode. Moreover, the residents would not have to wear a diaper. With this goal in mind, in this study, we developed a macroscopic model for urine accumulation in the bladder as well as a method for predicting the urine volume in the bladder based on the absorption spectrum of urine obtained immediately after urination. The proposed method does not involve attaching a sensor on the skin. We performed a series of experiments to evaluate the proposed method and calculated its error rate based on the actual amount of urine and that predicted using the method. The error rate was then compared with that for an ultrasonic sensor attached to the skin above the bladder. The mean of the error rate of the proposed method was 15.46% whereas that of the ultrasonic sensor was 23.42 %, with the two being significantly different at the 5% level.

Keywords

• Absorption spectrum
• excretion care
• Gaussian process regression
• hyperspectral imaging
• urine volume accumulation