Wearable Urination Prediction With Early Enuresis Alerts
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Solution Overview
Problem
Current enuresis treatments, such as drug therapy and enuresis alarms, are ineffective and uncomfortable, often triggering only after substantial urination has occurred, and existing sensors are cumbersome and unreliable, failing to provide timely alerts for involuntary urination.
Innovation Solution
A system using biometric and environmental data from wearable devices and patch sensors to predict urination events, providing early alerts through a network of connected devices, including a hub and network-controllable appliances, to facilitate timely responses and behavioral conditioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If moisture sensors are incorporated into beds to detect urination, then detection capability is provided, but the alarm only triggers after substantial urination has occurred, resulting in delayed response time
Solution Approach 1:
The system performs preliminary detection of moisture presence before substantial urination occurs. The moisture sensor continuously monitors for initial moisture contact, and the system activates an alarm and provides haptic feedback immediately upon detection, rather than waiting for accumulated moisture levels. This preliminary action enables early warning before the bed becomes substantially wet.
2Measurement precision
If large sensors are attached to undergarments with wired connections, then urination detection is achieved, but the wired connections hinder sleep and create tangling hazards
Solution Approach 1:
The patent replaces the mechanical wired connection system with a wireless communication system. The moisture sensor and control circuitry communicate with the external alarm device via wireless signals (such as radio frequency), eliminating the need for physical cables that could tangle or restrict movement. This substitution maintains detection functionality while significantly improving sleep comfort and safety.
3Measurement precision
If wireless sensors with large batteries are used, then urination detection is provided, but the large batteries and circuitry make the device cumbersome and uncomfortable
Solution Approach 1:
The patent extracts the heavy battery and complex circuitry from the wearable sensor component and relocates them to a separate base station or external device. The wearable sensor becomes a lightweight moisture detection element that communicates wirelessly, while the power supply and processing electronics remain in the external unit. This separation dramatically reduces the weight and bulk of the wearable component.
Solution Approach 2:
The external base station serves multiple functions: it houses the battery, provides wireless communication, processes sensor data, and generates alarm signals. By consolidating these functions in a single external device, the wearable component can be minimized to essential sensing elements only, reducing its weight and complexity.
4Measurement precision
If existing enuresis alarm systems are used, then alerts are provided, but they are difficult to use and prone to breakage
Solution Approach 1:
The wearable sensor component utilizes flexible, thin-film construction for the moisture sensing element. This flexible design eliminates rigid parts that could break, while the thin-film structure conforms to the body or bedding without creating pressure points or discomfort. The flexible nature also allows easy attachment and removal without damage.
Data Source
AI summary
A system for predicting and detecting urination events of users is disclosed. The system can include any number of wearable devices, mobile devices, hubs, computing devices, and servers to collect, share, process, and interpret data, as well as to provide stimuli to users and caregivers. Biometric and/or environmental data associated with a user can be collected and applied to a urination model to determine a predicted urination time. The user or a caregiver can be provided with direct or environmental stimuli conveying information about predicted urination times. Ongoing biometric and/or environmental data collection can be used to identify, and provide stimuli warning of, imminent urination events. Voluntary and involuntary feedback of actual urination events, as well as continued biometric and/or environmental data collection, can be used to train individual and collective urination models.