Inflatable Bed Barrier for Fall Prevention
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Solution Overview
Problem
Patients in senior living and assisted care facilities often fall out of bed due to unassisted exit, which existing technologies fail to prevent effectively, especially in situations where immediate on-site assistance is not readily available.
Innovation Solution
A remotely deployable, inflatable device that inflates under the mattress to create a barrier, triggered by remote monitoring via camera feeds and AI-assisted detection of undesired movement, using air pumps controlled via internet connection, and deflated once assistance is provided.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If remote monitoring and AI detection are used to detect undesired movement, then fall prevention effectiveness is improved, but device complexity and operational infrastructure requirements increase
Solution Approach 1:
The patent introduces an intermediary AI monitoring system that acts as a mediator between the patient and the inflatable barrier device. The AI analyzes camera feeds and sensor data to detect undesired movement patterns, then triggers the inflatable deployment automatically or alerts staff, reducing the complexity of direct human monitoring while maintaining high reliability in fall prevention.
Solution Approach 2:
The patent replaces the mechanical system of continuous human monitoring with an automated AI-based detection system using computer vision and sensor analysis. This substitution reduces the operational burden on staff while improving the consistency and reliability of fall detection, allowing the system to operate 24/7 without fatigue.
2Loss of time
If inflatable cylinders are deployed remotely via internet connection, then response time to prevent falls is improved, but dependency on network infrastructure increases
Solution Approach 1:
The patent implements preliminary action by pre-positioning the inflatable cylinders between the mattress and foundation before any fall event occurs. The system is pre-configured with deployment mechanisms that can be activated remotely or automatically, ensuring immediate response capability without requiring physical intervention or complex network infrastructure during the critical moment of deployment.
Solution Approach 2:
The patent enables self-service functionality where the inflatable barrier system can deploy automatically based on AI-detected movement patterns without requiring external network commands. The system includes local control logic and power sources that allow it to function autonomously, reducing dependency on continuous network connectivity while maintaining fast response times.
3Reliability
If the inflatable device creates a mechanical barrier under the mattress, then fall prevention effectiveness is improved, but patient comfort and ease of movement may deteriorate
Solution Approach 1:
The patent applies dynamics by making the inflatable barrier adjustable and temporarily deployable rather than static and permanent. The system can inflate to create a protective barrier when fall risk is detected, then deflate to restore normal mattress conditions, dynamically adapting to the patient's needs and maintaining comfort while preventing falls during critical periods.
Solution Approach 2:
The patent implements periodic action through temporary deployment cycles of the inflatable barrier. The system monitors patient movement continuously and deploys the barrier only during periods of detected undesired movement or high fall risk, then deflates when the risk subsides. This periodic deployment maintains patient comfort during normal rest while providing protection when needed.
Data Source
AI summary
A remotely deployed, inflatable device designed to reduce or eliminate falls in senior living and assisted care facilities. Upon detecting undesired movement, nurses may deploy one or more inflatable cylinders, thereby inflating the device under one or both sides of the mattress, creating a barrier that prevents the resident from exiting the bed until on-site assistance arrives. It is envisioned that initially the operation of the device will rely on the remote monitoring of residents by one or more operators via live camera feeds. In more advanced versions it is envisioned that software and artificial intelligence will be able to use one or more camera feeds and will be able to supplement or even replace the need for a person to monitor any camera feeds.