Multi-stable Compliant-Mechanism-based Mattress for Bedsore Prevention

Abstract Pressure ulcers or decubitus ulcers, more commonly known as bedsores are a huge problem affecting 2.5 million patients every year in the US and causes 60,000 deaths every year. Pressures exceeding 32 mm of Hg in the bony prominences in the back of the patient body lead to bedsores. Despite the existing low air loss mattresses, alternating pressure mattresses and the state-of-the-art air fluidized beds, bedsores prevail, and its prevention remains a huge healthcare challenge. Current hospital protocol is to turn patient every two hours. This is very disturbing and cause of pain to a resting patient who is dealing with other co-existing health conditions besides bedsores. Caregivers and nurses must turn heavy patients around, which sometimes lead to hurting their backs in the process. When not performed adequately and frequently (every 2 hours) as required, it is considered as negligence of care and causes litigation against nursing homes and hospitals causing huge financial losses to them. We propose a compliant-mechanism- based mattress that will obsolete the current clinical protocol of nurses and caregivers having to turn the patient every two hours. It will operate with minimal power, make small clicking noise when changing from one stable state to another using amount of force required to open a desk drawer. This switching of states can be further automated and can include a simple counter for documented evidence of alternating pressure to support against litigation of negligent care. In specific aim 1, machine learning using trained neural network will determine the functional requirements of the mattress (e.g., optimal amplitude and pitch for the undulation of the pressure points) by conducting a cohort pressure profile study that involves a bed that intentionally applies pressure on resting bodies. In specific aim 2, ideal topology with pitch and amplitude of undulations discovered in aim 1 will be developed using FACT and optimized using BLOT to create a prototype bi-stable compliant-mechanism-based mattress as a new approach for shifting pressure points on a patient’s body. FACT is advanced technique using freedom and constraint topologies for topology synthesis of the mattress and BLOT provides boundary layer optimization of the topology. Proposed mattress is innovative, disruptive, affordable, lightweight, does not use noisy air pumps, has no leakage issues and will eliminate the scourge of bedsores in the existing immobile and aging population.Project Narrative Numerous currently marketed alternating pressure mattresses have not received recommendations from reviewers due to poor correlation and unconvincing outcomes for bedsore prevention. Our approach of using neural network based machine learning will bring a new methodical approach to discerning the pitch and amplitude of undulations required to prevent dead pressure zones that exceed safe pressure of 32 mm of Hg on the patient’s back, which is fundamental to preventing bedsores. This will further serve as input to designing the prototype compliant-mechanism-based mattress using the freedom and constraint topologies (FACT) approach and the boundary learning optimization tool (BLOT) with end effect of developing an innovative mattress for preventing bedsores in the immobile and aging population.