Devices for prevention of pressure ulcers

Abstract

A support surface, such as an underpad, for preventing pressure sores in a patient is a multi-layer textile assembly having a skin contact layer formed from a fabric of synthetic filament yarns woven to provide air permeability and moisture vapor permeability and having a thickness of less than 1 mm. An absorbent middle layer is formed from a breathable microfiber fabric woven to provide for moisture transition from an upper surface of the middle layer to a bottom surface of the middle layer. The skin contact layer and the middle layer are stitched together using a stitching pattern optimized to produce an open pattern with minimal puckering. A bottom layer is formed from a breathable, waterproof fabric woven from synthetic yarn to produce a moisture vapor transfer rate within the range of 5,000 to 20,000 grams per meter squared per 24 hours. The three layers are attached together around their outer edges.

1 .- 19 . (canceled) 
     
     
         20 . In a system for reducing the occurrence of pressure ulcers in an at-risk patient, a computer monitoring system for receiving electronic signals generated by an array of pressure sensors positioned underneath the patient, the computer monitoring system comprising:
 a computer processor programmed to execute an algorithm that identifies a patient-specific pattern using a weighted Braden score in combination with one or more weighted risk factor selected from the group consisting of medical diagnosis, clinical assessment, laboratory data, mattress type and the electronic signals generated by the array of pressure sensors; and   a display device for displaying the patient-specific pattern.   
     
     
         21 . The computer monitoring system of  claim 20 , wherein the patient-specific pattern is plotted as a curve of time versus interface pressure. 
     
     
         22 . The computer monitoring system of  claim 21 , further comprising an alarm when a pre-determined combination of risk factors according to the patient-specific pattern is present. 
     
     
         23 . The computer monitoring system of  claim 22 , wherein the pre-determined combination comprises a pre-selected point on the curve of time versus interface pressure. 
     
     
         24 . The computer monitoring system of  claim 20 , wherein a weight of the weighted Braden score is 50% or higher. 
     
     
         25 . The computer monitoring system of  claim 20 , wherein raw data from each of the one or more weighted risk factors is mined using a supervised learning algorithm to determine the patient-specific pattern. 
     
     
         26 . A computer-program product embodied on a non-transitory computer readable medium comprising instructions for executing an algorithm that identifies a patient-specific pattern for reducing the occurrence of pressure ulcers in an at-risk patient, the instructions further comprising:
 receiving an input comprising electronic signals generated by an array of pressure sensors positioned beneath the patient;   receiving data comprising a Braden score and one or more risk factors selected from the group consisting of medical diagnosis, clinical assessment, laboratory data, and mattress type,   identifying a patient-specific pattern by applying a first weight to the Braden score and one or more second weights to the one or more risk factors;   generating a curve of interface pressure versus time using the electronic signals and the first and second weights; and   using the curve to identify a point at which an alarm is activated to indicate that the patient requires attention.   
     
     
         27 . The computer-program product of  claim 26 , wherein first weight is 50% or higher. 
     
     
         28 . The computer-program product of  claim 26 , wherein raw data from the Braden score and each of the one or more risk factors is mined using a supervised learning algorithm to determine the patient-specific pattern. 
     
     
         29 . A non-transitory machine readable medium comprising instructions for executing an algorithm that identifies a patient-specific pattern for reducing the occurrence of pressure ulcers in an at-risk patient, which in response to being executed results in a computing system:
 receiving an input comprising electronic signals generated by an array of pressure sensors positioned beneath the patient;   receiving data comprising a Braden score and one or more risk factors selected from the group consisting of medical diagnosis, clinical assessment, laboratory data, and mattress type,   identifying a patient-specific pattern by applying a first weight to the Braden score and one or more second weights to the one or more risk factors;   generating a curve of interface pressure versus time using the electronic signals and the first and second weights; and   using the curve to identify a point at which an alarm is activated to indicate that the patient requires attention.   
     
     
         30 . The non-transitory machine-readable medium of  claim 29 , wherein first weight is 50% or higher. 
     
     
         31 . The non-transitory machine-readable medium of  claim 29 , wherein raw data from the Braden score and each of the one or more risk factors is mined using a supervised learning algorithm to determine the patient-specific pattern.