METHODS AND SYSTEMS FOR MONITORING AND PREVENTING PRESSURE ULCERS

• US 20130090571A1
• Filed: 10/06/2011
• Published: 04/11/2013
• Est. Priority Date: 10/06/2011
• Status: Abandoned Application

• Current Assignee: Board of Regents of the University of Texas System (University of Texas System)
• Original Assignee: Board of Regents of the University of Texas System (University of Texas System)
• Inventors: Nourani, Mehrdad, Tamil, Lakshman S., Pompeo, Matthew Q., Ostadabbas, Sarah, Yousefi, Rasoul
• Application Number:
  US13/267,513
• Publication Number:
  US 20130090571A1
• Time in Patent Office: Days
• US Class Current: 600/587
• CPC Class Codes: A61B 5/103 Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes A61B5/08 takes precedence; measuring aids for tailors A41H1/00; measuring instruments specially adapted for dentistry A61C19/04
• CPC Class Codes: A61B 5/447 specially adapted for aiding the prevention of ulcer or pressure sore development, i.e. before the ulcer or sore has developed
• CPC Class Codes: A61B 5/6891 Furniture
• CPC Class Codes: A61B 5/6894 Wheel chairs
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

The present invention relates generally to the prevention and treatment of pressure ulcers and a platform for monitoring, prevention and management of pressure ulcer using a pressure mapping system that records a patient'"'"'s bed posture, tracks different limbs along with associated statistical pressure image data and produces a summary report for care givers after data analysis and risk assessment. The methodology allows care givers to utilize the stress data and schedule the repositioning of the patient more effectively. The invention relates to creation and using algorithms and analytics for monitoring, prevention and management of pressure ulcers which include time-stamped whole-body pressure distribution data collection and profiling; posture classification, limb detection and tracking; quality of turn and risk assessment; turning schedule and nursing staff utilization for pressure ulcer management; and patient status reporting system customized for caregivers.

Claims

1. A method of monitoring pressure applied to a pressure sensitive area of a human body, the method comprising:

contacting a plurality of pressure sensors with pressure sensitive areas of the human body;

determining body posture;

tracking and determining the position of limbs of the human body;

collecting data from the pressure sensors mounted on a bed'"'"'s surface such as a pressure sensor mat;

extracting features from the collected data;

training a model by using the extracted features; and

determining the level of risk associated with the development of a pressure ulcer.

2. The method according to claim 1, wherein the pressure sensors are mounted on a bed'"'"'s surface.

3. The method according to claim 1, wherein the pressure sensors are mounted on a mat that is placed on a bed'"'"'s surface.

4. The method according to claim 1, wherein the pressure sensors are mounted on the human body.

5. The method according to claim 4, wherein the pressure sensors are in the form of pressure sensor patches.

6. The method of claim 2, wherein the plurality of pressure sensors are distributed over the bed'"'"'s surface.

7. The method of claim 1, wherein the pressure sensors provide a pressure distribution image.

8. The method of claim 1, wherein the collected data provides body posture detection, limb detection and tracking, posture independent sensor data and posture dependent sensor data.

9. A method for the monitoring, prevention and management of pressure ulcers of a patient, the method comprising the steps of:

collecting and profiling time-stamped whole body pressure distribution data;

classifying the patient'"'"'s posture;

detecting and tracking the patient'"'"'s limbs;

assessing the risk and quality of turn of the patient;

analyzing the turning schedule and utilization of caregivers; and

customizing a reporting system of the patient'"'"'s status.

10. A method for the monitoring, prevention and management of pressure ulcers of a patient, the method comprising the step of:

collecting and profiling time-stamped whole body pressure distribution data, wherein the profiling step is based on tissue stress recovery as a function of pressure and time.

11. The method of claim 10 further comprising the step of:

classifying the patient'"'"'s posture using pressure input data, wherein the classifying step extracts a silhouette of the patient using binary image processing.

12. The method of claim 11 further comprising the step of:

detecting and tracking the patient'"'"'s limbs through a sequence of data processing including the steps of importing pressure image associated with the patient'"'"'s current posture, extracting a skeleton tree from the image using triangulation technique, pruning the skeleton tree and segmenting the patient'"'"'s limbs using the skeleton tree and associated posture.

13. The method of claim 12 further comprising the step of:

assessing the risk and quality of turn of the patient using a stress recovery model.

14. The method of claim 13 further comprising the step of:

analyzing the turning schedule of the patient by calculating a finite duration repositioning schedule based on a stress recovery model.

15. The method of claim 14 further comprising the step of:

developing an efficient and user-friendly summary of data derived from a plurality of pressure sensors, caregiver'"'"'s data, processed data and risk assessment data.

16. A method for monitoring, prevention and management of pressure ulcers of a patient, the method comprising:

acquiring at least one real-time physiological data stream;

identifying a physiological data related to pressure present in the at least one real-time physiological data stream;

selecting a first algorithm directed to produce a first diagnostic interpretation of the physiological data;

selecting a second algorithm directed to produce a second diagnostic interpretation of the physiological data, wherein the first algorithm and the second algorithm produce diagnostic interpretations of the same identified physiological data;

applying the first algorithm to the at least one real-time physiological data stream as the at least one real-time physiological data stream is acquired to produce at least one first diagnostic interpretation;

applying the second algorithm to the at least one real-time physiological data stream as the at least one real-time physiological data stream is acquired to produce at least one second diagnostic interpretation; and

displaying the first and second diagnostic interpretations.

17. The method according to claim 16 further comprising the step of selecting a third algorithm directed to produce a third diagnostic interpretation of the physiological data;

applying the third algorithm to the at least one real-time physiological data stream as the at least one real-time physiological data stream is acquired to produce a third diagnostic interpretation; and

displaying the first, second and third diagnostic interpretations.

18. The method according to claim 17 further comprising the step of selecting a fourth algorithm directed to produce a fourth diagnostic interpretation of the physiological data;

applying the fourth algorithm to the at least one real-time physiological data stream as the at least one real-time physiological data stream is acquired to produce a fourth diagnostic interpretation; and

displaying the first, second, third and fourth diagnostic interpretations.

19. The method according to claim 18 further comprising the step of selecting a fifth algorithm directed to produce a fifth diagnostic interpretation of the physiological data;

applying the fifth algorithm to the at least one real-time physiological data stream as the at least one real-time physiological data stream is acquired to produce a fifth diagnostic interpretation; and

displaying the first, second, third, fourth and fifth diagnostic interpretations.

20. The method according to claim 19 further comprising the step of selecting a sixth algorithm directed to produce a sixth diagnostic interpretation of the physiological data;

applying the sixth algorithm to the at least one real-time physiological data stream as the at least one real-time physiological data stream is acquired to produce a sixth diagnostic interpretation; and

displaying the first, second, third, fourth, fifth and sixth diagnostic interpretations.