A Novel IoT System For Patient-Centric Pressure Ulcer Prevention Using Sensor Embedded Dressings

Sachin Rangarajan, Young Lee, Vinith Johnson, Kaelan Schorger, Hanmin Lee, Dung Nguyen, Mohammad H. Behfar, Elina Jansson, Jari Rekilä, Jussi Hiltunen, Eric Vin, Katia Obraczka

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

Abstract

Pressure ulcers/injuries (PU/Is) are localized damage to the skin and/or underlying tissue caused by prolonged pressure to an area of the body. PU/Is affect over 2.5 million individuals in the United States annually, are associated with increased morbidity and mortality, and incur a cost of approximately $11 billion to the US healthcare system. Mitigating PU/Is continues to be a challenging task using traditional methods due to their time-and labor-intensive nature, and existing technological solutions tend to be prohibitively expensive, inefficiently implemented, or ineffective. Thus, there is a clear unmet need for a holistic, end-to-end, hospital-integrated, patient-centric system for PU/I prevention. Such a system can monitor pressure at high-risk areas and uses real-time sensor data, analysis, and visualization to guide clinicians and caregivers to perform effective preventative measures. In this paper, we describe a proof of concept of this system, which integrates: (A) a prototype "smart wound dressing"capable of detecting of changes in interface pressure and patient angle over time, including during routine patient repositioning maneuvers; and (B) an open software infrastructure that collects pressure-over-time data, stores, analyzes, and displays them to clinicians and caregivers. We present preliminary results obtained using our current prototype which uses machine learning algorithms to infer a patient's current position based on data from the pressure sensor.

Original languageEnglish
Title of host publication2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2022
PublisherIEEE Institute of Electrical and Electronic Engineers
Pages42-45
Number of pages4
ISBN (Electronic)978-1-6654-1647-4
ISBN (Print)978-1-6654-1648-1
DOIs
Publication statusPublished - 2022
MoE publication typeA4 Article in a conference publication
Event2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2022 - Pisa, Italy
Duration: 21 Mar 202225 Mar 2022

Conference

Conference2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2022
Country/TerritoryItaly
CityPisa
Period21/03/2225/03/22

Keywords

  • correlation and regression analysis
  • medical information systems
  • Wearable computers

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