Poster + Paper
18 June 2024 The novel care-cure pressure ulcer mobile sensor and algorithm for super aging people
Tae-mi Jung, Jong-Ha Lee
Author Affiliations +
Conference Poster
Abstract
Pressure ulcers are a significant concern in intensive and long-term care settings, posing a substantial financial burden with costs reaching approximately $167,000 for a four-stage ulcer. These ulcers progress from stage 1 to stage 4, with stages 3 and 4 marking a transition to irreversible inflammation, underscoring the importance of early diagnosis and treatment. The incidence and prevalence of pressure ulcers vary internationally, with reports indicating an average of 22-44% in intensive care units across US hospitals. Given their substantial prevalence and the financial and human costs involved, early treatment and prevention are paramount healthcare objectives. In response, we introduce an algorithm for a pressure ulcer treatment device, leveraging biophotonics sensor technology for impedance measurement and light irradiation, as developed in prior research. This algorithm generates a wound map from impedance data, facilitating tailored light output adjustments for each impedance pin based on the map. Validation through 10-Fold Cross Validation yielded an accuracy rate of 91% for the algorithm. Furthermore, we posit that ongoing advancements in mobile healthcare and data analytics will significantly enhance the efficacy of pressure ulcer treatment devices, streamlining management processes.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Tae-mi Jung and Jong-Ha Lee "The novel care-cure pressure ulcer mobile sensor and algorithm for super aging people", Proc. SPIE 12998, Optics, Photonics, and Digital Technologies for Imaging Applications VIII, 129981C (18 June 2024); https://doi.org/10.1117/12.3016595
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Skin

Cross validation

Algorithm development

Evolutionary algorithms

Data modeling

Diagnostics

Machine learning

Back to Top