TY - GEN
T1 - SigmoidOxy
T2 - 30th International Conference on Mobile Computing and Networking, ACM MobiCom 2024
AU - Gherardi, Alexander Jordan
AU - Demirbas, Ahmet
AU - Xu, Wenyao
N1 - Publisher Copyright:
© 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.
PY - 2024/12/4
Y1 - 2024/12/4
N2 - Diabetic foot ulcers (DFUs) represent a significant global health challenge for the elderly with high mortality rates and complications. While imaging technologies like NIRS and hyperspectral imaging have improved wound assessment in clinical settings, their cost, and large size limit their use in the home and primary care. On the other hand, existing mobile solutions only capture secondary bio-markers like color and wound size. This paper introduces SigmoidOxy (or σ(Oxy)), a novel smartphone-based perfusion tool for DFU management. SigmoidOxy extracts oxygenation information from standard RGB images captured by smartphone cameras by applying hyperspectral reconstruction models to infer oxygenation. We evaluate SigmoidOxy's performance using the SPECTRALPACA dataset [2] finding an Average Persons R of 0.72 and Average Mean Absolute Error of 0.239 when comparing sigmoid oxygenation signals and analyze its sensitivity to ischemia in the DFUC2021 dataset [17].
AB - Diabetic foot ulcers (DFUs) represent a significant global health challenge for the elderly with high mortality rates and complications. While imaging technologies like NIRS and hyperspectral imaging have improved wound assessment in clinical settings, their cost, and large size limit their use in the home and primary care. On the other hand, existing mobile solutions only capture secondary bio-markers like color and wound size. This paper introduces SigmoidOxy (or σ(Oxy)), a novel smartphone-based perfusion tool for DFU management. SigmoidOxy extracts oxygenation information from standard RGB images captured by smartphone cameras by applying hyperspectral reconstruction models to infer oxygenation. We evaluate SigmoidOxy's performance using the SPECTRALPACA dataset [2] finding an Average Persons R of 0.72 and Average Mean Absolute Error of 0.239 when comparing sigmoid oxygenation signals and analyze its sensitivity to ischemia in the DFUC2021 dataset [17].
KW - diabetic foot ulcers
KW - mobile health
KW - spectral reconstruction
UR - https://www.scopus.com/pages/publications/105002729111
U2 - 10.1145/3636534.3698119
DO - 10.1145/3636534.3698119
M3 - Conference contribution
AN - SCOPUS:105002729111
T3 - ACM MobiCom 2024 - Proceedings of the 30th International Conference on Mobile Computing and Networking
SP - 2290
EP - 2296
BT - ACM MobiCom 2024 - Proceedings of the 30th International Conference on Mobile Computing and Networking
PB - Association for Computing Machinery, Inc
Y2 - 18 November 2024 through 22 November 2024
ER -