Authors:
Zeynep Gundogan
1
and
Beren Semiz
2
Affiliations:
1
Department of Electrical Engineering, Istanbul Technical University, Istanbul, Turkey
;
2
Department of Electrical and Electronics Engineering, Koc University, Istanbul, Turkey
Keyword(s):
Seismocardiogram, Hemorrhage, Vascular Pressure, Biomedical Signal Processing.
Abstract:
When a mass incident occurs, determining the severity of injuries and arranging the hospital triage are of great importance to increase the survival rates. This study aims to develop a seismocardiogram (SCG)-based triage assessment system by (i) distinguishing between different levels of exsanguination, and (ii) estimating the vascular pressure values recorded from various body locations for prioritizing the triage processes and monitoring vital parameters. In this project, publicly available Wearable and Catheter-based Cardiovascular Signals During Progressive Exsanguination in a Porcine Model of Hemorrhage dataset, which includes cardiovascular signals acquired through a catheter-based system and wearable sensors during progressive exsanguination, was used. First, temporal and spectral features were extracted from the SCG signals taken at different blood-loss levels from six Yorkshire swines. Hemorrhage severity assessment was then performed through multi-class classification lever
aging one vs. all approach. As the second step, four different regression models were trained for each of the right atria, aortic root, femoral artery and pulmonary capillary locations to estimate the corresponding vascular pressure values. For hemorrhage severity assessment, the accuracy, sensitivity, precision and f1-score values were all calculated to be 0.96 for the best performing model (XGBoost). For the vascular pressure estimation, (mean-absolute-error and R 2 ) pairs were calculated to be (1.54, 0.94), (2.76, 0.58), (1.29, 0.87) and (0.95, 0.90) for aortic root, femoral artery, right atrium and pulmonary capillary models, respectively. Overall, this study introduced new use areas for the SCG signal, which can potentially be utilized in the development of continuous and non-invasive monitoring systems to prioritize the triage processes and track vital parameters.
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