Enabling the assessment of trauma-induced hemorrhage via smart wearable systems
Jonathan Zia, Jacob Kimball, Christopher Rolfes, Jin‐Oh Hahn, Omer T. Inan
Abstract
= 6). Ultimately, high-level features of cardiomechanical function were shown to strongly predict progression toward cardiovascular collapse and used to estimate BVS with a median error of 15.17 and 18.17% for the catheter-based and wearable systems, respectively. Exploring the nexus of biomedical theory and practice, these findings lay the groundwork for digital biomarkers of hemorrhage severity and warrant further study in human subjects.
Topics & Concepts
Wearable computerComputer scienceWearable technologyMedicineFunction (biology)Human–computer interactionEmbedded systemBiologyEvolutionary biologyNon-Invasive Vital Sign MonitoringCardiac Arrest and ResuscitationHemodynamic Monitoring and Therapy