Abstract
Targeted Temperature Management (TTM) is an emerging clinical technology designed to regulate the body temperature of post-cardiac arrest patients within the range of 32°C–34°C. This precise temperature control aims to reduce cerebral oxygen metabolism, thus stabilizing the medical condition of these patients. In the context of the COVID-19 pandemic, the importance of contactless healthcare and automated systems has grown significantly. This study leverages millimeter wave technology, a non-invasive approach, to gather comprehensive physiological data from patients, providing valuable insights into their overall health status. Beyond developing a predictive model for assessing TTM effectiveness, this research rigorously evaluates the data collection capabilities of millimeter wave technology, shedding light on its potential contributions to modern healthcare.
Recommended Citation
Lo, Chia-Lun and Yang, Tsung-Lung, "Development of an AI-based alert system for targeted temperature management patients using machine learning and millimeter-wave technology" (2023). ICEB 2023 Proceedings (Chiayi, Taiwan). 12.
https://aisel.aisnet.org/iceb2023/12