Massachusetts Institute of Technology;Children's Medical Center Corporation
发明人:
George Cheeran Verghese,Margaret Gan Guo,Rebecca Mieloszyk,Thomas Heldt,Baruch Shlomo Krauss
申请号：
US16452631
公开号：
US20190378595A1
申请日:
2019.06.26
申请国别(地区):
US
年份:
2019
代理人:
摘要：
Systems and methods are disclosed herein for quantitatively identifying a patient's sedation level and predicting adverse events, based on one or more capnograms or outputs from a pharmacokinetic, pharmacodynamic, or ventilatory model. A sensor measures a carbon dioxide concentration of air exhaled by a patient into a breath receiver. A processor processes the sensor data to generate a capnogram including one or more respiratory cycles, computes the outputs of pharmacokinetic, pharmacodynamic, or ventilatory models, and extracts one or more of the resulting features from the capnogram and pharmacokinetic, pharmacodynamic, or ventilatory model outputs. A multi-parameter metric is computed based on the one or more extracted features and estimates the current or predicted sedation level of the patient.
