Skip to content

Latest commit

 

History

History
11 lines (6 loc) · 998 Bytes

File metadata and controls

11 lines (6 loc) · 998 Bytes

Consciousness Classification Using Physiological Signals

image

Motivation: A patient’s level of consciousness is crucial for determining their care and prognosis. However, no methods continuously monitor consciousness and alert clinicians to changes.

To overcome this challenge and help clinicians better monitor patient health in critically ill patients, we develop a framework for classifying a patient’s state of consciousness using only physiological signals routinely collected in the ICU from patients with subarachnoid and intracerebral hemorrhages.

Gomez, L.A., Shen, Q., Doyle, K. et al. Classification of Level of Consciousness in a Neurological ICU Using Physiological Data. Neurocrit Care (2022). https://doi.org/10.1007/s12028-022-01586-0

Paper Link: https://link.springer.com/article/10.1007/S12028-022-01586-0