Non-invasive Hemodynamic Monitoring During Blood Donation for Developing Models of Early Blood Loss

Completed

Conditions studied: Hemorrhage

In brief

This study is part of a Phase II STTR project to develop an algorithm called CipherSensor to apply feature extraction and machine learning techniques to non-invasive hemodynamic data to identify early signs of acute blood loss. The availability of this information may help to establish required interventions for treating trauma patients and battlefield casualties. Study hypothesis: Hemodynamic changes measured non-invasively during the blood donation process can be modeled to provide early estimations of blood loss.

Key facts

Study ID
NCT01448694
Run by
University of Colorado, Denver
People needed
320
Starts
2011-11-01
Expected to finish
2014-09-01
Last updated by the study team
2014-12-03

Who can join

Age: 18 and older, up to 89. Sex: any. Healthy volunteers: accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

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