ECG Artifact Detector with Actionable Feedback
Artifact (an electrocardiographic wave that arises from sources other than the heart or brain) is a significant confounder in the acquisition and interpretation of multi-lead electrocardiograms (ECGs) for patient triage and diagnosis. While modern ECG acquisition systems have sophisticated software and hardware to minimize artifact, it is often insufficient. The ECG artifact rarely originates from the patient monitor itself but instead originates at the electrode-skin interface (poor contact), in the skeletal muscles (muscle artifact), or from radiated electromagnetic interference (EMI). Such ECG artifact is exacerbated in prehospital emergency care settings. Nevertheless, user action can often mitigate the presence of artifact through corrective action. The student team worked to develop an ECG artifact detection and classification algorithm that provides actionable feedback to the user to minimize the impact of such artifact.