Innovation in Signal Detection for Ambulatory ECG Monitoring - Powered by Baxter-Innovation in Signal Detection for Ambulatory ECG Monitoring

Innovation in Signal Detection for Ambulatory ECG Monitoring - Powered by Baxter

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The panel discussed how ambulatory ECG monitoring, AI, and EHR integration could close major gaps in cardiac care. Speakers agreed that earlier and longer monitoring could identify hidden high-risk patients—such as those with unexplained palpitations, inherited arrhythmia risk, mitral valve prolapse, or post-TAVR conduction disease—before serious events occur. They also emphasized the challenge of data overload: monitors generate too many alerts, many of them low-value, and responsibility for follow-up is often unclear across EP, cardiology, structural heart, and primary care teams.<br /><br />AI was seen as useful in two ways: first, to automate data processing and reduce noise; second, to uncover new prognostic signals from continuous ECG data, especially when combined with clinical context from the EHR and other wearable data like sleep, activity, or oxygenation. Panelists also highlighted the importance of better patient-friendly devices, improved skin tolerance, and more flexible wearables.<br /><br />A recurring theme was that monitoring must become more actionable and contextual—tailored to age, history, imaging, and risk profile—so data can guide decisions rather than overwhelm clinicians.

Keywords

ambulatory ECG monitoring

artificial intelligence

EHR integration

cardiac arrhythmia risk

data overload

wearable ECG devices

clinical decision support