Arrhythmia detection with feature delineation and machine learning

US11696718B2 · kind B2 · utility

Assignee

• Medtronic, Inc. · US

Inventors

• Niranjan Chakravarthy · Eden Prairie, US
• Siddharth Dani · Minneapolis, US
• Tarek D. Haddad · Minneapolis, US
• Donald R. Musgrove · Minneapolis, US
• Andrew Radtke · Minneapolis, US
• Eduardo N. Warman · Maple Grove, US
• Rodolphe Katra · Blaine, US
• Lindsay A. Pedalty · Minneapolis, US

Key dates

• Filing date: Jul 12, 2021
• Grant date: Jul 11, 2023
• Expiry date: Jul 12, 2041

Classification

• Technology area (CPC A): Human Necessities
• CPC primary: A61B2560/0214
• WIPO field: Medical technology
• WIPO sector: Instruments

Abstract

Techniques are disclosed for using both feature delineation and machine learning to detect cardiac arrhythmia. A computing device receives cardiac electrogram data of a patient sensed by a medical device. The computing device obtains, via feature-based delineation of the cardiac electrogram data, a first classification of arrhythmia in the patient. The computing device applies a machine learning model to the received cardiac electrogram data to obtain a second classification of arrhythmia in the patient. As one example, the computing device uses the first and second classifications to determine whether an episode of arrhythmia has occurred in the patient. As another example, the computing device uses the second classification to verify the first classification of arrhythmia in the patient. The computing device outputs a report indicating that the episode of arrhythmia has occurred and one or more cardiac features that coincide with the episode of arrhythmia.