Invention Grant
- Patent Title: Reduced power machine learning system for arrhythmia detection
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Application No.: US17377763Application Date: 2021-07-16
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Publication No.: US11443852B2Publication Date: 2022-09-13
- Inventor: Niranjan Chakravarthy , Siddharth Dani , Tarek D. Haddad , Donald R. Musgrove , Andrew Radtke , Rodolphe Katra , Lindsay A. Pedalty
- Applicant: Medtronic, Inc.
- Applicant Address: US MN Minneapolis
- Assignee: Medtronic, Inc.
- Current Assignee: Medtronic, Inc.
- Current Assignee Address: US MN Minneapolis
- Agency: Shumaker & Sieffert, P.A.
- Main IPC: G16H50/20
- IPC: G16H50/20 ; A61B5/00 ; A61B5/11 ; G16H50/30 ; G06N20/00 ; G06N5/04 ; G06N5/02 ; A61B5/35 ; A61B5/316

Abstract:
Techniques are disclosed for using feature delineation to reduce the impact of machine learning cardiac arrythmia detection on power consumption of medical devices. In one example, a medical device performs feature-based delineation of cardiac electrogram data sensed from a patient to obtain cardiac features indicative of an episode of arrythmia in the patient. The medical device determines whether the cardiac features satisfy threshold criteria for application of a machine learning model for verifying the feature-based delineation of the cardiac electrogram data. In response to determining that the cardiac features satisfy the threshold criteria, the medical device applies the machine learning model to the sensed cardiac electrogram data to verify that the episode of arrhythmia has occurred or determine a classification of the episode of arrythmia.
Public/Granted literature
- US20210343416A1 REDUCED POWER MACHINE LEARNING SYSTEM FOR ARRHYTHMIA DETECTION Public/Granted day:2021-11-04
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