A personalized and automated real-time meal detection algorithm based on continuous glucose monitoring and heart rate data for individuals with post-bariatric hypoglycemia - Takeaways - MDSpire

A personalized and automated real-time meal detection algorithm based on continuous glucose monitoring and heart rate data for individuals with post-bariatric hypoglycemia

  • By

  • Luca Cossu

  • Giacomo Cappon

  • Felix Wortmann

  • David Herzig

  • Lia Bally

  • Andrea Facchinetti

  • July 1, 2026

  • 0 min

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  • 1

    A real-time meal detection algorithm for post-bariatric hypoglycemia combines continuous glucose monitoring and heart rate data.

  • 2

    The algorithm achieved 100% recall in controlled settings and 85% precision with 78% recall in free-living conditions.

  • 3

    It reduced false positives compared to CGM-only algorithms, with one false positive every 2.3 days.

  • 4

    The algorithm eliminates the need for manual meal logging, addressing a significant barrier in glucose management.

  • 5

    The study involved 40 patients monitored for up to 50 days using a Dexcom G6 CGM and a Garmin Venu Sq smartwatch.

Original Source(s)

A personalized and automated real-time meal detection algorithm based on continuous glucose monitoring and heart rate data for individuals with post-bariatric hypoglycemia

  • by Luca Cossu, Giacomo Cappon, Felix Wortmann, David Herzig, Lia Bally, Andrea Facchinetti

  • July 1, 2026

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