Adaptive Cardio Load Targets for Improving Fitness and Performance

2025-08-15

AI Summary

Existing fitness goal systems lack dynamic adaptation of cardiovascular load to individual physiological responses. Method: This study proposes a personalized weekly cardiorespiratory workload targeting framework based on heart rate reserve (HRR). We first establish an integrated, 24-hour cardiovascular workload quantification model that unifies structured exercise and incidental daily activities. An adaptive algorithm—trained on user feedback and internal research data—enables real-time weekly goal adjustment. Contributions: (1) It explicitly distinguishes performance-oriented cardiorespiratory workload from health-oriented active minutes; (2) it supports accumulation of workload via short, frequent bouts, thereby improving adherence and cardiopulmonary fitness gains. The system has been fully developed and is scheduled for public beta release on Fitbit starting September 2025, establishing a novel paradigm for precision exercise prescription in wearable devices.

Technology Category

• Planning, Routing, and Scheduling: Activity and Plan Recognition
• Cognitive Modeling & Cognitive Systems: Adaptive Behavior
• Humans and AI: Intelligent User Interfaces

Application Category

• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Search and Retrieval-Augmented AI: Personalized, context-aware and across-device search
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Cardio Load, introduced by Google in 2024, is a measure of cardiovascular work (also known as training load) resulting from all the user's activities across the day. It is based on heart rate reserve and captures both activity intensity and duration. Thanks to feedback from users and internal research, we introduce adaptive and personalized targets which will be set weekly. This feature will be available in the Public Preview of the Fitbit app after September 2025. This white paper provides a comprehensive overview of Cardio Load (CL) and how weekly CL targets are established, with examples shown to illustrate the effect of varying CL on the weekly target. We compare Cardio Load and Active Zone Minutes (AZMs), highlighting their distinct purposes, i.e. AZMs for health guidelines and CL for performance measurement. We highlight that CL is accumulated both during active workouts and incidental daily activities, so users are able top-up their CL score with small bouts of activity across the day.

Problem

• Develop adaptive cardio load targets for fitness improvement
• Compare Cardio Load and Active Zone Minutes purposes
• Accumulate Cardio Load from workouts and daily activities

Innovation

• Adaptive weekly Cardio Load targets
• Personalized based on heart rate
• Combines workouts and daily activities