What is it about?
This study introduces an automated algorithm that analyzes heart rate during High‑Intensity Interval Training (HIIT) in real time. It detects the peaks (maxima) and dips (minima) in heart rate, calculates how quickly heart rate rises and falls, and computes average levels between intervals. Data from indoor cycling sessions with 25 healthy adults showed the algorithm accurately mirrored expert assessments, processing each session in about 1.2 seconds
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Why is it important?
Monitoring heart rate during HIIT is crucial for understanding cardiovascular strain, adaptation, and recovery. Traditional manual analysis is slow, inconsistent, and labor‑intensive. This automated approach offers objective, fast, and reliable insights. Specifically, it identifies patterns where rapid increases in heart rate and slow recovery indicate lower fitness, while consistent rises in minima and maxima signal effective conditioning
Perspectives
Future research should test the algorithm with different populations (e.g., elite athletes, clinical groups), add more physiological sensors, and deploy it in field training settings. Advanced versions could predict fatigue, track long‑term fitness trends, and support personalized HIIT prescription
Manuel Gómez-López
University of Murcia
Read the Original
This page is a summary of: Algorithm-Based Real-Time Analysis of Heart Rate Measures in HIIT Training: An Automated Approach, Applied Sciences, April 2025, MDPI AG,
DOI: 10.3390/app15094749.
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