Identification of anaerobic threshold using heart rate response during dynamic exercise.

Area of Science:

• Exercise Physiology
• Biomedical Engineering
• Cardiovascular Research

Background:

• The anaerobic threshold (AT) is a critical physiological marker during exercise.
• Accurate detection of AT is essential for training prescription and performance analysis.
• Current methods for AT detection can be invasive or require complex equipment.

Purpose of the Study:

• To characterize heart rate (HR) patterns in healthy males using the Autoregressive Integrated Moving Average (ARIMA) model.
• To evaluate the efficacy of the ARIMA model in detecting the anaerobic threshold (AT) during discontinuous dynamic exercise tests (DDET).
• To compare HR responses between young and middle-aged adults.

Main Methods:

• Nine young and nine middle-aged healthy males performed three discontinuous dynamic exercise tests (DDET) on a cycle ergometer.
• Protocols included stepped and randomized power increases, alongside a continuous ramp protocol for ventilatory AT measurement.
• Heart rate was recorded beat-to-beat and analyzed using ARIMA models.

Main Results:

• The median physical exercise workloads for AT were similar between stepped and randomized DDET protocols.
• AT occurred at comparable power values to the positive trend in HR responses identified by ARIMA.
• The ARIMA model demonstrated a promising ability to detect AT during submaximal dynamic exercise.

Conclusions:

• The Autoregressive Integrated Moving Average (ARIMA) model is a viable tool for analyzing heart rate patterns during exercise.
• ARIMA modeling shows potential for non-invasive detection of the anaerobic threshold (AT).
• Further research can explore the application of ARIMA in diverse populations and exercise modalities.