[Research Review] Underwater Heart Rate Error Analysis: Comparison of Optical Green Light Sensors and Chest Strap Heart Rate Monitors in Swimming — Advances in Frontier Exercise Physiology Research (Article 675)

Reference Journal Source: Journal of Sports Sciences • International Scientific Research Findings Review Series

This article explores the sources of error in underwater heart rate measurement, comparing the accuracy of optical green light sensors (PPG) and chest strap heart rate monitors (ECG-based) in swimming environments.

Sources of Error in Optical Heart Rate Sensing

Optical heart rate sensors (used by most sports watches) estimate heart rate by shining green LED light onto the skin and detecting changes in reflected light from blood flow. In swimming scenarios, there are three main sources of error:

• Water seepage interference: Water seeps through the gap between the strap and skin, altering the contact between the sensor and skin, and disrupting the stability of the optical signal
• Repetitive wrist muscle contraction: The pulling motion repeatedly compresses the wrist muscles and subcutaneous tissue, making the optical signal susceptible to contamination from muscle blood flow signals, which are difficult to distinguish from heartbeat signals
• Cold-induced vasoconstriction: When water temperature is low, peripheral blood vessels constrict, reducing blood flow in the superficial skin layers and weakening the optical signal intensity itself

Relative Advantages and Limitations of Chest Strap Heart Rate Monitors

Chest straps detect the heart’s electrical signals directly through electrodes (similar to a simplified ECG), and are unaffected by changes in superficial skin blood flow. In theory, they offer higher accuracy and serve as the “gold standard” reference used in most sports science research. However, chest straps still have limitations in swimming scenarios: they require good contact to maintain signal stability; prolonged swimming may cause electrode contact to loosen due to skin sweating/water ingress; and some chest strap products do not have sufficient waterproof ratings to withstand prolonged submersion.

Comparison of Error Magnitudes Between the Two Sensing Methods (Illustrative)

Core Research Conclusions and Practical Recommendations

• Choose chest straps for high-intensity training: If precise heart rate zone training is needed (e.g., interval workouts), it is recommended to use a chest strap heart rate monitor with a sufficient waterproof rating
• Optical watches as trend reference: Although optical sensing data contains errors, it can still serve as a reference for long-term training trends and overall intensity distribution — there is no need to completely abandon it due to errors
• Verify device fit: Regardless of the sensing method, confirming that the device fits snugly but comfortably before training is the most direct and effective way to reduce errors
• Combine with perceived exertion: When underwater heart rate data is unstable, the Rating of Perceived Exertion (RPE) scale can be used as a supplementary aid for pace adjustment

Common Research Q&A (FAQ)

Q: Why does watch heart rate often fluctuate erratically during swimming?

A: This is mostly noise caused by optical signals being interfered with by water flow and wrist muscle movement, rather than true dramatic fluctuations in heart rate. It is recommended to interpret data using trend lines rather than single-point values.

Q: Are all chest strap heart rate monitors suitable for swimming?

A: No. You need to confirm that the product explicitly indicates a waterproof rating suitable for underwater use and the signal transmission method (some chest straps using Bluetooth transmission will lose signal underwater; models with underwater memory storage capability should be selected).

References and Academic Citations

1. Journal of Sports Sciences — Research direction related to accuracy comparison of wearable device heart rate measurement.
2. IEEE Journal of Biomedical and Health Informatics — Literature related to optical heart rate sensing signal noise processing.

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