Key result
Breathing rate estimation from heart rate using band-pass filters with short-term Fourier transform achieved a 5.5% error compared to a metabolic measurement system.
Why the study?
The study evaluated whether breathing rate could be estimated from respiratory sinus arrhythmia using heart rate recorded via a chest belt during physical activities, providing additional physiological insight without an extra sensor.
Does indirect estimation of breathing rate from heart rate monitoring systems provide accurate measurements compared to a metabolic measurement system in healthy adults during running?
Observational (n=31)
Does indirect estimation of breathing rate from heart rate monitoring systems provide accurate measurements compared to a metabolic measurement system in healthy adults during running?
Breathing rate can be reasonably accurately estimated from heart rate chest belts during running using specific signal processing algorithms, eliminating the need for additional respiratory sensors.
May enable BR monitoring via existing HR belts in healthy runners; leaves open validation in patients and during varied conditions.
Recent advances in wearable technologies integrating multi-modal sensors have enabled the in-field monitoring of several physiological metrics. In sport applications, wearable devices have been widely used to improve performance while minimizing the risk of injuries and illness. The objective of this project is to estimate breathing rate (BR) from respiratory sinus arrhythmia (RSA) using heart rate (HR) recorded with a chest belt during physical activities, yielding additional physiological insight without the need of an additional sensor. Thirty-one healthy adults performed a run at increasing speed until exhaustion on an instrumented treadmill. RR intervals were measured using the Polar H10 HR monitoring system attached to a chest belt. A metabolic measurement system was used as a reference to evaluate the accuracy of the BR estimation. The evaluation of the algorithms consisted of exploring two pre-processing methods (band-pass filters and relative RR intervals transformation) with different instantaneous frequency tracking algorithms (short-term Fourier transform, single frequency tracking, harmonic frequency tracking and peak detection). The two most accurate BR estimations were achieved by combining band-pass filters with short-term Fourier transform, and relative RR intervals transformation with harmonic frequency tracking, showing 5.5% and 7.6% errors, respectively. These two methods were found to provide reasonably accurate BR estimation over a wide range of breathing frequency. Future challenges consist in applying/validating our approaches during in-field endurance running in the context of fatigue assessment.
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Prigent et al. (2021) conducted an observational in Healthy adults (n=31). Breathing rate estimation from heart rate using a chest belt vs. Metabolic measurement system was evaluated on Error in breathing rate estimation. Breathing rate estimation from heart rate using band-pass filters with short-term Fourier transform achieved a 5.5% error compared to a metabolic measurement system.
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