Heart rate monitoring of the endurance runner during high intensity interval training: Influence of device used on training functions

Ruiz-Alias, Santiago A.; García‐Pinillos, Felipe; Soto-Hermoso, Víctor M.; Ruiz-Malagón, Emilio J.

doi:10.1177/17543371211037035

Cited by 5 publications

(2 citation statements)

References 33 publications

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“…However, they have been characterized as being less accurate in tasks associated with high levels of movement compared to data acquired in clinic. The accuracy of wearable devices is related to their placement; for example, a device on the wrist is more likely to catch movement artefacts than one on the chest [1]. Nonetheless, even when placed on the chest, the relative error of a heart rate monitor increases with the level of exercise intensity [2].…”

Section: Introductionmentioning

confidence: 99%

Hearables: In-Ear Multimodal Data Fusion for Robust Heart Rate Estimation

Żyliński,

Nassibi,

Occhipinti

et al. 2024

BioMedInformatics

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Background: Ambulatory heart rate (HR) monitors that acquire electrocardiogram (ECG) or/and photoplethysmographm (PPG) signals from the torso, wrists, or ears are notably less accurate in tasks associated with high levels of movement compared to clinical measurements. However, a reliable estimation of HR can be obtained through data fusion from different sensors. These methods are especially suitable for multimodal hearable devices, where heart rate can be tracked from different modalities, including electrical ECG, optical PPG, and sounds (heart tones). Combined information from different modalities can compensate for single source limitations. Methods: In this paper, we evaluate the possible application of data fusion methods in hearables. We assess data fusion for heart rate estimation from simultaneous in-ear ECG and in-ear PPG, recorded on ten subjects while performing 5-min sitting and walking tasks. Results: Our findings show that data fusion methods provide a similar level of mean absolute error as the best single-source heart rate estimation but with much lower intra-subject variability, especially during walking activities. Conclusion: We conclude that data fusion methods provide more robust HR estimation than a single cardiovascular signal. These methods can enhance the performance of wearable devices, especially multimodal hearables, in heart rate tracking during physical activity.

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Section: Introductionmentioning

confidence: 99%

Hearables: In-Ear Multimodal Data Fusion for Robust Heart Rate Estimation

Żyliński,

Nassibi,

Occhipinti

et al. 2024

BioMedInformatics

View full text Add to dashboard Cite

show abstract

“…One of the exercises that can increase endurance is interval training (Feuerbacher & Schumann, 2023;Gibala et al, 2019;Hoffmann et al, 2021;Ruiz-Alias et al, 2021). This exercise is highly recommended by some experts in increasing Vo2max endurance.…”

Section: Introductionmentioning

confidence: 99%

The Effects of Interval Training on The V02max on The Basket Ball Players

Adila,

Ittaqwa,

Khozin

et al. 2023

JCSS

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Endurance plays an active role in basketball games as a support for implementing strategy and tactics, so players must have excellent endurance. The study aims to determine the impact of interval training on high school basketball players' endurance. The research applied the experimental method. The samples are ten participants of the As-Shofa basketball team determined through a total sampling technique. The research uses the one-group pretest-posttest design. The instrument in this study is a bleep test. Based on the test analysis, the tcount value obtained was 2,371, and the ttable value obtained was 1,833. These values indicate that the tcount value is greater than the ttable at a 0,05 sig. value. The results of this study can conclude a significant influence of interval training exercises on high school basketball players' endurance. The determinant value of endurance is 67% contribution. Thus, high-intensity interval training significantly increases the Vo2max endurance capacity.

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Examining weekly heart rate variability changes: a comparison between monitoring methods

et al. 2022

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Monitoring heart rate variability has been commonly performed by different devices which differ in their methods (i.e., night recording vs. upon awakening measure, pulse vs. R waves, and software signal processing), Thus, the purpose of this study was to determine the level of agreement between different methods of heart rate variability monitoring, represented in two different systems (i.e., the Polar Nightly Recharge™ function present in Polar sport watches and the Polar H10 chest strap synchronized with the Kubios app). A group of 11 recreational athletes performed a concurrent training program for eight weeks and heart rate variability was daily monitored through both devices. Very large correlation (r = 0.714) and good reliability (ICC = 0.817) were obtained between devices through the entire training program. The magnitude-based inference method was also applied to determine the likelihood of the change concerning the smallest worthwhile change. From a baseline corresponding to the first two weeks of the training program, the weekly heart rate variability changes of the following six weeks were determined for each participant with each device. Despite the large correlation and good reliability between devices, there was a 60.6% of discordance in the likelihood interpretation of the change for the 66 weeks evaluated, explained by the random errors found. Thus, practitioners should be aware of these differences if their training groups use different devices or if an athlete interchanges them. The different nuances of each device can condition the heart rate variability data variation which could compromise the interpretation of the autonomic nervous system modulation.

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Heart rate monitoring of the endurance runner during high intensity interval training: Influence of device used on training functions

Cited by 5 publications

References 33 publications

Hearables: In-Ear Multimodal Data Fusion for Robust Heart Rate Estimation

Hearables: In-Ear Multimodal Data Fusion for Robust Heart Rate Estimation

The Effects of Interval Training on The V02max on The Basket Ball Players

Examining weekly heart rate variability changes: a comparison between monitoring methods

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