TU Darmstadt / ULB / TUprints

Measurement, Prediction, and Control of Individual Heart Rate Responses to Exercise — Basics and Options for Wearable Devices

Ludwig, Melanie ; Hoffmann, Katrin ; Endler, Stefan ; Asteroth, Alexander ; Wiemeyer, Josef (2024)
Measurement, Prediction, and Control of Individual Heart Rate Responses to Exercise — Basics and Options for Wearable Devices.
In: Frontiers in Physiology, 2018, 9
doi: 10.26083/tuprints-00016219
Article, Secondary publication, Publisher's Version

Copyright Information: CC BY 4.0 International - Creative Commons, Attribution.

Download (633kB) | Preview
Item Type: Article
Type of entry: Secondary publication
Title: Measurement, Prediction, and Control of Individual Heart Rate Responses to Exercise — Basics and Options for Wearable Devices
Language: English
Date: 8 March 2024
Place of Publication: Darmstadt
Year of primary publication: 25 June 2018
Place of primary publication: Lausanne
Publisher: Frontiers Media S.A.
Journal or Publication Title: Frontiers in Physiology
Volume of the journal: 9
Collation: 15 Seiten
DOI: 10.26083/tuprints-00016219
Corresponding Links:
Origin: Secondary publication DeepGreen

The use of wearable devices or "wearables" in the physical activity domain has been increasing in the last years. These devices are used as training tools providing the user with detailed information about individual physiological responses and feedback to the physical training process. Advantages in sensor technology, miniaturization, energy consumption and processing power increased the usability of these wearables. Furthermore, available sensor technologies must be reliable, valid, and usable. Considering the variety of the existing sensors not all of them are suitable to be integrated in wearables. The application and development of wearables has to consider the characteristics of the physical training process to improve the effectiveness and efficiency as training tools. During physical training, it is essential to elicit individual optimal strain to evoke the desired adjustments to training. One important goal is to neither overstrain nor under challenge the user. Many wearables use heart rate as indicator for this individual strain. However, due to a variety of internal and external influencing factors, heart rate kinetics are highly variable making it difficult to control the stress eliciting individually optimal strain. For optimal training control it is essential to model and predict individual responses and adapt the external stress if necessary. Basis for this modeling is the valid and reliable recording of these individual responses. Depending on the heart rate kinetics and the obtained physiological data, different models and techniques are available that can be used for strain or training control. Aim of this review is to give an overview of measurement, prediction, and control of individual heart rate responses. Therefore, available sensor technologies measuring the individual heart rate responses are analyzed and approaches to model and predict these individual responses discussed. Additionally, the feasibility for wearables is analyzed.

Uncontrolled Keywords: wearable sensors, heart rate modeling, heart rate control, heart rate prediction, phenomenological approaches, training monitoring, load control
Identification Number: Artikel-ID: 778
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-162198
Additional Information:

This article is part of the Research Topic: Wearable Sensor Technology for Monitoring Training Load and Health in the Athletic Population

Specialty section: This article was submitted to Exercise Physiology, a section of the journal Frontiers in Physiology

Classification DDC: 000 Generalities, computers, information > 004 Computer science
600 Technology, medicine, applied sciences > 610 Medicine and health
700 Arts and recreation > 796 Sports
Divisions: 03 Department of Human Sciences > Institut für Sportwissenschaft > Sportinformatik
Date Deposited: 08 Mar 2024 13:10
Last Modified: 30 Apr 2024 15:12
SWORD Depositor: Deep Green
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/16219
PPN: 517683091
Actions (login required)
View Item View Item