In recent years, heart rate monitoring has emerged as a critical tool in the fitness industry. With the advent of wearable technology and advancements in sensor integration, athletes and fitness enthusiasts now have unprecedented access to real-time data that offers a deeper understanding of their bodies’ responses during physical activity. Monitoring heart rate (HR) is no longer just about performance tracking; it has become essential for optimizing workout effectiveness, enhancing safety, and achieving long-term fitness goals. In this blog, we explore how heart rate monitoring has evolved and the impact it has on effective exercise and training.
The methodology for monitoring physical or sports training (classified as resistance activities) has progressed significantly. From an almost exclusive use of subjective perception of effort we have progressed to a much more individualized, adjusted, streamlined, and to a certain degree, much more effective level of training planning. The use of devices which simultaneously read multiple variables, both internal (HR, respiratory rate, temperature) as well as external (accelerometry, speed, height, temperature, etc.) has permitted specific monitoring of the intensity and even the duration of physical activity.
Why Heart Rate Monitoring Matters
Health Experts Recommend
Scientific monitoring of training sessions has led to a considerable advance in the physiological measurement of humans adaptation to physical effort. The massification of the use of devices and applications which monitor HR constantly during exercise or even during competition makes it easier to include people in sporting events geared towards the general public (10K races, bicycle tours, hikes, etc.). In the field of sports sciences and clinically applied sports medicine, the emergence of numerous and modern individual monitoring devices is increasingly common. Generally, we can speak of broad groups of sensors: movement sensors (pedometers, accelerometers, and GPS) and physiological sensors (heart rate monitors, temperature sensors and integrated sensors.)
Overall, many of these contribute to improving the confidence of those who engage in exercise, and provide a certain degree of security on a cardiovascular level. However, during physical exertion, individuals may occasionally register HRs which tend to be abnormally elevated. It is important to remember that although heart rate monitors were designed for healthy athletes with a baseline sinus rhythm, these devices are capable of detecting exercise-induced arrhythmias. However, they do not detect QRS complex morphology, let alone atrial signs, and should therefore be used cautiously. Although many healthcare professionals may broadly recognize the relevance of continuous ongoing HR monitoring during exercise, heart rate rhythm monitors continue to be very frequently misused or even discontinued after a time by users and patients when their functions, even the most basic ones, are not understood.
Anatomical Perspective of Wearable Technology (WT)
Anatomy is the study of the structure and organization of living organisms and their parts. WT is the term for devices or materials that can be worn on the body and provide some functionality, such as sensing, computing, communication, or entertainment.
The relationship between anatomy and the physical structure of WT is important for several reasons:
It affects the comfort, fit, and usability of the WT or material.
It influences the accuracy, reliability, and validity of the data collected by the WT or material.
It determines the potential benefits, risks, and limitations of the WT or material for different applications and users.
Sleeves, shirts, trousers, vests, jerseys, and gloves allow real-time monitoring of various internal and external training loads related to athletes. For this purpose, WT structures are designed to be placed on different anatomical regions according to the type of training and sport. Some of the anatomical concepts that are relevant for WT are:
Anatomical regions: The body can be divided into different regions based on location, function, or structure. For example, the head, neck, torso, arm, hand, leg, and foot are anatomical regions that can wear different devices or materials.
Physical movement: The body can perform different types of movement based on the joints, muscles, and bones involved. For example, flexion, extension, abduction, adduction, rotation, and circumduction are types of movement that can affect the fit, function, and comfort of WTs or materials.
Perspiration-comfort: The body can produce sweat as a way of cooling down and regulating body temperature. Sweat can affect the skin condition, moisture level, and friction of the body part that wears the device or material. For example, sweat can cause skin irritation, infection, or corrosion if not properly managed by the WT or material.
Ergonomics: The body can interact with the environment and the device or material in different ways based on its posture, position, and orientation. Ergonomics is the study of how to design devices or materials that fit the human body and its activities. For example, ergonomics can improve the usability, efficiency, and safety of WTs or materials.
Heart Rate Measurement in Recent Years
Over the last 20 years, heart rate monitors (HRMs) have become a widely used training aid for a variety of sports.
The development of new HRMs has also evolved rapidly during the last two decades.
In addition to heart rate (HR) responses to exercise, research has recently focused more on heart rate variability (HRV). Increased HRV has been associated with lower mortality rate and is affected by both age and sex. During graded exercise, the majority of studies show that HRV decreases progressively up to moderate intensities, after which it stabilises. There is abundant evidence from cross-sectional studies that trained individuals have higher HRV than untrained individuals.
The results from longitudinal studies are equivocal, with some showing increased HRV after training but an equal number of studies showing no differences. The duration of the training programmes might be one of the factors responsible for the versatility of the results. HRMs are mainly used to determine the exercise intensity of a training session or race. Compared with other indications of exercise intensity, HR is easy to monitor, is relatively cheap and can be used in most situations. In addition, HR and HRV could potentially play a role in the prevention and detection of overtraining. The effects of overreaching on submaximal HR are controversial, with some studies showing decreased rates and others no difference. Maximal HR appears to be decreased in almost all 'overreaching' studies. So far, only few studies have investigated HRV changes after a period of intensified training and no firm conclusions can be drawn from these results.
The relationship between HR and oxygen uptake (VO(2)) has been used to predict maximal oxygen uptake (VO(2max)). This method relies upon several assumptions and it has been shown that the results can deviate up to 20% from the true value. The HR-VO(2) relationship is also used to estimate energy expenditure during field conditions. There appears to be general consensus that this method provides a satisfactory estimate of energy expenditure on a group level, but is not very accurate for individual estimations. The relationship between HR and other parameters used to predict and monitor an individual's training status can be influenced by numerous factors. There appears to be a small day-to-day variability in HR and a steady increase during exercise has been observed in most studies. Furthermore, factors such as dehydration and ambient temperature can have a profound effect on the HR-VO(2) relationship.
There has been a rapid increase in the use of wearable technology-based physical activity trackers. Most of these physical activity trackers include tracking and displaying the individual's heart rate (HR). There is little known about how HR monitoring influences the perception of exertion and attention allocation. Shifting attentional focus toward the body (association), such as monitoring HR, instead of environmental stimuli (dissociation) may increase one's perceived level of exertion. The purpose of the study was to examine the effects of HR monitoring on ratings of perceived exertion (RPE) and attention allocation during an exertive stepping task in individuals of varying fitness levels.
The YMCA stepping task normative values determined fitness levels. For the experimental condition, participants were randomly assigned to one of two conditions (i.e., HR monitoring or control) and completed a stepping task with a weighted vest at 20% of their bodyweight. HR, RPE, and attention allocation were collected at 30-s intervals. Performing the stepping task resulted in a gradual increase of HR and RPE along with a shift from dissociative to associative attention across all conditions. Monitoring one's HR during the task resulted in more dissociative attention allocation, however, no RPE differences were reported between the two conditions. Unfit individuals reported lower levels of RPE during the first time point compared to fit individuals despite having higher HR throughout the task.
The results of this study have relevance for applied practitioners implementing physical activity interventions with individuals who monitor their HR.
At its core, WT is the Internet of Things devices and consists of three layers: sensor, processing and network. The first two layers, the sensor and the processor, cover all the operations that take place only on the electronic hardware of the WT. In October, various external devices, computing methods and communication protocols are included in the network layer as part of the WT.
Physiological Sensors
Physiological data covers information obtained from biological processes occurring in the human body and serves as a valuable source of insight into an individual's health, performance or general condition. Prominent among the sensors used to capture physiological data are Decently recognized devices such as Electromyography (EMG), Electrocardiography (ECG) and Electroencephalography (EEG). In addition, physiological data collection is expanded to include a number of sensors such as functional Near-Infrared Spectroscopy (fNIRS), Oximetry, Blood Pressure Sensors (BPS), Galvanic Skin Response (GSR) and respiratory monitoring sensors.
In the context of sports and related fields, the term “biometric data” is used from time to time to describe the physiological data obtained from athletes. However, it is important to distinguish this use from the field of engineering, where “biometric data” covers information used for the purpose of identifying individuals through the analysis of their biological characteristics and events. Biometric authentication is based on immutable physical or behavioral characteristics unique to each individual and is considered unalterable. Governments and security systems therefore use biometrics as a robust method of personal identification. It is very important to recognize that the data collected from sensors that measure an athlete's physiological responses do not, by their very nature, have the same uniqueness or distinguishing feature as biometric data.
As a result, caution should be exercised when applying the term "biometric data" in the context of athletic research, as this misalignment in terminology can potentially lead to legal and ethical complications, as well as cause confusion in the scientific community.
ECG
An ECG is a technique that records cardiac electrical activity and provides information about heart rate variability (HRV), cardiac arrhythmias, and cardiovascular health. The ECG is a valuable tool for assessing the health and performance of athletes, as it can reflect autonomic nervous system regulation, metabolic demand, and cardiac adaptation to exercise. An ECG is an important tool for monitoring the health and performance of athletes, optimizing exercise programs, and evaluating heart health.
ECG electrodes are placed in certain places of the trunk and limbs to capture signals generated by cardiac depolarization and repolarization. Some commercial wts, such as smartwatches and wristbands, claim to have ECG detection capabilities, but they usually measure a single-ended ECG, which is more suitable for detecting training load or heart conditions than providing a comprehensive ECG analysis. Traditional ECG acquisition is often uncomfortable and intrusive, as it requires multiple electrodes and cables, which can interfere with the natural movement of athletes.
The uses and benefits of wearable technologies in research
There are many benefits of using wearable technologies in PNI research in general and stress and health studies in particular. At the most basic level, researchers can Decently use wearable devices to compare basal physiological functioning and behaviors between populations. For example, researchers can Decipher how resting HR (calculated as the average heart rate when relatively inactive for several weeks, for example) changes depending on lifetime exposure to major stressors, and it has been found that this predicts health, or between healthy adults and patients with post-traumatic stress disorder , depression or diabetes.
Also, because wearable technologies can track intrapersonal changes in biomarkers over time, researchers can track and Decode both interpersonal and intrapersonal changes from minute to minute, hour to hour, day to day, week to week, or month to month. In doing so, wearable technologies can provide researchers with real-time feedback on chronic disease management and progression and early disease detection. For example, the COVID-19 pandemic has found a new use for wearable devices for early detection of infectious diseases even before users realize they have a disease, which is often done by developing algorithms using "donated" wearable data from participants who already have wearable technology. Others have used wearable technologies to help develop machine learning algorithms that can identify the presence of mental health disorders (depression, for example) and monitor clinical treatment response. Remarkably, while the uses so far have shown promise in terms of wearable technologies' ability to detect and monitor diseases, the level of accuracy in wearable technologies (especially consumer-grade devices) and the variety of algorithms tested so far do not yet provide sufficient support for using wearable technologies to inform clinical decisions and monitor diseases on their own.
Until further research validation is completed, a strong safety and efficacy evidence base is available, and data security is guaranteed, appropriate attention is required to ensure that patients are not harmed by using wearable technologies in healthcare.
Psychological, Behavioral and Physiological Factors in Natural Environments
Importantly, data from wearable technologies and their applications allow researchers to observe every day differences in people to better understand how psychological, behavioral and physiological factors are interconnected in natural environments over time. For example, researchers can study how psychological factors such as feeling anxious, captured using in-app measurements, or health behaviors such as sleep quantity and sleep quality affect stress and health-related physiological indicators such as heart rate variability in both the short and long term. Similarly, researchers can investigate how changes in physiological indicators of stress affect the likelihood that participants will engage in certain health behaviors, as well as their self-reported impact and cognition. For example, researchers can ask questions such as:
How do fluctuations in HRV and resting heart rate affect the likelihood of drinking alcohol?
Finally, wearable technologies allow researchers to collect physiological and behavioral data remotely. Remote data collection continues to become more widespread as researchers develop new processes to improve participant recruitment, reduce the likelihood of the "white coat phenomenon" affecting data, and expand participant access. Remote data collection became even more popular when the COVID-19 pandemic required many laboratories to stop face-to-face purchases. January May 2020, a survey of 245 researchers found that the proportion of remote interactions with participants changed from 9% in January 2020 to 57% in May 2020. Wearable technologies have made the transition to remote research possible in many studies examining physiological processes.
References
Comments