Abstract
The use of wearable sensor technology for athlete training monitoring is growing exponentially, but some important measures and related wearable devices have received little attention so far. Respiratory frequency (fR), for example, is emerging as a valuable measurement for training monitoring. Despite the availability of unobtrusive wearable devices measuring fR with relatively good accuracy, fR is not commonly monitored during training. Yet fR is currently measured as a vital sign by multiparameter wearable devices in the military field, clinical settings, and occupational activities. When these devices have been used during exercise, fR was used for limited applications like the estimation of the ventilatory threshold. However, more information can be gained from fR. Unlike heart rate, O2, and blood lactate, fR is strongly associated with perceived exertion during a variety of exercise paradigms, and under several experimental interventions affecting performance like muscle fatigue, glycogen depletion, heat exposure and hypoxia. This suggests that fR is a strong marker of physical effort. Furthermore, unlike other physiological variables, fR responds rapidly to variations in workload during high-intensity interval training (HIIT), with potential important implications for many sporting activities. This Perspective article aims to (i) present scientific evidence supporting the relevance of fR for training monitoring; (ii) critically revise possible methodologies to measure fR and the accuracy of currently available respiratory wearables; (iii) provide preliminary indication on how to analyze fR data. This viewpoint is expected to advance the field of training monitoring and stimulate directions for future development of sports wearables.
Highlights
The large diffusion of wearable devices has stimulated interest in athlete training monitoring, with the aim of maximizing performance, and minimizing the risk of injury and illness (Düking et al, 2016)
Emblematic here, is the example of respiratory frequency, which may provide a better marker of physical effort compared to traditionally monitored physiological variables
The first attempt to interpret fR data normalized to f Rmax was made by Nicolò et al (2014a). They found a strong correlation between fR and Rating of Perceived Exertion (RPE) with similar values across a continuous and three different high-intensity interval training (HIIT) trials matched for effort and exercise duration
Summary
The large diffusion of wearable devices has stimulated interest in athlete training monitoring, with the aim of maximizing performance, and minimizing the risk of injury and illness (Düking et al, 2016). The development of sport-related technologies is occurring rapidly and is often guided by market forces rather than athlete or scientific needs. In this process, it is not uncommon that technological solutions and measures are available before the sport scientist or practitioner can appreciate their importance, and this can reduce the use of new technologies. Despite the availability of unobtrusive wearable devices measuring fR with relatively good accuracy, the practice of measuring fR during training is not common yet
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