Wearable devices represent one of the most popular trends in health and fitness. Rapid advances in wearable technology present a dizzying display of possible functions: from thermometers and barometers, magnetometers and accelerometers, to oximeters and calorimeters. Consumers and practitioners utilize wearable devices to track outcomes, such as energy expenditure, training load, step count, and heart rate. While some rely on these devices in tandem with more established tools, others lean on wearable technology for health-related outcomes, such as heart rhythm analysis, peripheral oxygen saturation, sleep quality, and caloric expenditure. Given the increasing popularity of wearable devices for both recreation and health initiatives, understanding the strengths and limitations of these technologies is increasingly relevant. Need exists for continued evaluation of the efficacy of wearable devices to accurately and reliably measure purported outcomes. The purposes of this review are (1) to assess the current state of wearable devices using recent research on validity and reliability, (2) to describe existing gaps between physiology and technology, and (3) to offer expert interpretation for the lay and professional audience on how best to approach wearable technology and employ it in the pursuit of health and fitness. Current literature demonstrates inconsistent validity and reliability for various metrics, with algorithms not publicly available or lacking high-quality validation studies. Advancements in wearable technology should consider standardizing validation metrics, providing transparency in used algorithms, and improving how technology can be tailored to individuals. Until then, it is prudent to exercise caution when interpreting metrics reported from consumer-wearable devices.

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TO THE EDITOR: Podlogar et al. ( 1) have nicely discussed current methods for classifying athletes in applied physiology studies attending to their training or performance level. We agree with them that relying on a single physiological marker such as maximum oxygen uptake is not without limitations and endorse the use of more performance-based indicators. However, before proposing critical power/speed (CP/ CS) as the primary indicator of an athlete's training status, the robustness of these variables and the best method for their determination remains to be confirmed. Differences in mathematical models or test durations can indeed have a remarkable impact on an individual's CP/CS (e.g., up to $1 km/ h for CS in top-level runners) (2).More research is needed to provide reference or "normative" values of CP/CS allowing classification of athletes into different performance/fitness categories. An alternative, at least in cycling, might be classifying athletes attending to the highest power output that they can achieve for a given duration-the so-called "mean maximum power" (MMP) (3). This approach does not require the use of mathematical calculations or additional laboratory testing and is sensitive enough to allow discerning actual performance even between the two highest category levels-Union Cycliste Internationale [UCI] ProTeam versus UCI WorldTour-in professional cyclists (4). We have recently reported normative MMP values for male (n = 144) (4) and female professional cyclists (n = 44) (5). If a similar approach was used in cyclists of a lower training/competition level, scientists and coaches could accurately classify participants in cycling physiology studies.