![]() ![]() Technology development has typically been driven by bioengineers. In this way, technology is becoming “smarter,” more personalized with the possibility of providing real-time feedback to users (Sawka and Friedl, 2018). Health and performance technology is now moving toward miniaturized sensors, integrated computing, and artificial intelligence. Consumer technology is moving beyond basic measurement and telemetry of standard vital signs, and predictive algorithms based on static population-based information. This technology is at various stages of development: some has been independently tested to determine its reliability and validity, whereas other technology has not been properly tested. The number and availability of consumer technologies for evaluating physical and psychological health, training emotional awareness, monitoring sleep quality, and assessing cognitive function has increased dramatically in recent years. To get the best value, consumers should carefully select such products, not only based on their personal needs, but also according to the strength of supporting evidence and effectiveness of the products. To create a competitive advantage, companies producing health and performance technologies should consult with consumers to identify real-world need, and invest in research to prove the effectiveness of their products. Looking to the future, the rapidly expanding market of health and sports performance technology has much to offer consumers. The value of such technologies for consumer use is debatable, however, because they may require extra time to set up and interpret the data they produce. Around 10% of technologies have been developed for and used in research. Only 5% of the technologies have been formally validated. Among the technologies included in this review, more than half have not been validated through independent research. Consumers who are choosing new technology should consider whether it (1) produces desirable (or non-desirable) outcomes, (2) has been developed based on real-world need, and (3) has been tested and proven effective in applied studies in different settings. ![]() In this review, we have summarized the features and evaluated the characteristics of a cross-section of technologies for health and sports performance according to what the technology is claimed to do, whether it has been validated and is reliable, and if it is suitable for general consumer use. These variables include cardiorespiratory function, movement patterns, sweat analysis, tissue oxygenation, sleep, emotional state, and changes in cognitive function following concussion. A wide range of smart watches, bands, garments, and patches with embedded sensors, small portable devices and mobile applications now exist to record and provide users with feedback on many different physical performance variables. ![]() Even the most advanced machine learning and signal processing techniques for EEG data cannot remove all sources of noise, so getting good electrode contact and reducing body and movement is an important part of using Muse® effectively.The commercial market for technologies to monitor and improve personal health and sports performance is ever expanding. Muse® is very sensitive and will pick up electrical activity from muscles around the eyes, jaw, and brainwaves from visual processing. It is very important that you are sitting in a comfortable position with your eyes lightly closed when using Muse®, as having open eyes will impact the experience session. The Muse application takes each unique session’s calibration as a baseline for the corresponding session. Any sharing of your account, testing during the calibration, calibrating with your eyes open, being overly active, moving, or visualizing things during the calibration could potentially skew your data, creating an inaccurate baseline for your sessions to compare against, generally resulting in a higher calm score. This stage is important, as it provides Muse® with a picture of your active brain to compare against during the session. Discrepancies in your sessions are generally tied to the calibration stage. The results of a Muse® session are dependent on the quality of the calibration before your session. ![]()
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