capacity to provide customized recommendations and insights fit for certain needs and preferences. The accuracy and dependability of AI-powered wearables in health tracking have shown by empirical validation studies, hence strengthening their credibility and usefulness.Many research have been done to carefully evaluate how faithfully these devices capture physiological data. A fundamental research by Shcherbina et al. (2017) shows the
need of empirical validation.In their work, the authors matched gold-standard electrocardiogram values against heart rate readings taken from many wearable devices. The results showed a strong link between wearables' and s heart rate measurements, therefore proving the accuracy of wearable technologies in heart rate
monitoring. By means of a comparison of wearable device heart rate measures and electrocardiogram readings, one can assess the dependability and accuracy of the wearable devices in data capture. Given direct monitoring of the heart's electrical activity, it is regarded as the gold standard for heart rate measurement and so this
Comparison is quite important
By using cutting-edge artificial intelligence algorithms, including AI into wearable technology marks a major step forward for forward monitoring and intervention techniques. These systems examine personal traits, behavior patterns, and real-time physiological data gathered by wearable sensors to customize recommendations and treatments based on the particular need of the user. Several cases show the success of tailored monitorie tiredness or stress;
the wearable may advise lowering the intensity or stopping to avoid overuse and damage.On the other hand, if the user's physiological dat length, quality, and sleep stages, then tailored advice for bettering sleep quality can be given. Should the wearable identify poor sleep quality or disturbance, for example, it may provide relaxing strategies or lifestyle adjustments to
support improved sleep hygiene. Wearables can also alter wake-up alarms depending on sleep cycles to guarantee users feel rejuvenated and well-rested. Wearables can detect physiological stress signals, like heart rate variability; so, deconducted a validation study to evaluate the accuracy of Sleep-tracking characteristics in wearables under many conditions.
Inspired by a well-known technique
for recording sleep patterns—polysomnography—the researchers assessed wearable device performance in relation to sleep length, sleep stages, and sleep quality. The findings of the study showed that wearable sleep-tracking characteristics were equivalent to polysomnography in precisely measuring sleep metrics, therefore confirming their value in tracking sleep patterns.Considered the gold standard for measuring sleep parameters,
validating the accuracy of sleep-tracking features in wearables using polysomnography (PSG) includes comparing the sleep metrics collected by wearable devices with those obtained by Participants in empirical validation studies don wearable devices with sleep-tracking capabilities while PSG monitoring in a clinical or sleep laboratory. PSG entails thorough observation of many physiological factors including brain waves, eye movements, muscle
action, and heart rate during sleep. It offers comprehensive details on stages of sleep, length, efficiency, and other criteria. To evaluate the accuracy and dependability of the wearable devices' sleep-tracking features, researchers then contrast their metrics with those acquired from PSG recordings.Cases where wearable technologies show strong correlation and
Agreement with readings show how precisely
they capture sleep data. In a validation study, for instance, individuals wore wearable devices able of tracking sleep concurrently under PSG monitoring (Chinoy et al., 2021). The wearable devices' recorded sleep metrics—total sleep time, sleep onset latency, and sleep efficiency—were matched with the relevant PSG analysis measurements. Cases when the accuracy of the wearable devices in assessing sleep characteristics revealed their closely matching PSG-
derived sleep metrics.Using PSG as a benchmark, instances of proven accuracy of sleep-tracking features in wearables offer proof of the dependability of the devices in observing sleep patterns. These scenarios show how wearable technology could provide quick and non-invasive means of monitoring sleep in practical environments. It is important to recognize,
nonetheless, that the accuracy of sleep-tracking features could differ depending on wearable devices and individuals. Thus, thorough validation studies including various populations and settings are required to guarantee the dependability of sleep tracking in wearables. These empirical validation tests show rather convincing proof of how well artificial intelligence
essentially gathering heart rate data. Wearable technology's dependability in tracking heart rate is demonstrated by cases of great correlation and accuracy between ECG readings and wearable devices.Such situations highlight the practical and handy nature of wearable devices as means of real-world cardiovascular health monitoring instruments. Nevertheless,
Conclusion
the particular wearable device, its sensor technology, and the environment in which it is worn will affect these events. Consequently, thorough validation studThe local shoe industry in Indonesia is growing, one of the local shoe brands that is well known is PIERO, which has been established since 1999 Having experienced its peak in the early 2000s, many efforts are being made by Piero to maintain its existence. The development of the digital world,
especially the social media sector which eventually became social commerce, made Piero think about whether they should choose brand ambassadors and calculate the budget to collaborate with the right brand ambassador. Moreover, there are two kinds of digital brand ambassadors: micro and macro influencers. This issue ultimately becomes a problem that must be answered immediately, because PIERO's competitors have begun to move rapidly
social media with their brand ambassadors. The purpose of this research is to identify the effect between micro and macro brand ambassadors related to soft or hard language with brand trust, purchasing decision, brand image on Piero shoes. This research is using quantitative design. To conduct the study, the authors recruited 339 participants from an online social media then randomly assigned to one of four conditions: micro influencer with
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