Insomnia (the persistent inability to fall or stay asleep) is one of the most commonly diagnosed sleep disorders in teenagers today. However, the troubling fact is that the way doctors currently diagnose it is almost entirely based on what patients say about their own sleep. They fill out questionnaires and keep sleep diaries. Research shows that these self-reports are frequently inaccurate, and in some cases, patients who are sleeping normally are being diagnosed with insomnia (sometimes even receiving powerful prescription sleep medications as a result). This paper argues that consumer wearable devices, the smartwatches and fitness trackers millions of teenagers already own, combined with artificial intelligence (AI), could fundamentally change this. By measuring heart rate variability (the small changes between heartbeats), movement, and other physiological signals, these devices can track sleep in ways that are objective, continuous, and surprisingly accurate. This review looks at how these technologies work, how accurate they are, what AI tools are being used to analyze their data, and why using objective, wearable-based measurement as an adjunct to clinical assessment could be one of the most important upgrades in sleep medicine in decades.
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