When Dr. Jessilyn Dunn's research team at Duke University started analyzing data from thousands of wearables in 2020, they discovered something remarkable: the devices could detect COVID-19 infections before symptoms appeared. Heart rate variability, skin temperature, and sleep patterns shifted in subtle but measurable ways days before people felt sick. The revelation wasn't just about one virus—it was proof that the fitness trackers millions wear on their wrists had quietly become medical instruments.
From Step Counters to Medical Devices
The transformation happened faster than most people realized. Between 2019 and 2024, smartwatch ownership in the U.S. crept from 30% to 31% of the general population—a seemingly modest increase that masks a more significant shift. These devices stopped being glorified pedometers. The FDA approved more than 10 wearable health devices in 2024 alone, including continuous glucose monitors that eliminate fingersticks and ECG patches that detect irregular heart rhythms. The Dexcom G7, for instance, transmits glucose readings every five minutes directly to a smartphone.
The market reflects this evolution. What was a $10.72 billion industry in 2024 is projected to hit $25.26 billion by 2034. More telling: heart rate monitoring—once a niche feature for athletes—now accounts for 30% of the entire wearable biometrics market. Blood oxygen levels, ECG readings, and even blood pressure tracking have moved from doctor's offices to wrist-worn devices that cost less than a single emergency room visit.
The Research Revolution Nobody Planned
The pandemic accelerated something researchers now call "bring-your-own-device" studies. Instead of recruiting participants to wear specialized equipment in controlled settings, scientists started using data from devices people already owned. The approach solved several problems at once: larger sample sizes, longer observation periods, and data collected during actual daily life rather than artificial laboratory conditions.
Dr. Dunn's lab at Duke exemplifies this shift. Her team's BIG IDEAs Lab—Biomedical Informatics Group: Integrating Data Engineering and Analytics—analyzes digital biomarkers to identify both acute infections and chronic conditions. The CDC now estimates that nearly half of American adults monitor at least one health metric digitally. That's millions of data points collected continuously, creating a real-world dataset that would have been unimaginable a decade ago.
The implications extend beyond individual health tracking. Wearables detect subtle changes over weeks or months before major cardiac events occur. Traditional medicine catches problems after symptoms appear; continuous monitoring reveals warning signs during the asymptomatic phase when intervention might actually prevent the crisis.
The Gap Between Promise and Practice
Yet the people who might benefit most from these devices often don't use them. Less than one in four adults with cardiovascular disease or at risk for it wears a tracking device. Among those who do own wearables, only 38% use them regularly—compared to nearly 50% of adults without heart conditions.
The pattern repeats across demographics. Adults aged 18-49, those with higher household incomes, and college-educated individuals dominate wearable adoption. The technology is reshaping personal health data, but it's reshaping it selectively. A 55-year-old with hypertension and limited income—exactly the person who might prevent a heart attack through continuous monitoring—is statistically unlikely to own a device that costs $200-400 and requires a compatible smartphone.
This disparity matters because wearables are increasingly integrated into healthcare delivery. More than 80% of device users would share their data with doctors, and the healthcare providers segment is growing faster than the consumer fitness market. When clinical decisions start incorporating wearable data, patients without devices face a new kind of disadvantage. They're not just missing out on personal insights; they're excluded from an emerging standard of care.
The AI Layer That Makes It Work
Raw biometric data means little without interpretation. A resting heart rate of 72 beats per minute tells you nothing useful—but a 15% increase from your personal baseline might signal an oncoming infection. This is where artificial intelligence transforms wearables from sensors into diagnostic tools.
AI algorithms analyze patterns across multiple metrics simultaneously. They learn individual baselines, detect anomalies, and improve accuracy over time. The technology also extends battery life by determining when to collect data actively versus when to enter low-power modes. A device that measures heart rate every second during exercise but every ten minutes during sleep can run for days on a single charge.
Bluetooth connectivity—which accounts for 52% of wearable device connections—enables this processing to happen partly on the device and partly on smartphones or in the cloud. The 20-foot range limitation that once seemed like a technical constraint now functions as a privacy feature: data doesn't transmit unless you're near your phone.
When Your Bracelet Knows You're Getting Sick
The shift from fitness tracking to health monitoring raises questions the industry hasn't fully answered. If your smartwatch detects irregular heart rhythms, should it alert you immediately? What if the algorithm is wrong? If it's right and you ignore the warning, who bears responsibility?
These aren't hypothetical concerns. Continuous glucose monitors like the Dexcom G7 already make treatment decisions possible—and necessary—based on real-time data. As wearables detect more conditions earlier, the line between information and diagnosis blurs. The FDA regulates medical devices, but the approval process wasn't designed for software that updates automatically and algorithms that improve through machine learning.
Privacy concerns intensify as the data becomes clinically relevant. Fitness tracking felt optional and personal; medical monitoring involves insurance companies, employers, and healthcare systems. The multimodal authentication market is growing specifically to address these security needs, but authentication only protects against unauthorized access. It doesn't address who owns the data, who can sell it, or how predictive health information might be used by entities with financial interests in your future medical costs.
The Clinical Transformation Already Underway
North America leads the wearable biometrics market with 37% of global revenue, but Asia-Pacific is growing fastest. Mobile internet penetration exceeds 68% across the Asia-Pacific region, creating infrastructure for remote health monitoring in places where traditional medical facilities remain scarce. The technology might reach rural areas before comprehensive clinics do.
Chronic disease management applications are expanding faster than fitness tracking, signaling where the industry sees its future. The consumer electronics segment still holds 38% of the market, but healthcare providers and hospitals are adopting wearables for patient monitoring at accelerating rates. Published research in JAMA Network Open and other medical journals legitimizes the technology in clinical contexts, moving wearables from wellness accessories to diagnostic tools that generate data doctors increasingly trust.
The transformation is already reshaping what personal health data means. It's no longer primarily self-reported symptoms and annual checkups. It's continuous, multimodal, algorithmically analyzed streams of physiological information. The question isn't whether this changes healthcare—it already has. The question is whether the benefits will reach beyond the young, affluent, and healthy people who need them least.