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<\/p>\nWhen the first activity trackers hit the market in the 1960s, they did one thing: counted steps. In the 1980s and 1990s, athletes started wearing heart-rate monitors. In the early 2000s, tech companies like Fitbit and Garmin added GPS features, allowing runners and cyclists to track speed, distance and pace. Wearable technology expanded from shoe-mounted sensors and chest straps to armbands and wristwatches.\u00a0<\/p>\n
Today, a single smartwatch \u2014 or smart ring \u2014 can continuously monitor heart rate, stress, physical activity and dozens of other metrics. Some can even detect irregular heart rhythms or early signs of illness.\u00a0<\/p>\n
Researchers increasingly see these devices as something far more ambitious than fitness gadgets. They envision a future where artificial intelligence combines wearable data with blood tests, genomics and other biomarkers to detect disease earlier, personalize treatment and shift medicine from reacting to illness to preventing it.\u00a0<\/p>\n
\u201cThey\u2019re amazing,\u201d said Michael Snyder, a professor of genetics at Stanford Medicine who has spent years studying wearable devices and famously wears four different smartwatches, two smart rings and an exposometer to measure airborne exposures. \u201cThey track your health 24\/7 as long as you keep them charged.\u201d<\/p>\n
Snyder compares wearables to the dashboard of a car.<\/p>\n
\u201cYou don\u2019t drive a car without sensors and a dashboard,\u201d he said. \u201cYet we do that for our health. We run around without any sensors and health dashboards.\u201d His research has shown that changes in metrics such as resting heart rate and heart-rate variability can identify respiratory viral infections before symptoms appear.\u00a0<\/p>\n
\u201cWe think this is the tip of the iceberg.\u201d<\/p>\n
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As wearables become increasingly capable of monitoring the human body, many researchers say the bigger challenge is no longer simply collecting accurate data; it\u2019s determining how to turn the flood of information into meaningful insights for users, and perhaps, even for their doctors. Snyder and other researchers are hopeful that wearables could revolutionize personalized medicine. But it is unclear if the U.S. healthcare system can make use of smartwatch data \u2014 and whether consumers trust that their most personal health information will remain private.\u00a0<\/p>\n
How accurate are today\u2019s wearables?\u00a0<\/p>\n
Researchers say wearable activity trackers have become increasingly accurate at measuring dozens of different metrics from heart rate and heart rate variability to blood oxygen and skin temperature. Snyder and his colleagues routinely compare wearables with clinical-grade devices and generally, he said, most line up well.<\/p>\n
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A pedometer showing the number of steps Rikki Wolpowitz wears while playing soccer during physical education class at Foothill Elementary Tuesday. Credit: Jon Hatch\/Digital First Media\/Boulder Daily Camera via Getty Images.<\/p>\n
Jessilyn Dunn, a biomedical engineering professor at Duke University, said many of the sensors in today\u2019s wearables use the same underlying technology as medical devices already found in hospitals and clinics. Pulse oximeters, the small devices that clip to a patient\u2019s fingertip, use beams of light to estimate blood oxygen levels and heart rate. Smartwatches use a similar approach, using sensors on the underside of the watch.\u00a0<\/p>\n
But not all wearables collect data the same way. Many devices measure the same physiological signals, Snyder said, but might differ in how frequently they collect data or how much information is collected. For example, the Apple Watch measures heart rate more frequently than some competing devices, making it better suited to capturing brief spikes in heart rate. The trade-off, Snyder said, is shorter battery life.\u00a0<\/p>\n
Snyder said the trickiest activity to measure is sleep.\u00a0<\/p>\n
\u201cIn general, none of the devices are perfect,\u201d he said.\u00a0<\/p>\n
Kelly Glazer Baron, a behavioral sleep medicine researcher at the University of Utah, said that\u2019s because wearables aren\u2019t actually measuring sleep itself. \u201cSleep is defined by the rhythmic firing of neurons in your brain,\u201d she said. \u201cEverything else we\u2019re doing based on heart rate, movement, temperature, all that is trying to estimate the brain.\u201d\u00a0<\/p>\n
Today\u2019s newest devices have improved substantially, Baron said. Most estimate total sleep duration within about eight to 10 minutes of a laboratory sleep study, in which researchers hook sleeping patients up to an EEG to directly measure electrical activity in the brain.\u00a0<\/p>\n
Measuring sleep stages, however, is less precise.\u00a0<\/p>\n
While most wearables agree with EEG sleep studies about 70% of the time when classifying sleep into its four main categories \u2014 wakefulness, light sleep, deep sleep and REM \u2014 Baron said the bigger challenge is how people interpret those numbers. Patients frequently come to her worried that they aren\u2019t getting enough REM or deep sleep, even though those measurements can vary widely from person to person and have limited clinical significance for most people.\u00a0<\/p>\n
\u201cIt\u2019s a beautiful picture to see your sleep stages,\u201d Baron said, but \u201cthere\u2019s a tendency to overestimate that staging data.\u201d<\/p>\n
More than half of a typical night\u2019s sleep is naturally spent in light sleep, she noted. Medications, age and a slew of other factors can influence REM and deep sleep in ways that aren\u2019t necessarily cause for concern, she said.\u00a0<\/p>\n
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Researcher Hans Van Dongen, Ph.D., looks over recent polysomnographic sleep recordings at Washington State University Spokane\u2019s Sleep and Performance Research Center December 13, 2006 in Spokane, Washington. Credit: Jeff T. Green\/Getty Images.<\/p>\n
Data deluge<\/p>\n
Advances in genetic testing, blood biomarkers, microbiome research and artificial intelligence are increasingly moving medicine away from a one-size-fits-all approach toward more personalized care, allowing physicians to tailor prevention and treatment to each individual patient. Snyder believes wearable devices could become a key part of that transformation.\u00a0<\/p>\n
For one, they continuously monitor a person\u2019s physiology, creating a far richer picture of health than the single snapshot captured during an annual office visit \u2014 which can be influenced by temporary factors such as illness, stress, a poor night\u2019s sleep or even white coat syndrome<\/a>, where the nervousness or anxiety of being in a medical setting spikes a patient\u2019s blood pressure.\u00a0<\/p>\n Moreover, Snyder envisions a future in which physicians compare patients against their own historical baseline rather than broad population-based reference ranges. Medical textbooks and organizations such as the American Heart Association and Cleveland Clinic, for example, define a \u201cnormal\u201d resting heart rate for adults as 60 to 100<\/a> beats per minute and normal blood pressure as less than 120\/80<\/a> \u2014 thresholds derived from large populations that help identify people at increased risk of disease. <\/p>\n Data collected by wearable devices could create unique reference ranges for each patient, allowing physicians to detect meaningful departures from that person\u2019s typical patterns even when measurements remain within traditional \u201chealthy\u201d ranges. A resting heart rate of 80 beats per minute, for example, may be perfectly normal for the general population but represent a significant change for someone whose usual resting heart rate is 60.\u00a0<\/p>\n \u201cIt\u2019s the delta that counts,\u201d Snyder said. \u201cIt\u2019s the shift from your baseline.\u201d A sudden increase in resting heart rate or drop in heart-rate variability might indicate the body is under stress, he explained.<\/p>\n Snyder and other researchers have already begun testing this idea. During the COVID-19 pandemic, his team developed<\/a> a smartwatch-based alert system that continuously monitored participants\u2019 heart rate and activity levels, looking for meaningful departures from each person\u2019s baseline. When the system detected a sustained change, participants were asked what might have triggered it, such as vigorous exercise, emotional stress or illness.<\/p>\n The researchers wanted to determine whether physiological changes could serve as an early warning sign of COVID-19 infection. In many cases, it did. The system detected more than 80% of infections before or at symptom onset, with physiological changes appearing a median of three days before symptoms.<\/p>\n While Snyder\u2019s findings offer a glimpse of how continuous monitoring could help detect disease, translating the constant stream of smartwatch data into meaningful information is far more difficult than simply collecting and analyzing it.\u00a0<\/p>\n A modern wearable device records thousands of measurements every day. By themselves, most have little clinical value. Much of that information remains locked inside company-specific platforms disconnected from electronic health records or other clinical systems. Even when the data are available, few physicians have the time or desire to sift through months of heart-rate readings, sleep scores and activity logs. But researchers like Duke University\u2019s Dunn are developing digital biomarkers \u2014 models that combine many different metrics to identify people at risk for prediabetes, respiratory infections or complications following surgery.<\/p>\n Rather than presenting physicians with raw smartwatch data, Dunn envisions a standardized dashboard or report that highlights meaningful changes \u2014 much like a routine bloodwork report. The goal is not to ask clinicians to interpret thousands of data points, but to surface only the information that could change medical care.<\/p>\n Much of that work remains experimental, but Dunn said researchers are getting \u201cvery close.\u201d Even today, many wearable technology companies generate proprietary health scores \u2014 such as readiness, recovery or stress scores \u2014 that function as digital biomarkers. The difference, she said, is that companies don\u2019t always publicly report how those algorithms were developed, validated or how accurately they perform.<\/p>\n Researchers say two major hurdles remain before wearable-derived data become a routine part of healthcare: integrating them into a reactionary healthcare system currently designed to treat, rather than prevent, illness and establishing clear standards for when data or digital biomarkers are accurate and reliable enough to guide patient care.\u00a0<\/p>\n From data to better health<\/p>\n Even as smartwatches collect increasingly sophisticated health data and researchers become better at translating those measurements into meaningful insights, that information doesn\u2019t automatically translate into better health. One reason, researchers say, is that it\u2019s difficult to turn information into sustained behavior change.\u00a0<\/p>\n \u201cJust because you have a lot of information doesn\u2019t mean you\u2019re going to do something with it,\u201d John Jakicic, professor of physical activity and weight management at the University of Kansas Medical Center, said.<\/p>\n Activity trackers are built on a simple theory of behavior change: people monitor their behavior, receive feedback and adjust their actions accordingly. Someone who sees they are falling short of a daily step goal, for example, might choose to take an evening walk.<\/p>\n \u201cBut that doesn\u2019t always work,\u201d Jakicic said.<\/p>\n In one of the first large randomized clinical trials<\/a> to evaluate wearable activity trackers for weight loss, Jakicic, then at the University of Pittsburgh, and his colleagues enrolled 471 young adults in a two-year weight-loss program that required a low-calorie diet, increased physical activity and group counseling sessions. After six months, study participants were randomly assigned to different additional interventions. One group was given a wearable device to track their diet and physical activity. At the end of the study, participants using the wearable lost less weight on average than those who did not receive the device.<\/p>\n
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Guests use Ashley Borden\u2019s fitness app during the exclusive afternoon workout hosted by Ashley Borden and Reza Farahan of Shah\u2019s of Sunset for the launch of Revenge Body\u2019s Ashley Borden fitness app at Studio10 on March 29, 2018 in West Hollywood, California. Credit: Rachel Murray\/Getty Images for Ashley Borden Fitness & Lifestyle.<\/p>\n