The Healthcare Shift No One Can Ignore

The future of healthcare is no longer happening inside the clinic, it’s happening between visits. Wearables are producing a new class of real-time, continuous patient-generated health data (PGHD), data that was never available through traditional health systems.

According to McKinsey, up to $265B in U.S. care services could shift to digital and at-home models by 2030, with Remote Patient Monitoring (RPM) as a primary driver of that transformation. And yet, most hospitals still struggle to unlock real clinical value from wearable data.

This article breaks down exactly what wearables can capture, why this data matters, and how the next generation of AI-driven platforms like Health Studio are translating data into action, not noise.

What Data Can Wearables Capture Today?

Modern wearables have evolved significantly, now offering a comprehensive array of data points that extend far beyond basic steps and heart rate. Leading devices such as Fitbit, Garmin, Whoop, Oura, and Withings are at the forefront of this revolution, providing detailed insights that are becoming increasingly critical for remote patient monitoring (RPM) and population health management.

Here's an expanded look at the types of data these advanced wearables can track:



Activity and Movement

• Steps and Distance: The foundational metrics, still crucial for understanding general activity levels.
• Calories Burned: Estimated based on activity, heart rate, and personal biometrics.
• Active Minutes/Intensity: Tracking periods of moderate to vigorous physical activity.
• Floors Climbed: Utilizing altimeters to measure vertical movement.
• Activity Recognition: Automatically identifying specific activities like walking, running, swimming, or cycling.
• Workout Tracking: Detailed metrics for specific exercise types, including pace, routes (via GPS), and more.

Heart Health

• Heart Rate (HR): Real-time and continuous monitoring of beats per minute.
• Resting Heart Rate (RHR): A key indicator of cardiovascular fitness and overall health.
• Heart Rate Variability (HRV): Measuring the variation in time between heartbeats, reflecting autonomic nervous system activity and stress levels.
• ECG/EKG (Electrocardiogram): Some devices can capture single-lead ECGs to detect signs of atrial fibrillation (AFib) or other heart rhythm irregularities.
• Oxygen Saturation (SpO2): Measuring blood oxygen levels, important for respiratory health and sleep apnea detection.

Sleep Tracking

• Sleep Stages: Differentiating between awake, REM, light, and deep sleep cycles.
• Sleep Duration: Total time spent asleep.
• Sleep Quality Score: An overall assessment based on various metrics.
• Sleep Disturbances: Identifying restless periods, awakenings, and potential breathing irregularities.
• Wake-up Times: Analyzing consistency and patterns.

Stress and Recovery

• Stress Levels: Often derived from HRV and heart rate patterns, providing insights into physiological stress.
• Recovery Metrics: Assessing how well the body is recovering from physical and mental exertion.
• Body Battery/Energy Levels: Proprietary metrics that estimate available energy throughout the day.

Temperature

• Skin Temperature: While not a precise core body temperature, changes in skin temperature can indicate fever, illness, or menstrual cycle phases.

Other Biometric Data (Emerging/Advanced)

• Blood Pressure (Emerging): Some newer devices are beginning to offer cuff-less blood pressure monitoring, though accuracy is still evolving.
• Glucose Monitoring (Future): Non-invasive glucose tracking is a major area of research and development for future wearables.

The ability to continuously and passively collect such a rich dataset empowers healthcare providers with unprecedented insights into their patients' daily lives and physiological responses. This data is instrumental in:

• Remote Patient Monitoring (RPM): Allowing healthcare professionals to track vital signs and other health metrics from a distance, enabling early intervention and personalized care for chronic conditions.
• Population Health: Aggregating data across large groups to identify health trends, manage disease outbreaks, and design more effective public health interventions.
• Personalized Health Insights: Empowering individuals to better understand their own bodies, make informed lifestyle choices, and proactively manage their well-being.

As wearable technology continues to advance, the scope and accuracy of the data they capture will only expand, further cementing their role as indispensable tools in both individual health management and the broader healthcare ecosystem.