Features

AFib Detection

Detects irregular heart rhythms indicative of atrial fibrillation

AGEs Index

Blood Oxygen Monitoring

Measures peripheral oxygen saturation (SpO2)

Blood Pressure Monitoring

Measures systolic and diastolic blood pressure

Body Composition

ECG/EKG

Records electrical activity of the heart via electrocardiogram

Energy Score

Health Monitor

Healthspan

Healthspan Tracking

Heart Rate

HRV Tracking

Recovery Score

Respiratory Rate Tracking

Monitors breathing rate throughout day and night

Sleep Apnea Detection

Identifies potential sleep apnea events during sleep

Temperature Sensing

Continuous skin temperature monitoring

Vitals App

Crash Detection

Detects car crashes and can automatically call emergency services

Emergency SOS

Quickly contact emergency services with location sharing

Fall Detection

Automatically detects hard falls and can alert emergency contacts

Heart Rate Alerts

Notifications for unusually high or low heart rate

Irregular Rhythm Alerts

Notifications when irregular heart rhythms are detected

Activity Score

Auto Workout Detection

Automatically recognizes and records exercise activities

Automatic Activity Detection

Depth Tracking

GPS Tracking

Track outdoor activities with satellite positioning

Multi-band GPS

Enhanced GPS accuracy using multiple satellite frequencies

Muscular Strain

Running Power

Measures running efficiency in watts

Snorkeling Mode

Step Tracking

Strain Score

Strain Tracking

Swim Tracking

Track pool and open water swimming with stroke detection

Training Load

Tracks cumulative training stress and recovery needs

VO2 Max Estimation

Estimates maximum oxygen uptake during exercise

Water Temperature

Workout Heart Rate

Bluetooth Music

Play music to wireless headphones

LTE Cellular

Make calls and use data without phone nearby

NFC Payments

Contactless payments via Apple Pay, Google Pay, etc.

Offline Music Storage

Store music directly on device for phone-free listening

Wi-Fi

Connect to wireless networks

Always-On Display

Screen remains visible without raising wrist

Double Pinch Gesture

Double Tap Gesture

Find My Ring

Gesture Control

Gesture Controls

Journal

Touch Screen

Interactive touch display

Voice Assistant

Control device with voice commands

WHOOP Coach

Blood Glucose Monitoring

Continuous measurement and tracking of blood glucose levels, essential for diabetes management and metabolic health optimization. Continuous glucose monitors (CGMs) provide readings every 1-5 minutes, revealing glucose patterns invisible to periodic fingerstick testing—including nocturnal hypoglycemia, postprandial spikes, and dawn phenomenon. Users can set customizable high/low alerts to prevent dangerous glucose excursions. Time-in-range metrics (typically 70-180 mg/dL for diabetics) provide more actionable feedback than single-point measurements or HbA1c alone. For people with diabetes, CGM use is associated with improved glycemic control (0.5-1% HbA1c reduction) and reduced hypoglycemia. Emerging applications for non-diabetics include metabolic health optimization, understanding individual food responses, and athletic performance fueling. CGM devices are FDA-regulated Class II medical devices; accuracy is measured by Mean Absolute Relative Difference (MARD), with current systems achieving 9-11%.

Blood Oxygen Monitoring

Monitoring of peripheral blood oxygen saturation (SpO2), measuring the percentage of hemoglobin carrying oxygen. Normal SpO2 ranges from 95-100% at sea level; values below 90% indicate hypoxemia requiring medical attention. Wearables offer either continuous background monitoring or on-demand spot checks. Continuous overnight SpO2 monitoring can screen for sleep-disordered breathing patterns suggestive of sleep apnea—characterized by repetitive oxygen desaturation events. SpO2 tracking gained prominence during COVID-19 as respiratory deterioration indicator. Accuracy limitations exist: wearable SpO2 is less accurate than medical pulse oximeters, particularly at lower saturation levels, in users with darker skin pigmentation, during motion, or with poor peripheral perfusion. Most wearable SpO2 features are classified as wellness tools rather than medical devices and should not replace clinical pulse oximetry for medical decisions. Persistent low readings warrant professional evaluation.

Blood Pressure Monitoring

Non-invasive measurement of systolic and diastolic blood pressure without traditional arm cuffs. Hypertension (≥130/80 mmHg) affects nearly half of US adults and is a leading modifiable risk factor for cardiovascular disease, stroke, and kidney disease. Traditional monitoring requires arm cuff devices, limiting measurement frequency. Wearable BP monitoring enables more frequent tracking to detect white-coat hypertension, masked hypertension, and circadian BP patterns. Technologies include oscillometric wrist cuffs, pulse transit time (PTT) analysis, and PPG waveform analysis. FDA-cleared wearable BP monitors must meet ANSI/AAMI/ISO 81060-2 accuracy standards (±5 mmHg mean error, ±8 mmHg standard deviation). Wearable measurements can be affected by wrist position, cuff placement, and motion; periodic validation against calibrated arm cuff devices is recommended. BP trends over time may be more valuable than individual readings for clinical decision-making.

Double Tap

ECG Recording

On-demand recording of single-lead electrocardiogram (ECG) tracings that can be shared with healthcare providers. Users typically initiate a 30-second recording by touching electrodes, generating a Lead I equivalent ECG showing P waves, QRS complexes, and T waves. This provides more diagnostic information than heart rate alone, enabling detection of AFib, other arrhythmias, and certain conduction abnormalities. FDA-cleared ECG features classify rhythms as sinus rhythm, AFib, or inconclusive. ECG recordings can capture symptomatic episodes (palpitations, dizziness) that might not occur during a clinical visit, providing valuable diagnostic information for physicians. Single-lead wearable ECG cannot detect all conditions visible on 12-lead clinical ECG, including most heart attacks, many conduction blocks, and chamber enlargement. Signal quality depends on electrode contact and user stillness. Exported PDFs typically include rhythm classification, heart rate, and the full waveform tracing.

Heart Rate Zones

Training intensity guidance based on real-time heart rate relative to personalized heart rate zones. Zones are typically defined as percentages of maximum heart rate (HRmax) or heart rate reserve (HRR = HRmax - resting HR). Common five-zone models include: Zone 1 (50-60% HRmax) for recovery, Zone 2 (60-70%) for base aerobic training, Zone 3 (70-80%) for aerobic capacity, Zone 4 (80-90%) for lactate threshold, and Zone 5 (90-100%) for VO2max intervals. Training in appropriate zones optimizes physiological adaptations: Zone 2 builds mitochondrial density and fat oxidation, while Zone 4-5 improves lactate clearance and VO2max. Wearables can auto-detect HRmax from workout data or use age-based estimates (220-age), though individual variation is significant. Zone alerts help maintain target intensity during workouts. Time-in-zone analysis reveals training distribution, supporting polarized training approaches (80% easy, 20% hard) recommended by exercise physiologists.

Irregular Rhythm Notification

Passive background monitoring that alerts users to irregular heart rhythm patterns beyond atrial fibrillation. Using continuous PPG or periodic ECG sampling, algorithms detect rhythm irregularities including frequent premature atrial contractions (PACs), premature ventricular contractions (PVCs), and other arrhythmias. Irregular rhythm notifications differ from AFib detection in detecting broader abnormality categories without specific diagnosis. Occasional irregular beats are normal and increase with age, caffeine, stress, and dehydration; notifications indicate patterns exceeding normal thresholds. FDA-cleared irregular rhythm features must demonstrate appropriate sensitivity and specificity to avoid excessive false alarms while catching clinically significant arrhythmias. Users receiving notifications should consult healthcare providers for proper evaluation, which may include Holter monitoring or event recorders. These notifications have identified previously undiagnosed arrhythmias leading to appropriate treatment, though they can also cause anxiety from benign findings.

Meditation Tracking

Guided meditation and mindfulness sessions with real-time biofeedback from physiological sensors. Sessions typically guide users through breathing exercises, body scans, or focused attention practices while monitoring heart rate, HRV, and sometimes EDA (skin conductance) to assess relaxation response. Biofeedback visualizations show users when they achieve calm states, reinforcing effective techniques. HRV-based metrics indicate parasympathetic activation—increased HRV during meditation suggests successful stress reduction. Breathing guidance helps users achieve coherent breathing patterns (typically 5-7 breaths per minute) that optimize HRV and activate the relaxation response. Session libraries range from 1-minute breathing exercises to 30+ minute guided meditations. Progress tracking shows meditation frequency, duration streaks, and physiological improvements over time. Research supports meditation's benefits for stress reduction, anxiety, blood pressure, and cognitive function. Integration with daily readiness scores helps users understand meditation's cumulative impact on overall wellbeing.

Menstrual Tracking

Tracking of menstrual cycles, fertility windows, and related symptoms using logged data and physiological measurements. Users log period start/end dates, flow intensity, and symptoms (cramps, mood, energy); algorithms predict future periods and fertile windows based on cycle history. Advanced tracking incorporates basal body temperature (BBT)—skin temperature rises ~0.3°C after ovulation due to progesterone—enabling more accurate ovulation detection than calendar methods alone. Some devices detect the luteinizing hormone (LH) surge preceding ovulation. Cycle tracking helps users understand patterns affecting energy, sleep, and athletic performance throughout the month. For fertility planning, combining multiple indicators (temperature, cervical mucus, LH) improves accuracy over single-method tracking. Cycle irregularities may indicate conditions warranting medical evaluation (PCOS, thyroid disorders). Privacy considerations are significant given sensitive health data; users should understand data storage and sharing policies. Cycle predictions improve with more logged cycles, typically requiring 3+ months of data.

Music Storage

Readiness Score

Daily composite score indicating physiological readiness for physical and mental exertion, guiding training and recovery decisions. Readiness algorithms integrate multiple overnight biomarkers: heart rate variability (higher HRV = better recovery), resting heart rate (lower = better recovered), sleep quality and duration, respiratory rate, body temperature deviation, and previous day's activity load. Scores are typically personalized to individual baselines established over 1-2 weeks of consistent wear. High readiness suggests the autonomic nervous system is recovered and prepared for intense training; low readiness indicates accumulated fatigue or stressors requiring rest or light activity. Readiness scores support periodized training by identifying optimal days for hard workouts versus recovery. Factors beyond exercise affecting readiness include alcohol, illness, travel, psychological stress, and sleep quality. Some platforms provide activity recommendations based on readiness. While readiness scores synthesize complex physiology into actionable guidance, they remain estimates—users should integrate readiness data with subjective feelings and training goals.

Sleep Staging

Classification of sleep into distinct stages—typically Wake, Light (N1/N2), Deep (N3/slow-wave), and REM—based on physiological signals during sleep. Clinical polysomnography (PSG) uses EEG, EOG, and EMG to stage sleep; wearables approximate staging using heart rate patterns, HRV, movement, and sometimes respiratory rate and SpO2. Each stage serves distinct functions: light sleep facilitates memory consolidation and transition, deep sleep enables physical restoration, hormone release (growth hormone), and immune function, while REM supports cognitive processing, emotional regulation, and memory integration. Healthy adults typically experience 4-6 sleep cycles nightly, with deep sleep concentrated early and REM increasing toward morning. Wearable staging accuracy varies significantly compared to PSG gold standard—deep sleep detection is particularly challenging—but relative trends and patterns provide useful insights. Sleep staging helps users understand sleep architecture, identify factors affecting specific stages (alcohol reduces REM, late exercise may reduce deep sleep), and optimize sleep quality beyond simple duration.

Sleep Tracking

Automatic detection and analysis of sleep periods, tracking duration, timing, and quality metrics. Sleep tracking typically uses accelerometer-based movement detection combined with heart rate patterns to identify sleep onset and wake times, eliminating manual logging. Key metrics include total sleep time, time in bed, sleep efficiency (time asleep / time in bed), sleep latency (time to fall asleep), and wake episodes. Many devices calculate composite sleep scores integrating multiple factors. Consistent sleep timing (low variability in bedtime and wake time) is associated with better health outcomes independent of duration. The circadian alignment of sleep—sleeping during biological night—affects sleep quality and metabolic health. Sleep debt from chronic insufficient sleep accumulates and requires multiple recovery nights to resolve. Wearables help users understand sleep patterns, identify improvement opportunities (earlier bedtime, reduced evening screen time, consistent schedule), and correlate sleep with next-day energy and performance. Accuracy for total sleep time is generally within 30 minutes of PSG; efficiency and wake detection are less accurate.

Temperature Tracking

Continuous monitoring of skin or core body temperature trends for health insights, fever detection, illness prediction, and menstrual cycle tracking. Skin temperature measured at the wrist or finger runs 3-4°C below core temperature and varies with ambient conditions, blood flow, and circadian rhythm. Wearables establish personalized baselines and detect meaningful deviations. Elevated nocturnal temperature often precedes symptom onset in respiratory infections by 1-2 days, enabling early illness detection. In menstrual tracking, basal body temperature rises approximately 0.3°C (0.5°F) after ovulation due to progesterone, remaining elevated until the next period—this thermal shift confirms ovulation occurred. Temperature also reflects circadian rhythm health, with normal nighttime drops supporting sleep quality. Athletes use temperature trends to monitor training load and recovery status. Factors affecting readings include alcohol (raises temperature), room temperature, blankets, and device positioning. Some devices measure continuous temperature; others sample periodically. Temperature tracking has expanded following COVID-19 awareness of fever as an early symptom indicator.

VO2 Max Estimation

Estimation of maximal oxygen uptake (VO2max), the gold-standard measure of cardiorespiratory fitness and a powerful predictor of longevity. VO2max represents the maximum rate at which the body can consume oxygen during intense exercise, measured in mL/kg/min. Laboratory VO2max testing requires graded exercise to exhaustion with respiratory gas analysis; wearables estimate VO2max using submaximal data—typically heart rate response during walking or running at known speeds (via GPS). The relationship between heart rate, pace, and oxygen consumption allows algorithmic estimation without maximal exertion. Population averages range from 35-40 mL/kg/min for sedentary adults to 70+ for elite endurance athletes. VO2max declines approximately 10% per decade after age 30 but responds well to training at any age. Higher VO2max is associated with reduced cardiovascular mortality, improved metabolic health, and better cognitive function. Wearable estimates typically correlate 0.8-0.9 with laboratory values but absolute accuracy varies. Tracking VO2max trends over months reveals fitness trajectory more reliably than individual readings.

Workout Tracking

Automatic and manual tracking of exercise sessions with activity-specific metrics, duration, intensity, and caloric expenditure. Auto-detection algorithms recognize common activities (walking, running, cycling, swimming) from movement patterns without user initiation, ensuring workouts are captured even when users forget to start tracking. Manual workout modes provide activity-specific interfaces and metrics: running shows pace, cadence, and ground contact time; cycling displays speed, power (with sensors), and elevation; swimming counts laps, strokes, and identifies stroke type; strength training logs sets, reps, and exercises. Heart rate integration enables intensity analysis, training load calculation, and accurate calorie estimation based on physiological effort rather than motion alone. Workout history reveals training patterns, progressive overload, and recovery needs. Many platforms provide structured workout guidance, training plans, and competitive features (segments, challenges). GPS-enabled activities include route mapping and environmental data (elevation, weather). Post-workout analysis includes performance metrics, comparisons to previous sessions, and recovery recommendations based on accumulated training load and current fitness level.