A Fitbit is essentially a small bundle of sensors strapped to your wrist, continuously collecting data about your body and movement. It uses an accelerometer to detect motion, LEDs to monitor your heart rate through your skin, and algorithms that translate all of this raw data into the steps, calories, sleep stages, and health metrics you see in the app. Here’s what’s actually happening inside the device.
How Step and Motion Tracking Works
Every Fitbit contains a three-axis accelerometer, a tiny chip that detects movement in three dimensions. When you walk, the accelerometer picks up the rhythmic back-and-forth motion of your wrist and identifies it as steps. The device’s software filters out random arm movements (like gesturing during a conversation) by looking for patterns that match a walking or running gait. Most Fitbits also include an altimeter that measures changes in air pressure, which is how the device knows when you’ve climbed stairs.
For distance tracking, Fitbit multiplies your step count by your estimated stride length, which it calculates from your height. Some models include built-in GPS, which maps your actual route during outdoor workouts and gives more precise distance and pace data. Other models use “connected GPS,” meaning they borrow your phone’s GPS signal over Bluetooth. Built-in GPS is more accurate but drains the watch battery significantly faster, so some users switch to connected mode for longer runs.
Heart Rate Monitoring With Light
The green LEDs on the back of your Fitbit flash hundreds of times per second against your skin. This technique, called photoplethysmography, works because blood absorbs green light. Each time your heart beats, blood pulses through the capillaries in your wrist, absorbing more light. Between beats, less light is absorbed. A photodetector next to the LEDs measures how much light bounces back, and the device calculates your heart rate from these fluctuations.
When compared against medical-grade ECGs, Fitbit heart rate readings show an overall mean absolute percentage error of about 7%, which falls within the accepted accuracy threshold of 10%. Accuracy is highest during relaxation (around 6% error) and drops slightly during periods of psychological stress or anticipation (closer to 10% error). Tight wrist placement matters here. A loose band lets ambient light leak in and disrupts the readings.
How Calories Are Calculated
Your Fitbit doesn’t directly measure calories. Instead, it estimates them by combining two things: your basal metabolic rate and your activity data. Your BMR, the energy your body burns just to keep you alive (breathing, circulating blood, maintaining body temperature), accounts for at least half of the calories you burn each day. Fitbit calculates this from the height, weight, age, and sex you entered in your profile.
On top of that baseline, the device layers in movement data from the accelerometer and, on heart-rate-enabled models, your pulse during exercise. Heart rate data is especially useful for activities like cycling, yoga, or weight training where your step count alone wouldn’t reflect how hard you’re working. The combination of resting metabolism plus real-time effort data gives you the total calorie estimate that updates throughout the day on your dashboard.
Sleep Stage Detection
Fitbit tracks sleep using two inputs: wrist movement and heart rate variability. While you sleep, your heart rate doesn’t stay perfectly steady. The tiny variations between each beat shift in characteristic ways depending on your sleep stage. During deep sleep, your heart rate variability follows a different pattern than during REM sleep or light sleep. The device’s algorithm combines these cardiac patterns with how much you’re moving (or not moving) to estimate how long you spent in each stage and how many times you woke up.
Compared to polysomnography, the gold-standard sleep test used in clinical labs, Fitbit devices correctly identify sleep epochs over 91% of the time. The catch is specificity: Fitbits are much better at detecting when you’re asleep than when you’re awake. Specificity for detecting wake periods sits around 47 to 49%, meaning the device misses roughly half of your brief awakenings and logs them as sleep instead. Overall agreement between Fitbit and clinical polysomnography is moderate, so the sleep stage breakdowns are useful for spotting trends over weeks and months rather than treating any single night’s data as precise.
Blood Oxygen Sensing
Some Fitbit models measure blood oxygen saturation (SpO2) while you sleep using a different set of LEDs from the ones that track heart rate. These sensors shine red and infrared light onto your skin. Oxygen-rich blood reflects more red light than infrared, while oxygen-poor blood reflects more infrared light than red. By comparing the ratio of reflected red to infrared light, the device estimates how saturated your blood is with oxygen.
This measurement runs overnight rather than continuously because it requires the device to be still against your skin for consistent readings. The data shows up as an average and a range on your morning dashboard. Consistently low readings (well below 95%) can be a signal of breathing disruptions during sleep, though Fitbit is not a medical device and doesn’t diagnose conditions.
Stress and Skin Conductance
Select Fitbit models (like the Sense line) include an electrodermal activity sensor that measures tiny changes in how well your skin conducts electricity. When your nervous system ramps up, even slightly, your sweat glands activate at a microscopic level. This changes your skin’s electrical conductance. The sensor on the back of the device picks up these shifts and uses them as an indicator of sympathetic nervous system arousal, which correlates with stress.
The sensor measures impedance on the wrist through a dry electrode, so it works passively throughout the day. One limitation: because it’s measuring conductance, water on your skin (from washing hands or sweating heavily during a workout) can produce artificially high readings. The stress score you see in the app also factors in heart rate variability and exertion level, not just skin conductance alone.
How Data Gets to Your Phone
Your Fitbit stores data locally on the device and syncs it to the Fitbit app over Bluetooth Low Energy, a power-efficient wireless protocol. Syncing happens automatically throughout the day whenever your phone is nearby, and it also triggers each time you open the app. From your phone, the data uploads to Fitbit’s cloud servers, which is where the app generates your trends, graphs, and historical comparisons.
Because the device stores data onboard, you don’t lose your steps or heart rate readings if your phone is out of range for a while. Most Fitbits can hold several days’ worth of detailed data (and up to 30 days of daily summaries) before they need to sync. This local storage is also why your stats sometimes appear to “jump” when you open the app after a gap: the device is uploading everything it collected in the meantime.
What Ties It All Together
The hardware inside a Fitbit is relatively simple: an accelerometer, optical heart rate LEDs, and on some models, GPS, SpO2 sensors, and an EDA sensor. What makes the device useful is the software layer that interprets all of these signals together. A single set of heart rate data feeds into your calorie estimates, sleep staging, cardio fitness score, and stress tracking simultaneously. The accelerometer data shapes your step count, distance, active minutes, and sleep detection. Each metric you see in the app is a software interpretation of overlapping sensor data rather than a standalone measurement, which is why wearing the device consistently and keeping your profile information accurate makes everything more reliable over time.