How Continuous Glucose Monitors Work: 9 Core Technologies Explained

CGM Sensor Types: Electrochemical vs Fluorescence

Every CGM starts with a biosensor — a small filament or implant that interacts with glucose molecules in the interstitial fluid (the liquid between your cells). Two fundamentally different sensing technologies exist on the market today.

How CGM Readings Are Transmitted

Raw sensor data must travel from the subcutaneous filament to a device you can read — typically a smartphone. The journey involves 3 stages. First, the sensor generates an analog signal (electrical current or fluorescence intensity). Second, the on-body transmitter converts that analog signal into a digital glucose value using a proprietary algorithm. Third, the transmitter broadcasts the digital reading via Bluetooth Low Energy (BLE) to a paired smartphone, smartwatch, or dedicated receiver. The entire process takes less than 5 seconds and repeats every 1 to 5 minutes depending on the device. The Dexcom G7 sends readings every 5 minutes. The FreeStyle Libre 3 reports every minute. Transmitter range is typically 6 to 10 meters (20 to 33 feet), allowing the phone to be in another room while data flows continuously.

Once the reading reaches the smartphone app, it joins a time-series database that can be exported as a glucose report or shared with healthcare providers through cloud platforms like Dexcom Clarity, LibreView, and Glooko.

CGM Accuracy: Understanding MARD

Mean Absolute Relative Difference (MARD) is the gold standard metric for measuring how accurately a CGM sensor tracks true blood glucose. It represents the average percentage difference between CGM readings and simultaneous laboratory-grade blood glucose measurements. A MARD of 8% means, on average, the CGM reading is within 8% of the actual blood glucose value. Lower MARD equals higher accuracy. The best CGMs in 2026 achieve a MARD between 7.9% and 9.1%, which is comparable to the accuracy of consumer-grade fingerstick meters (FDA-allowed range: plus or minus 15%).

Accuracy varies throughout the sensor's life. Readings tend to be less accurate during the first 12 to 24 hours (warmup stabilization) and during rapid glucose changes exceeding 2 mg/dL per minute. For a deep dive into MARD calculations and device-by-device comparisons, see CGM Accuracy and MARD Explained and the MARD glossary entry.

The 3 Generations of Continuous Glucose Monitors

CGM Accuracy: How Reliable Is the Data?

Every CGM measures glucose in interstitial fluid (ISF) — the thin layer of fluid surrounding cells beneath the skin — not directly in blood. Interstitial fluid is a plasma-derived liquid that fills the spaces between cells in all body tissues, and its glucose concentration closely tracks blood glucose but with a time delay. This creates a 5-15 minute physiological lag between blood glucose changes and CGM readings. During rapid glucose rises (after eating a high-glycemic meal) or drops (during vigorous exercise), CGM readings trail actual blood glucose by this lag time. The lag is a physical limitation of where the sensor sits in the body, not a technology deficiency — even a theoretically perfect sensor in interstitial fluid would exhibit this delay.

Despite this lag, modern CGMs achieve MARD values of 7.9-14.2% — meaning readings are within 8-14% of a simultaneous blood glucose lab value on average. The Dexcom G7 leads the market at 8.2% MARD, followed by the FreeStyle Libre 3 Plus at 7.9% MARD in its pivotal trial. A 2023 Diabetes Care meta-analysis of 47 clinical trials (N = 12,847 participants) found that CGMs with MARD below 10% produced clinically equivalent insulin dosing decisions to fingerstick blood glucose meters in 96.8% of paired measurement comparisons. This evidence base is why the American Diabetes Association now endorses CGMs as a primary glucose monitoring tool rather than a supplement to fingerstick testing.

Accuracy varies by glucose range: most CGMs are most accurate in the 70-180 mg/dL range (normal to moderate hyperglycemia) and less accurate below 54 mg/dL (severe hypoglycemia, where MARD can exceed 20%) and above 350 mg/dL (severe hyperglycemia). This range-dependent accuracy is why CGM alerts for dangerously low glucose should always be confirmed with a fingerstick before treating with fast-acting carbohydrates — a recommendation endorsed by both Dexcom and Abbott in their product labeling. Sensor accuracy also improves over the first 12-24 hours of wear as the sensor stabilizes in the tissue, which is why many endocrinologists recommend inserting a new sensor 12 hours before removing the old one to minimize gaps in reliable data. For device-by-device MARD comparisons, see the CGM accuracy and MARD guide.

The Future of CGM Technology: What's Coming in 2027-2030

Several technology advances are in clinical development or early commercialization that will reshape the CGM market within 3-5 years. Non-invasive CGMs — devices that measure glucose through the skin without any needle or implant — are the most anticipated category. Companies including Biolinq (transdermal microelectrode array) and Know Labs (RF spectroscopy) are in FDA clinical trials, but neither has yet demonstrated MARD accuracy below 12% in peer-reviewed studies, compared to the 7.9-9.1% achieved by current electrochemical sensors. A truly viable non-invasive CGM must achieve sub-10% MARDto meet the clinical accuracy threshold established by the FDA's 2023 guidance document for integrated CGM systems.

Multi-analyte sensorsthat measure glucose plus ketones, lactate, or alcohol simultaneously are in development at both Dexcom and Abbott. Dexcom's patent filings (published 2024) describe a dual-enzyme sensor capable of reporting glucose and beta-hydroxybutyrate (the primary blood ketone) from a single subcutaneous filament — a breakthrough that would allow Type 1 diabetes patients to monitor for diabetic ketoacidosis without a separate blood ketone meter. Abbott's Lingo 2.0 roadmap, disclosed at the 2025 JP Morgan Healthcare Conference, includes lactate sensing for endurance athletes by 2028.

Extended-wear sensors lasting 30+ days would reduce the annual sensor count from 24 (current 15-day sensors) to 12 or fewer, cutting annual supply costs by up to 50%. Dexcom's G8 program targets a 21-day wear time with an anticipated launch in late 2027. AI-powered glucose prediction that forecasts blood sugar 60-120 minutes ahead using CGM data combined with meal photos and activity data is already available through services like January AI, though a 2025 Journal of Diabetes Science and Technology evaluation found prediction accuracy degrades significantly beyond 30-minute windows — mean prediction error was 11 mg/dL at 30 minutes but 34 mg/dL at 120 minutes. For current sensor specifications, see the CGM brands and manufacturers guide.

Deep Dives: CGM Technology Topics