CGM Sensors: Continuous Glucose Monitoring Guide

TL;DR: Fasting 70–90 mg/dl (3.9–5.0 mmol/l), postprandial peak below 140 mg/dl (7.8 mmol/l), Time in Range above 90 %, average glucose below 105 mg/dl. FreeStyle Libre 3 and Dexcom G7 cost 60–70 euros per sensor and run 10–14 days. A CGM shows you what HbA1c cannot — but healthy people do not need it permanently.

This article does not replace medical advice. If you regularly see glucose values below 55 mg/dl or above 180 mg/dl, consult a doctor.

What a CGM Actually Measures

A Continuous Glucose Monitor measures glucose — but not in blood. The sensor sits with a thin filament a few millimeters below the skin and measures glucose in the interstitial fluid, the space between cells. Every 1 to 5 minutes it delivers a reading. After 10 to 14 days you replace the sensor.

The difference to blood glucose is real. When your blood sugar rises quickly after a meal, glucose arrives in the interstitium with a 5 to 15 minute delay. Same in reverse when it drops. At stable values the difference is minimal, at rapid changes it matters.

Accuracy is expressed as MARD — Mean Absolute Relative Difference to lab blood glucose. FreeStyle Libre 3 and Dexcom G7 sit around 8 to 9 percent. Good enough for trends, too imprecise for insulin dosing in type 1 diabetes without fingerstick verification.

A practical example: You eat a plate of rice. Your capillary blood glucose shows 165 mg/dl at 45 minutes. Your CGM shows 148 mg/dl — and reaches 165 mg/dl only at 55 minutes. Both readings are correct. They simply measure different compartments.

Brief History: From Diabetes Tool to Biohacker Gadget

CGM was developed for type 1 diabetics. The first commercial systems (MiniMed) launched in 1999. For years they were expensive, inaccurate, and prescription-only.

The turning point came in 2014 with Abbott’s FreeStyle Libre. No fingerstick calibration, simple application, lower price. From around 2020 onwards, biohackers and health-optimizers discovered the device. Companies like Levels, Nutrisense and Veri began marketing CGM to non-diabetics — as a tool for individualized nutrition.

In 2024, Stelo (Dexcom) became the first OTC CGM in the US specifically for non-diabetics. Lingo (Abbott) followed shortly after. In Europe the rollout is slower, but Libre 3 is available via online pharmacies without prescription.

In parallel, studies like PREDICT (Zeevi 2015, Berry 2020) demonstrated that glucose responses to identical meals vary 3 to 10-fold between people. That fueled the biohacker hype further.

Device Overview: Libre, Dexcom, Stelo, Lingo, Eversense

This table compares the key devices. Prices reflect Europe / US, 2026.

Device	Wear Time	Measurement Interval	Price/Sensor	Notable Feature
FreeStyle Libre 3 (Abbott)	14 days	1 min	~60 €	Smallest form, direct-to-phone, OTC in EU
Dexcom G7	10 days	5 min	~70 €	Best accuracy (MARD ~8%), often by prescription
Eversense (Senseonics)	180 days	5 min	~1,000 €/year	Implanted, physician-only
Stelo (Dexcom, US)	15 days	15 min	~89 USD	OTC for non-diabetics
Lingo (Abbott, US)	14 days	1 min	~89 USD	OTC, biohacker audience

Without prescription in Germany: Libre 3 is the easiest route. Online pharmacies and specialty shops sell sensors to private customers. Dexcom G7 is harder but possible.

Insurance: Statutory health insurance covers CGM only with a medical indication — typically type 1 diabetes, difficult-to-manage type 2, or gestational diabetes. For biohacking, you pay yourself.

Target Ranges for Healthy Adults

Targets for non-diabetics are stricter than the official diabetes thresholds. What is acceptable for diabetics is suboptimal for healthy people.

Parameter	Target Range (healthy)	In mmol/l
Fasting glucose	70 to 90 mg/dl	3.9 to 5.0 mmol/l
Postprandial peak	below 140 mg/dl (ideal <120)	below 7.8 mmol/l
Time in Range (70–140)	above 90 %	—
24-h average	below 105 mg/dl	below 5.8 mmol/l
Glucose variability (SD)	below 15 mg/dl	below 0.8 mmol/l
Return to baseline	within 2 h	—

The shape of your glucose curve tells more than single readings. A flat curve with gentle rises and slow declines is good. Sharp spikes followed by reactive lows below 70 mg/dl are bad — even if your HbA1c is normal.

For deeper understanding of insulin-glucose dynamics, read the guide on insulin resistance and HOMA-IR.

What CGM Reveals That HbA1c Cannot

HbA1c is a 3-month average. Two people with identical HbA1c can have completely different glucose profiles. One stays flat at 100 mg/dl all day, the other oscillates between 60 and 180 mg/dl.

Individual food spikes. Rice spikes one person to 180 mg/dl, another only to 120 mg/dl. Oats react the opposite way. Without CGM you cannot tell.

Dawn phenomenon. Between 3 and 8 AM glucose often rises 10 to 30 mg/dl due to cortisol and growth hormone — without food. This is physiological but can skew your fasting readings.

Stress spikes. An important meeting without food can raise glucose by 20 to 40 mg/dl. CGM makes this visible and helps you understand the stress-metabolism link. Combined with HRV tracking the picture becomes complete.

Nocturnal patterns. Reactive nighttime hypoglycemia, dawn phenomenon, effects of late meals — all of this emerges only with CGM. Many people with poor sleep have nocturnal glucose anomalies invisible without a sensor. More on sleep data in the sleep tracking guide.

Training effects. Strength training briefly raises glucose (cortisol, glucagon). Endurance training lowers it during and for hours after. Intense HIIT sessions sometimes push glucose above 160 mg/dl post-workout — entirely normal.

Methodological Pitfalls

CGM is powerful but not perfect. Five sources of error you should know.

Compression artifacts. Sleeping on the sensor compresses interstitial fluid. The sensor then reads falsely low, often showing sudden drops below 60 mg/dl. If you wake up symptom-free, it was not a real low. Fix: sensor on non-dominant arm or change sleep position.

Blood-to-interstitium lag. 5 to 15 minutes delay, particularly during rapid changes. If you try to verify a spike by fingerstick, the CGM reading may be lower — simply because it lags.

Sensor drift. The first 24 hours after insertion are unstable, often running low. The last 24 hours before sensor end become inaccurate too. Fingerstick verification makes sense during onboarding.

Calibration. Libre and Dexcom G7 are factory-calibrated, no manual calibration needed. At values that feel wrong (e.g., 180 mg/dl without a meal), a fingerstick clarifies.

Meal context. What you ate before influences the next meal. An isolated “rice test” right after waking shows different values than rice after a workout or after a stressful day. Standardize your tests.

For wearable data quality in general, read the guide on wearable data quality.

N=1 Experiments: What You Learn in 2 Weeks

A CGM delivers best as a time-limited experiment. 2 to 4 weeks, concrete questions, documented results. The most valuable tests:

Food comparison. On different days, eat the same amount of rice, oats, sweet potato and quinoa — each for breakfast, fasted, no additions. Compare peak and AUC (Area Under the Curve) of the following 2 hours. You often find surprising differences.

Meal order. Day 1: 100 g rice first, then chicken and vegetables. Day 2: chicken and vegetables first, then rice. The peak in the meal-order test is often 30 to 50 mg/dl lower when protein and fiber come first.

Post-meal walk. Day 1: sit after eating. Day 2: 15 minutes of walking. The peak drops by 30 to 50 mg/dl in most people. One of the most reliable CGM effects.

Apple cider vinegar test. 1 to 2 tablespoons in 200 ml water, 10 minutes before a carb-heavy meal. Studies show a peak reduction of about 20 percent. Does it work for you?

Cinnamon, berberine, metformin. Cinnamon (1 to 3 g Ceylon cinnamon) has weak evidence. Berberine (500 mg before meals) measurably lowers glucose — but CGM shows you how much. Metformin reduces fasting glucose by 10 to 20 mg/dl, prescription only.

Document every experiment: timing, portion, previous meal, sleep, training. Without context, CGM data is noise.

Critical Perspective: Do You Actually Need This?

The uncomfortable truth: most healthy people do not need continuous CGM. Four reasons for restraint.

Cost. 60 to 70 euros per sensor, 4 sensors every 2 months — that is 120 to 150 euros per month without indication. At 1,500 to 1,800 euros per year, asking about benefit is fair.

Pathologizing normal spikes. A peak at 140 mg/dl after pasta is not a disease. Non-diabetics are allowed to spike postprandially. Obsessive optimization of every single meal peak can do more harm than good, especially when it leads to restrictive eating.

Orthorexia glucosa. A new phenomenon: people develop compulsive behavior around their glucose curve. No more bread, only salads, fear of fruit. This is not biohacking. It is an eating disorder dressed in tracking.

Weak evidence in healthy people. Randomized trials of CGM in non-diabetics show short-term mild behavioral changes but no robust long-term effects on HbA1c, weight or cardiovascular markers. The biggest benefit lies in the learning curve during the first 4 to 8 weeks.

Smarter strategy: 1 to 2 sensors per year, 4 weeks of intensive experimentation, then pause. If you have insulin resistance risk (abdominal fat, family history, elevated HbA1c), measure more often. If you are metabolically healthy, an HbA1c every 12 to 24 months suffices.

Integration Into Lab2go

CGM data unfolds its value only in long-term comparison. Export your Libre or Dexcom data as CSV and import into Lab2go. There you correlate glucose with other signals.

Average glucose vs. HbA1c. A CGM average of 100 mg/dl corresponds to an HbA1c around 5.1 %. Does your HbA1c lab value fit? Deviations suggest high variability or lab error.

Glucose vs. sleep. Nights below 6 hours of sleep raise glucose response the next day by 20 to 40 percent. Your CGM shows it, your sleep tracker confirms the cause.

Glucose vs. training. Endurance sessions lower glucose for 24 to 48 hours. Weeks with little training show higher averages. Visible in trend, not single readings.

Glucose vs. weight. A 5 percent weight reduction often lowers average glucose by 8 to 15 mg/dl in overweight individuals. You document the effect in the Lab2go dashboard. The features show all tracking options.

For the methodology of long-term tracking, read the guide on long-term biomarker tracking.

Bottom Line: CGM as a Time-Limited Learning Tool

CGM is not the new mandatory metric for every healthy person. It is a powerful learning tool — best used as a 2 to 4 week experiment, not permanent therapy.

Three steps to get started:

1. Define your question. What do you want to learn? Meal responses? Sleep effects? Stress signature? Without a question, CGM is noise.
2. Buy a sensor. Libre 3 via online pharmacy, about 60 euros. Wear for 2 weeks, document systematically.
3. Analyze and stop. Draw conclusions, adjust nutrition and timing, then stop measuring. A year later you can verify with a new sensor whether the changes hold.

Start with the biomarker baseline and compare CGM results to your HOMA-IR. For platform integration, check the features or compare the pricing.

This article does not replace medical advice. If you repeatedly see values below 55 mg/dl or above 180 mg/dl two hours after meals, consult a doctor. CGM complements clinical diagnostics — it does not replace them.