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Calcimator

Body Temperature Monitoring Calculator

Estimate wrist skin temperature from core temp, ambient conditions, activity, circadian rhythm, and menstrual cycle phase. Includes fever detection threshold analysis.

Inputs

Results

Estimated skin temp (C)

33.7

Deviation from baseline (C)

0

Estimated skin temp (F)92.7
Baseline skin temp (C)33.7
Fever likely (0/1)0
Fever detection confidence (%)99
Normal range low (C)33
Normal range high (C)34.4
Core Temp F98.6
How to Use This Calculator
  1. Enter your wearable-measured core body temperature (°C) and the current ambient temperature.
  2. Set your sensor accuracy rating (°C) — consumer wearables are typically ±0.2 °C.
  3. Select your current activity level and minutes since last exercise session.
  4. Enter the current hour of day (0–23) and menstrual cycle phase if applicable.
  5. Review the estimated skin temperature, deviation from baseline, and fever-likelihood confidence score.

How the result changes with Core body temp (C)

Core body temp (C)Estimated skin temp (C)Deviation from baseline (C)
3632.7-1
3733.70
4036.73
4137.74

What each input means

Core body temp (C)
Core body temperature in Celsius. Normal is ~37.0C (98.6F).
Ambient temperature (C)
Room or outdoor temperature. Affects vasoconstriction and skin-core offset.
Sensor accuracy (degC)
Wearable thermistor accuracy. Consumer: ~0.2C, medical: ~0.1C.
Current activity level
Select the current activity level
Minutes since exercise
Minutes since last exercise session ended (affects residual heat).
Time of day (hour, 0-23)
Current hour of day. Body temp has a circadian cycle (lowest ~4 AM, highest ~6 PM).
Menstrual cycle phase
Select the menstrual cycle phase

What each result means

Estimated skin temp (C)
Predicted wrist skin temperature based on all factors.
Estimated skin temp (F)
Same estimate in Fahrenheit.
Baseline skin temp (C)
Expected healthy baseline skin temp at this time of day.
Deviation from baseline (C)
How far current skin temp deviates from expected baseline.
Fever likely (0/1)
1 if skin temperature exceeds the fever detection threshold, 0 otherwise.
Fever detection confidence (%)
Confidence level that fever detection is correct given sensor accuracy.
Normal range low (C)
Lower bound of expected normal skin temperature range.
Normal range high (C)
Upper bound of expected normal skin temperature range.

How this is calculated

Worked example, using the default values

  1. Identify Input Parameters
    4 parameters
    Core body temp (C) = 37, Ambient temperature (C) = 22, Sensor accuracy (degC) = 0.2, Current activity level = 0 = 7 input(s) provided
  2. Calculate Estimated skin temp
    Estimated skin temp = coreTempC + baseSkinOffset + activityEffect + circadianEffect + menstrualTemp
    33.7 = 33.7
  3. Calculate Deviation from baseline
    Deviation from baseline = skinTempC - baselineSkinC
    0 = 0
  4. Calculate Estimated skin temp
    Estimated skin temp = skinTempC * 9 / 5 + 32
    92.7 = 92.7
  5. Calculate Baseline skin temp
    Baseline skin temp = 37 + baseSkinOffset + circadianEffect
    33.7 = 33.7

Engine last updated . Checked against 2 independently-derived tests — how we verify calculators.

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