ThermoHuman is a specialized software platform designed to analyze infrared thermography data. It uses computer vision and artificial intelligence to automatically process thermal images, specifically focusing on human body temperature distribution.

ThermoHuman specializes in improving player availability and optimize post-game recovery through the automatic analysis of skin temperature for this reason we create a 7 steps to interpretate thermograms.

First step: Alarms (We have an artificial intelligence module that generates three levels of alerts based on the evolution of asymmetries.)

The software assigns alert levels (1, 2, or 3) depending on the relevance of the finding. The first interpretation filter is the alert levels, which rank findings by their relevance.

• Level 1 (Low Attention):
  Small asymmetries or thermal variations.
  Usually do not require immediate intervention.
  Useful as background “noise” reference or to monitor if they appear combined with other data (pain, questionnaires, GPS, etc.).
• Level 2 (Medium Attention):
  Moderate asymmetries or relevant thermal variations.
  May be related to overload, localized fatigue, or onset of an inflammatory process.
  Require monitoring in upcoming sessions to see if they evolve or disappear.
• Level 3 (High Attention):
  Significant findings: marked asymmetries, regions with abrupt increases/decreases in temperature.
  Indicate higher risk of injury or poor load assimilation.
  Require immediate investigation, crossing clinical and performance data.

Second step: Thermogram Review

Check the thermogram for noise, factors or bad body segmentation.

Before analyzing metrics, it is essential to look at the original thermal map with the thermogram application in a constant scale:

• Discard poor image capture: Clothing, sweat, poor posture, creams, bandages, chains, external sources (AC, heaters) can distort readings.
• Identify visual patterns: Concentrated hot areas → inflammation or overload.
  Cold areas → muscle inhibition, neuromuscular fatigue, or circulatory issues.
  Abnormal distributions → possible technical error or relevant clinical finding.
  

Third step: Asymmetries

This step compares left vs. right regions, detecting imbalances.

Thermal asymmetry (normal):
Measures temperature difference between the same region on both sides.
⚠️ Considered asymmetry if difference exceeds 0.3 °C.
Not all are pathological: some are chronic or “normal” for each player.

Neutralized asymmetry:
Compares current session with player’s history.
✅ Filters chronic asymmetries (e.g., one shoulder always hotter due to old injury).
✅ Highlights only new deviations → reduces false positives.
Requires several prior evaluations.

Fourth step: Thermal Risk Index (TRI)

📊 Keys to interpretation:

🟢 Low TRI (<30): tendency to symmetry → Low risk.
🔴 High TRI (50–100): significant asymmetry, may indicate overload or injury risk.

📈 Temporal interpretation:
It is important to check the TRI trend over the last two weeks:
Rising trend: worsening asymmetry → possible poor load assimilation.
Falling or stable trend: improvement or maintenance → positive evolution.

TRI provides a global and quick view of the squad’s thermal risk, while avatars help identify which specific regions are generating the imbalance.

Fifth step: Softened Coefficient of Variation

The SCV (Softened Coefficient of Variation) analyzes how each region’s temperature evolves by comparing it with its own history.

🔥 Hot SCV: increased blood flow due to inflammation or overload → reduce load, apply drainage or physiotherapy.

❄️ Cold SCV: may suggest muscle inhibition or neuromuscular involvement → prioritize activation and mobility.

⚖️ Stable SCV (≈ 0): region within normal parameters → maintain the current plan.

Detects relevant trends even if there are no asymmetries.
Especially useful in large muscle groups (quadriceps, hamstrings, lumbar)
A sustained trend confirms a real physiological process rather than a one-off change.

Sixth step: Normality Block

📊 Main metric: Normality (comparison with ThermoHuman database)
This block complements the asymmetry analysis, helping identify which specific regions are heating up or cooling down.

🔵 Blue line → average temperature of each region of the right leg.
🟠 Orange line → average temperature of each region of the left leg.
⚪ Gray band → population normality range for each region (ThermoHuman database).

Interpretation:

Lines within the gray band → normal behavior.
Shift to the right of the region’s midline → region hotter than expected (hyperthermia) 🔥
Shift to the left of the region’s midline → region colder than expected (hypothermia) ❄️

Seventh step: Fatigue Identification (TSI)
The TSI (Thermal Status Index) is a fatigue-mode metric that classifies a player’s thermal status according to the trend of their global temperature compared with their own history.

It is used mainly 24–48 h post-match. The scale goes from +100 to −100.

📈 Interpretation:

🔥 TSI > 0 (hyperthermia): structural fatigue (inflammation, microdamage) → cold strategies.
❄️ TSI < 0 (hypothermia): metabolic/central fatigue (travel, congestion, energy deficit) → heat strategies.
⚖️ TSI ≈ 0 (neutral): stable state → standard recovery (rest, nutrition, hydration).

TSI provides a quick, objective read on fatigue type (structural vs. metabolic), facilitating the choice of the most appropriate recovery strategy for each player.

Conclusion

The interpretation flow in summary:

Alerts → Quickly detect which players/regions require priority attention.
Thermograms → Confirm visual patterns and discard elements that distort the image.
Asymmetries & Neutralized Asymmetry → Reveal thermal imbalances, filtering the chronic from the new.
TRI (Thermal Risk Index) → Offers a global view of thermal risk and its evolution over time.
SCV (Softened Coefficient of Variation) → Detects trends in the thermal evolution of muscle groups or specific regions.
Normality Block → Compares each region’s temperatures with the population database, clarifying whether a region is hotter (hyperthermia) or colder (hypothermia) than expected.
TSI (Thermal Status Index) → Analyzes the post-match global temperature trend, differentiating between structural (hyperthermia), metabolic (hypothermia), or neutral states.

Key point: each step adds a layer of context—from the initial alert, through visual confirmation and data filtering, to identifying the type of fatigue or thermal alteration. With this order, interpretation is fast, standardized, and actionable, connecting thermography to practical decisions in prevention, monitoring, and recovery.

If you want this guide with examples please write to our customer service: info@thermohuman.com