The issue of Fatigue

Usually overlooked, central Fatigue affects daily performance and has been shown to be associated with a wide variety of issues. Everyone feels tired at one point or another, but if you can measure it, you can improve it. This is particularly critical for athletes, as fatigue can lead to a higher risk of injuries, but also for anybody, to ensure vitality and resilience from day to day and avoid burn-out.

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Heart-rate Variability Analysis

Beyond subjective scores or lab measurements which are invasive and time consuming, Fatigue can be assessed objectively by analyzing the Sympathetic and Parasympathetic Nervous System (SNS & PNS) modulations on the heart, also referenced as Heart-rate variability (HRV) analysis. PNS aka the “rest and digest” system dominates during rest and stimulates tissue regeneration. SNS aka the “fight or flight” system dominates during physical exercise and stimulates energy expenditure. Best performances occur when both PNS and SNS have a high modulation capacity on heart rate, and this can be evaluated during a 5min or 10min protocol.

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inCORPUS® profiling Algorithm

The proprietary inCORPUS® fatigue profiling algorithm is the result of 20+ years of scientific research and field testing with elite athletes. inCORPUS® technology exploits the raw data coming from almost any commercial hear-rate sensor. It computes and analyze both temporal and frequential HRV metrics, to identify eight unique profiles corresponding to a specific fatigue or non-fatigue physiological status. inCORPUS® profiling is tailored to each user’s reference baseline to guarantee highest levels of reliability.

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The CUBE predictive engine

The CUBE is our novel patent-pending data processing engine which can predict approaching fatigue before it settles in. The CUBE is created based on user’s HRV reference point. It computes all physiologically possible HRV-based variations, to create a hyperspace with all possible inCORPUS® profiles.

Using artificial intelligence, the CUBE evaluates user’s physiological profiles and allow to derive trends and prognosis to anticipate potential fatigue episodes.

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