New Method for Better Training and Performance Readiness through Eye Tracking and Artificial Intelligence Tools (ETAI)

Developing AI‑based human load measurement methods

Duration of the project

1.1.2026 – 31.12.2027

Source of funding

Business Finland

Total funding

675 772 €

The project develops a new invisible, real-time physiological measurement method to predict human mental and physical load in advance. Based on AI and machine learning, the method enables the early detection of fatigue and load with only millisecond-level delay. The solution responds to the rapidly evolving technological environment and opens new possibilities for managing human load across different contexts.

The project develops a next‑generation physiological measurement method that will transform existing practices for assessing human load and recovery. Traditional measurements have been retrospective, providing results with delays ranging from minutes to days. The new method predicts fatigue and load in real time with only millisecond-level delay.

The approach is based on machine learning and AI-driven algorithms that model mental and physical load based on autonomic nervous system activity. Unlike indirect indicators such as heart rate variability, the method reduces the impact of voluntary physiological responses on measurement results.

The solution enables real-time, predictive assessment of human mental and physical load, which creates broad application potential in traffic safety, preventive occupational health, learning, endurance and life‑cycle performance management, elite sports, and other demanding operational environments. The project ensures that physiological load measurement evolves in step with rapidly advancing technology..