Developed by a team of scientists, the system measures heart rate, heart rate variability, skin temperature and movement patterns at six points on the torso and arms. The study involved 43 people between the ages of 18 and 56 who performed complex work tasks under conditions that simulated fatigue levels.
The machine learning model was able to predict participants’ fatigue levels in real time based on their physiological data. In universal trends, a connection has been found between movements of the non-dominant hand and fatigue.
Testing of the system in large factories showed that workers rated it as unobtrusive and easy to use. This technology has the potential to improve workplace safety and reduce risks for employees.
Source: Ferra
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