Only [PERSON] and [PERSON] (2020) [24] assessed whether fatigue should be among the PSFs included in Petro-HRA, suggesting four possible PSFs based on the causes of are suggested: Sleep deprivation, Shift-length, Non-day shift, and Prolonged task performance. This gap is mainly due to the difficulty that the definition and measurement of fatigue are not easily achievable. Over the past several decades, much research has been conducted on human fatigue prevention, focusing on two main thrusts. The first one is to understand the physiological mechanism of human fatigue and how to measure fatigue level [25] and in fact, neurobiological studies have provided bio-mathematical models to predict fatigue. The second thrust focuses on developing technological devices to detect and monitor human fatigue, as fatigue appears as the major cause of accident and error in the working setting. Several ways to measure this parameter are present in the scientific and industrial field, but also in real life as the cars' system for the identification of the sleepiness of the driver installed on several cars' brands [26; 27; 28; 29]. Starting from the possibility to measure the fatigue of the humans when they are doing their job, this paper addresses the possibility to include a neuro-behavioral measure of fatigue to improve the possibility to involve this measure in the real system of performance measurement in a working activity. For this reason, this paper aims to present a first experimental results set using the algorithm for the sleepiness identification through easily available technology and then the fatigue in humans involved in work activities. For this purpose, no particular technological implementations were used, but only common and available technologies such as small cameras for eyes pointing and the interface of these cameras. Note that the knowledge improvement offered by this paper is mainly focused on the use of a technology (used in car accident prevention) in a very different context such as a workplace and finally to identify a first tentative curve for the fatigue during the normal work shifts for a specific category of workers. Finally, the limitations and future possible developments in use that these experiments revealed are reported. Therefore, starting from the literature and lack of knowledge about the use of fatigue in traditional engineering HEP methods, an open issue about the fatigue measurement at work is identified and on this basis a technology able to measure its effect is selected. After that, using this technology a real experiment on office workers is conducted to understand which is a possible fatigue curve during a real work shift for this kind of workers. In perspective, the fatigue measurements and their consideration in job assignments to different age workers could be of great impact to the improvement of the social sustainability of the companies that will consider the new aging accountability in their mission. It is worth to underline that the possibility to implement a system able to recognize fatigue, as the one here proposed, can lead the workers and their communities to a better life. This improvement in life experience can be given by the reduction of injuries caused by fatigue and by the possibility for the workers to achieve their objectives minimizing the cognitive effort and maximizing their activity in the communities out of the work. Moreover, the results of this paper will help designers and decision-makers improve workplaces, especially for some specific sectors that suffer from cognitive fatigue. These sectors, namely the aeronautical or the truck services, could implement the technological and methodological results of this paper to improve the safety conditions of the specific workplace for the pilots and drivers respectively. Looking at the impact of this work on the generality of the workplaces, it could be possible to rethink the possibility to integrate into the workplaces the video-capture technologies needed to understand the fatigue level of the workers.