Bridging minds and machines in Industry 5.0: neurobiological approach - Rueda-Castro, Valentina; Azofeifa, Jose Daniel; Chacon, Julian; Caratozzolo, Patricia (Frontiers in Human Neuroscience, 2024)
In transitioning from Industry 4.0 to the forthcoming Industry 5.0, this research explores the fusion of the humanistic view and technological developments to redefine Continuing Engineering Education (CEE). Industry 5.0 introduces concepts like biomanufacturing and human-centricity, embodying the integration of sustainability and resiliency principles in CEE, thereby shaping the upskilling and reskilling initiatives for the future workforce. The interaction of sophisticated concepts such as Human-Machine Interface and Brain-Computer Interface (BCI) forms a conceptual bridge toward the approaching Fifth Industrial Revolution, allowing to know deeper into understanding human beings and the impact of their biological development across diverse and changing workplace settings. Our research is based on recent studies into Knowledge, Skills, and Abilities taxonomies, linking these elements with dynamic labor market profiles. This work intends to integrate a biometric perspective to conceptualize and describe how cognitive abilities could be represented by linking a Neuropsychological test and a biometric assessment. To achieve this aim, we administered the brief Neuropsychological Battery in Spanish (Neuropsi Breve) while 15 engineering students were using the Emotiv insight device that allowed the EEG recollection to measure performance metrics such as attention, stress, engagement, and excitement. The findings of this research illustrates a methodology that allowed having a first approach to cognitive abilities of engineering students from a neurobiological and behavioral perspectives. Additionally, two profiles were extracted from the results. The first, illustrates the Neuropsi test areas, its most common mistakes, and its performance ratings regarding the students´ sample. The second profile shows the interaction between the EEG and Neuropsi test showing engineering students´ cognitive and emotional states base on biometric levels.