## 2 Methods  
### Material Selection  
The present review follows an accurate and rigorous methodology to ensure comprehensive coverage of the research topic and transparency in the selection process. Specifically, the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework was adopted to structure the review process comprehensively and consistently. The application of the PRISMA methodology allows for clear documentation of the stages of literature selection, inclusion, and exclusion criteria, ensuring the replicability and reliability of the findings. This ensured that only the papers assumed to be relevant, up-to-date, and of high quality were included, as shown in Figure 1. The literature search was conducted using major scientific databases, including Scopus, Web of Science, and PubMed, with the objective of identifying studies utilizing neurophysiological methods for human factors analysis in the context of Industry 5.0. Therefore, the literature research was focused on previous works based on neurophysiological signals, such as the one representing the brain activity and the autonomous nervous system activations (e.g., electrodermal and cardiac activities). More specifically, the present work aimed at identifying (i) how have neurophysiological methods been used to assess human factors in industrial environments, and (ii) what are the existing gaps and limitations in current research on neurophysiological methods in Industry 5.0. In order to achieve this, a review was performed by focusing on the neurophysiological signal-based works (i.e., brain activity, electrodermal and cardiac activities, and eye-tracking). In this context, the search strategy was based on the use of specific keywords and the application of exclusion criteria. The query used on both search engines was as follows: (\"neurophysiological measures' OR 'EEG' OR 'GSR' OR 'EDA' OR 'eye-tracking' OR 'ECG') AND ('human factors' OR 'worker training' OR 'operator training' OR 'human-machine interaction') AND ('Industry 5.0' OR'semi-automated machines' OR 'automation'). The Boolean AND and OR operators were employed in order to obtain a combination of terms that would encompass the widest possible range of research pertinent to the utilization of neurophysiological measures for the evaluation of human factors in human-machine interaction and in an industrial context. The inclusion criteria were defined as follows:  
* Studies focusing on the characterization of human factors in industrial or workplace settings. * Research employing neurophysiological methods (e.g., EEG, EDA, PPG) to evaluate human factors. * Articles providing empirical data, theoretical insights, or methodological advancements related to Industry 5.0. Similarly, the exclusion criteria were defined as it follows:  
* Studies not directly related to the context of Industry 5.0. * Research focusing exclusively on clinical or non-industrial applications. * Articles without accessible full text or with incomplete datasets. The analysis included peer-reviewed articles published in English between 2018 and 2024. This ensured that the review was based on the most recent findings and thus, related to Industry 5.0, which has its theoretical origins less than a decade ago. The initial search yielded a total of 56 articles, of which 36 were excluded due to thematic irrelevance, as they focused on the study of human factors in automotive or air traffic control. The final sample comprised 20 articles, which were included in the review to provide a comprehensive and up-to-date overview of the applications of neurophysiological methods in Industry 5.0. In summary, the 45% of the selected works rely exclusively on the HFs characterization through the EEG features, while the 25% rely on the multimodal approach (i.e., considering the combination of different neurophysiological signals). Table 1 presents an