Frontiers in neuroergonomics最新文献

{"title":"Detecting sources of anger in automated driving: driving-related and external factor.","authors":"Jordan Maillant, Christophe Jallais, Stéphanie Dabic","doi":"10.3389/fnrgo.2025.1548861","DOIUrl":"10.3389/fnrgo.2025.1548861","url":null,"abstract":"<p><strong>Introduction: </strong>Anger while driving is often provoked by on-road events like sudden cut-offs but can also arise from external factors, such as rumination of negative thoughts. With the rise of autonomous vehicles, drivers are expected to engage more in non-driving activities, potentially increasing the occurrence of anger stemming from non-driving-related sources. Given the well-established link between anger and aggressive driving behaviors, it is crucial to detect and understand the various origins of anger in autonomous driving contexts to enhance road safety.</p><p><strong>Methods: </strong>This study investigates whether physiological (cardiac and respiratory activities) and ocular indicators of anger vary depending on its source (driving-related or external) in a simulated autonomous driving environment. Using a combination of autobiographical recall (AR) for external anger induction and driving-related scenarios (DS), 47 participants were exposed to anger and/or neutral conditions across four groups.</p><p><strong>Results: </strong>The results revealed that combined anger induction (incorporating both external and driving-related sources) led to higher subjective anger ratings, more heart rate variability. However, when examined separately, individual anger sources did not produce significant differences in physiological responses and ocular strategies.</p><p><strong>Discussion: </strong>These results suggest that the combination of anger-inducing events, rather than the specific source, is more likely to provoke a heightened state of anger. Consequently, future research should employ combined induction methods to effectively elicit anger in experimental settings. Moreover, anger detection systems should focus on the overall interplay of contributing factors rather than distinguishing between individual sources, as it is this cumulative dynamic that more effectively triggers significant anger responses.</p>","PeriodicalId":517413,"journal":{"name":"Frontiers in neuroergonomics","volume":"6 ","pages":"1548861"},"PeriodicalIF":1.5,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12098279/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144145349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Visualization and workload with implicit fNIRS-based BCI: toward a real-time memory prosthesis with fNIRS.","authors":"Matthew Russell, Samuel Hincks, Liang Wang, Amin Babar, Zaiyi Chen, Zachary White, Robert J K Jacob","doi":"10.3389/fnrgo.2025.1550629","DOIUrl":"10.3389/fnrgo.2025.1550629","url":null,"abstract":"<p><p>Functional Near-Infrared Spectroscopy (fNIRS) has proven in recent time to be a reliable workload-detection tool, usable in real-time implicit Brain-Computer Interfaces. But what can be done in terms of application of neural measurements of the prefrontal cortex beyond mental workload? We trained and tested a first prototype example of a memory prosthesis leveraging a real-time implicit fNIRS-based BCI interface intended to present information appropriate to a user's current brain state from moment to moment. Our prototype implementation used data from two tasks designed to interface with different brain networks: a creative visualization task intended to engage the Default Mode Network (DMN), and a complex knowledge-worker task to engage the Dorsolateral Prefrontal Cortex (DLPFC). Performance of 71% from leave-one-out cross-validation across participants indicates that such tasks are differentiable, which is promising for the development of future applied fNIRS-based BCI systems. Further, analyses within lateral and medial left prefrontal areas indicates promising approaches for future classification.</p>","PeriodicalId":517413,"journal":{"name":"Frontiers in neuroergonomics","volume":"6 ","pages":"1550629"},"PeriodicalIF":1.5,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12089058/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144113217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Learning selection-based augmented reality interactions across different training modalities: uncovering sex-specific neural strategies.","authors":"John Hayes, Joseph L Gabbard, Ranjana K Mehta","doi":"10.3389/fnrgo.2025.1539552","DOIUrl":"https://doi.org/10.3389/fnrgo.2025.1539552","url":null,"abstract":"<p><strong>Introduction: </strong>Recent advancements in augmented reality (AR) technology have opened up potential applications across various industries. In this study, we assess the effectiveness of psychomotor learning in AR compared to video-based training methods.</p><p><strong>Methods: </strong>Thirty-three participants (17 males) trained on four selection-based AR interactions by either watching a video or engaging in hands-on practice. Both groups were evaluated by executing these learned interactions in AR.</p><p><strong>Results: </strong>The AR group reported a higher subjective workload during training but showed significantly faster completion times during evaluation. We analyzed brain activation and functional connectivity using functional near-infrared spectroscopy during the evaluation phase. Our findings indicate that participants who trained in AR displayed more efficient brain networks, suggesting improved neural efficiency.</p><p><strong>Discussion: </strong>Differences in sex-related activation and connectivity hint at varying neural strategies used during motor learning in AR. Future studies should investigate how demographic factors might influence performance and user experience in AR-based training programs.</p>","PeriodicalId":517413,"journal":{"name":"Frontiers in neuroergonomics","volume":"6 ","pages":"1539552"},"PeriodicalIF":1.5,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12066766/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144054054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From beeps to streets: unveiling sensory input and relevance across auditory contexts.","authors":"Silvia Korte, Manuela Jaeger, Marc Rosenkranz, Martin G Bleichner","doi":"10.3389/fnrgo.2025.1571356","DOIUrl":"https://doi.org/10.3389/fnrgo.2025.1571356","url":null,"abstract":"<p><strong>Introduction: </strong>This study investigates the neural basis of sound perception in everyday life using EEG data recorded in an office-like environment over 3.5 h. We aimed to understand how contextual factors such as personal relevance, task complexity, and stimulus properties influence auditory processing in ecologically valid settings.</p><p><strong>Methods: </strong>By systematically increasing the complexity of acoustic scenes and tasks, we analyzed changes in neural responses, focusing on the N100 and P300 components.</p><p><strong>Results: </strong>Our results show that while the P300 is a stable marker of attention in both isolated sounds and complex soundscapes, the N100 is more sensitive to task complexity and environmental factors.</p><p><strong>Discussion: </strong>These findings highlight the importance of context in shaping auditory perception and suggest that laboratory-based findings can be partially generalized to real-world settings. At the same time, task demands significantly influence neural markers. This opens new opportunities to study sound perception in naturalistic environments without sacrificing the control typically afforded by laboratory studies.</p>","PeriodicalId":517413,"journal":{"name":"Frontiers in neuroergonomics","volume":"6 ","pages":"1571356"},"PeriodicalIF":1.5,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12066603/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144065404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Systematic review of neurophysiological assessment techniques and metrics for mental workload evaluation in real-world settings.","authors":"Moussa Diarra, Jean Theurel, Benjamin Paty","doi":"10.3389/fnrgo.2025.1584736","DOIUrl":"https://doi.org/10.3389/fnrgo.2025.1584736","url":null,"abstract":"<p><strong>Introduction: </strong>Mental Workload (MWL) is a concept that has garnered increasing interest in professional settings but remains challenging to define consensually. The literature reports a plurality of operational definitions and assessment methods, with no established unified framework. This review aims to identify objective and validated measurement methods for evaluating MWL in real-world work contexts. Particular attention is given to neurophysiological methods, recognized for their efficiency and robustness, enabling real-time assessment without disrupting operator activity.</p><p><strong>Method: </strong>To conduct this analysis, a systematic search was performed in three databases (PubMed, ScienceDirect, and IEEEXplore), covering studies published from their inception until March 30, 2023. Selection criteria included research focusing on MWL and its derivatives, as well as neurophysiological measures applied in real-world conditions. An initial screening based on titles and abstracts was followed by an in-depth review, assisted by the bibliometric software Rayyan.</p><p><strong>Results: </strong>The explored concepts, applied methods, and study results were compiled into a synthesis table. Ultimately, 35 studies were included, highlighting the diversity of measurement tools used in field settings, often combined with subjective assessments.</p><p><strong>Discussion: </strong>Furthermore, key physiological indicators such as ECG, eye data, EEG and the relationship between MWL metrics and those uses to measure stress are emphasized and discussed. A better understanding of these interrelations could refine the assessment of their respective impacts and help anticipate their consequences on workers' mental health and safety.</p>","PeriodicalId":517413,"journal":{"name":"Frontiers in neuroergonomics","volume":"6 ","pages":"1584736"},"PeriodicalIF":1.5,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12061935/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144052342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mind the road: attention related neuromarkers during automated and manual simulated driving captured with a new mobile EEG sensor system.","authors":"Joanna Elizabeth Mary Scanlon, Daniel Küppers, Anneke Büürma, Axel Heinrich Winneke","doi":"10.3389/fnrgo.2025.1542379","DOIUrl":"10.3389/fnrgo.2025.1542379","url":null,"abstract":"<p><strong>Background: </strong>Decline in vigilance due to fatigue is a common concern in traffic safety. Partially automated driving (PAD) systems can aid driving but decrease the driver's vigilance over time, due to reduced task engagement. Mobile EEG solutions can obtain neural information while operating a vehicle. The purpose of this study was to investigate how the behavior and brain activity associated with vigilance (i.e., alpha, beta and theta power) differs between PAD and manual driving, as well as changes over time, and how these effects can be detected using two different EEG systems.</p><p><strong>Methods: </strong>Twenty-eight participants performed two 1-h simulated driving tasks, while wearing both a standard 24 channel EEG cap and a newly developed, unobtrusive and easy to apply 10 channel mobile EEG sensor-grid system. One scenario required manual control of the vehicle (manual) while the other required only monitoring the vehicle (PAD). Additionally, lane deviation, percentage eye-closure (PERCLOS) and subjective ratings of workload, fatigue and stress were obtained.</p><p><strong>Results: </strong>Alpha, beta and theta power of the EEG as well as PERCLOS were higher in the PAD condition and increased over time in both conditions. The same spectral EEG effects were evident in both EEG systems. Lane deviation as an index of driving performance in the manual driving condition increased over time.</p><p><strong>Conclusion: </strong>These effects indicate significant increases in fatigue and vigilance decrement over time while driving, and overall higher levels of fatigue and vigilance decrement associated with PAD. The EEG measures revealed significant effects earlier than the behavioral measures, demonstrating that EEG might allow faster detection of decreased vigilance than behavioral driving measures. This new, mobile EEG-grid system could be used to evaluate and improve driver monitoring systems in the field or even be used in the future as additional sensor to inform drivers of critical changes in their level of vigilance. In addition to driving, further areas of application for this EEG-sensor grid are safety critical work environments where vigilance monitoring is pivotal.</p>","PeriodicalId":517413,"journal":{"name":"Frontiers in neuroergonomics","volume":"6 ","pages":"1542379"},"PeriodicalIF":1.5,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11937089/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143723070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial: Advances in mobile optical brain activity monitoring.","authors":"Surjo R Soekadar, Felix Scholkmann, Meryem Ayşe Yücel, Paola Pinti, J Adam Noah, Alexander von Lühmann","doi":"10.3389/fnrgo.2025.1568619","DOIUrl":"10.3389/fnrgo.2025.1568619","url":null,"abstract":"","PeriodicalId":517413,"journal":{"name":"Frontiers in neuroergonomics","volume":"6 ","pages":"1568619"},"PeriodicalIF":1.5,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11925908/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143695062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correlations of pilot trainees' brainwave dynamics with subjective performance evaluations: insights from EEG microstate analysis.","authors":"Mengting Zhao, Andrew Law, Chang Su, Sion Jennings, Alain Bourgon, Wenjun Jia, Marie-Hélène Larose, David Bowness, Yong Zeng","doi":"10.3389/fnrgo.2025.1472693","DOIUrl":"10.3389/fnrgo.2025.1472693","url":null,"abstract":"<p><strong>Objective: </strong>This study aims to investigate the relationship between the subjective performance evaluations on pilot trainees' aircraft control abilities and their brainwave dynamics reflected in the results from EEG microstate analysis. Specifically, we seek to identify correlations between distinct microstate patterns and each dimension included in the subjective flight control evaluations, shedding light on the neurophysiological mechanisms underlying aviation expertise and possible directions for future improvements in pilot training.</p><p><strong>Background: </strong>Proficiency in aircraft control is crucial for aviation safety and modern aviation where pilots need to maneuver aircraft through an array of situations, ranging from routine takeoffs and landings to complex weather conditions and emergencies. However, the neurophysiological aspects of aviation expertise remain largely unexplored. This research bridges the gap by examining the relationship between pilot trainees' specific brainwave patterns and their subjective evaluations of flight control levels, offering insights into the cognitive underpinnings of pilot skill efficiency and development.</p><p><strong>Method: </strong>EEG microstate analysis was employed to examine the brainwave dynamics of pilot trainees while they performed aircraft control tasks under a flight simulator-based pilot training process. Trainees' control performance was evaluated by experienced instructors across five dimensions and their EEG data were analyzed to investigate the associations between the parameters of specific microstates with successful aircraft control.</p><p><strong>Results: </strong>The experimental results revealed significant associations between aircraft control levels and the parameters of distinct EEG microstates. Notably, these associations varied across control dimensions, highlighting the multifaceted nature of control proficiency. Noteworthy correlations included positive correlations between microstate class E and class G with aircraft control, emphasizing the role of attentional processes, perceptual integration, working memory, cognitive flexibility, decision-making, and executive control in aviation expertise. Conversely, negative correlations between microstate class C and class F with aircraft control indicated links between pilot trainees' cognitive control and their control performance on flight tasks.</p><p><strong>Conclusion: </strong>The findings underscore the multidimensional nature of aircraft control proficiency and emphasize the significance of attentional and cognitive processes in achieving aviation expertise. These neurophysiological markers offer a basis for designing targeted pilot training programs and interventions to enhance trainees' aircraft control skills.</p>","PeriodicalId":517413,"journal":{"name":"Frontiers in neuroergonomics","volume":"6 ","pages":"1472693"},"PeriodicalIF":1.5,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11919915/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143665816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Construction and evaluation of a finger motor feedback system to improve finger dexterity.","authors":"Shingo Takahashi, Noriko Sakurai, Yuki Kuroiwa, Daishi Takahashi, Naoki Kodama","doi":"10.3389/fnrgo.2025.1502492","DOIUrl":"10.3389/fnrgo.2025.1502492","url":null,"abstract":"<p><strong>Introduction: </strong>Recently, a link has been established between cognitive function and hand dexterity in older adults. Declines in cognitive function have been shown to impair performance in finger tapping movements. Research suggest that hand training can improve dexterity, executive function, and cognitive function over time. This underscores the need for effective methods to improve hand and finger dexterity.</p><p><strong>Method: </strong>In this study, we introduced a new hand training system that provides real-time feedback on finger movements during tapping tasks. We examined the system's impact on the finger dexterity of 32 healthy young participants by using a magnetic sensor finger tapping device (UB-2). During the finger tapping task, the participants performed opening and closing movements either in-phase or anti-phase on both left and right hands for 15 s. They were instructed to tap as quickly as possible. The number of taps, left-right balance, and other relevant data were measured using the UB-2 device.</p><p><strong>Results: </strong>In terms of the number of tapping, a significant difference was found between 64.4 without feedback and 68.1 with feedback for the simultaneous opening and closing movements in the dominant hand. In the alternating open-close movement, the significant difference was 50.3 without feedback and 53.4 with feedback. The results showed that the system significantly improved the number and frequency of taps for both hands.</p><p><strong>Conclusion: </strong>The improved tapping performance with feedback suggests that this system can improve hand dexterity.</p>","PeriodicalId":517413,"journal":{"name":"Frontiers in neuroergonomics","volume":"6 ","pages":"1502492"},"PeriodicalIF":1.5,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11897288/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143618136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating robotic actions: spatiotemporal brain dynamics of performance assessment in robot-assisted laparoscopic training.","authors":"Katharina Lingelbach, Jennifer Rips, Lennart Karstensen, Franziska Mathis-Ullrich, Mathias Vukelić","doi":"10.3389/fnrgo.2025.1535799","DOIUrl":"10.3389/fnrgo.2025.1535799","url":null,"abstract":"<p><strong>Introduction: </strong>Enhancing medical robot training traditionally relies on explicit feedback from physicians to identify optimal and suboptimal robotic actions during surgery. Passive brain-computer interfaces (BCIs) offer an emerging alternative by enabling implicit brain-based performance evaluations. However, effectively decoding these evaluations of robot performance requires a comprehensive understanding of the spatiotemporal brain dynamics identifying optimal and suboptimal robot actions within realistic settings.</p><p><strong>Methods: </strong>We conducted an electroencephalographic study with 16 participants who mentally assessed the quality of robotic actions while observing simulated robot-assisted laparoscopic surgery scenarios designed to approximate real-world conditions. We aimed to identify key spatiotemporal dynamics using the surface Laplacian technique and two complementary data-driven methods: a mass-univariate permutation-based clustering and multivariate pattern analysis (MVPA)-based temporal decoding. A second goal was to identify the optimal time interval of evoked brain signatures for single-trial classification.</p><p><strong>Results: </strong>Our analyses revealed three distinct spatiotemporal brain dynamics differentiating the quality assessment of optimal vs. suboptimal robotic actions during video-based laparoscopic training observations. Specifically, an enhanced left fronto-temporal current source, consistent with P300, LPP, and P600 components, indicated heightened attentional allocation and sustained evaluation processes during suboptimal robot actions. Additionally, amplified current sinks in right frontal and mid-occipito-parietal regions suggested prediction-based processing and conflict detection, consistent with the oERN and interaction-based ERN/N400. Both mass-univariate clustering and MVPA provided convergent evidence supporting these neural distinctions.</p><p><strong>Discussion: </strong>The identified neural signatures propose that suboptimal robotic actions elicit enhanced, sustained brain dynamics linked to continuous attention allocation, action monitoring, conflict detection, and ongoing evaluative processing. The findings highlight the importance of prioritizing late evaluative brain signatures in BCIs to classify robotic actions reliably. These insights have significant implications for advancing machine-learning-based training paradigms.</p>","PeriodicalId":517413,"journal":{"name":"Frontiers in neuroergonomics","volume":"6 ","pages":"1535799"},"PeriodicalIF":1.5,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11880255/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143575060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}