Multiple resources and mental workload

Chunking of Control: An Unrecognized Aspect of Cognitive Resource Limits

Why do we divide ('chunk') long tasks into a series of shorter subtasks? A popular view is that limits in working memory (WM) prevent us from simultaneously maintaining all task relevant information in mind. We therefore chunk the task into smaller units so that we only maintain information in WM that is relevant to the current unit. In contrast to this view, we show that long tasks that are not constrained by WM limits are nonetheless chunked into smaller units. Participants executed long sequences of standalone but demanding trials that were not linked to any WM representation and whose execution was not constrained by how much information could be simultaneously held in WM. Using signs well-known to reflect beginning of new task units, we show that such trial sequences were not executed as a single task unit but were spontaneously chunked and executed as series smaller units. We also found that sequences made of easier trials were executed as longer task units and vice-versa, further suggesting that the length of task executed as one unit may be constrained by cognitive limits other than WM. Cognitive limits are typically seen to constrain how many things can be done simultaneously e.g., how many events can be maintained in WM or attended at the same time. We show a new aspect of these limits that constrains the length of behaviour that can be executed sequentially as a single task-unit.

Impacts of complex electromagnetic radiation and low-frequency noise exposure conditions on the cognitive function of operators

Background

Both electromagnetic radiation (EMR) and low-frequency noise (LFN) are widespread and influential environmental factors, and operators are inevitably exposed to both EMR and LFN within a complex exposure environment. The potential adverse effects of such exposure on human health must be considered seriously. This study aimed to investigate the effects of EMR and LFN on cognitive function as well as their interaction effect, which remain unclear.

Methods

Sixty young male college students were randomly grouped and experiments were conducted with a 2 × 2 factorial design in a shielded chamber. Mental workload (MWL) levels of the study subjects were measured and assessed using the NASA-task load index (TLX) subjective scale, an n-back task paradigm, and the functional near-infrared spectroscopy (fNIRS) imaging technique.

Results

For the 3-back task, the NASA-TLX subjective scale revealed a statistically significant main effect of LFN intensity, which enhanced the subjects' MWL level (F = 8.716, p < 0.01). Behavioral performance revealed that EMR intensity (430.1357 MHz, 10.75 W/m²) and LFN intensity (0-200 Hz, 72.9 dB) had a synergistic interaction effect, and the correct response time was statistically significantly prolonged by the combined exposure (F = 4.343, p < 0.05). The fNIRS imaging technique revealed a synergistic interaction effect between operational EMR intensity and operational LFN intensity, with statistically significant effects on the activation levels in the left and right dorsolateral prefrontal cortex (DLPFC). The mean β values of DLPFC were significantly increased (L-DLPFC F = 5.391, p < 0.05, R-DLPFC F = 4.222, p < 0.05), and the relative concentrations of oxyhemoglobin in the DLPFC were also significantly increased (L-DLPFC F = 4.925, p < 0.05, R-DLPFC F = 9.715, p < 0.01).

Conclusion

We found a statistically significant interaction effect between EMR (430.1357 MHz, 10.75 W/m²) and LFN (0-200 Hz, 72.9 dB) when simultaneously exposing subjects to both for 30 min. We conclude that exposure to this complex environment can cause a statistically significant increase in the MWL level of operators, and even alterations in their cognitive function.

Multimodal interface and reliability displays: Effect on attention, mode awareness, and trust in partially automated vehicles

The goal of this study is to evaluate the effect of a multimodal interface indicating the limits of automation in order to stimulate an appropriate level of attention and to induce accurate mode awareness and trust in partial driving automation. Participants drove in a driving simulator with partial driving automation and were confronted with surprising situations of suspension of driving automation systems in different contexts. They drove the simulator during three driving sessions, with either a multimodal interface indicating the limits of automation or a visual basic interface. Their driving performance, ocular behavior, and subjective evaluation of trust and workload were evaluated. The results revealed that the multimodal interface stimulates an appropriate level of attention and increases mode awareness and trust in automation, but these effects are context-dependent. The indications of the limits of automation improved the knowledge regarding automation, but this knowledge did not necessarily lead to improved driving performance. Design solutions are discussed to support the improvement of driving performance for take-overs in vehicles equipped with partial driving automation.

Impact of experience on the sensitivity, acceptability, and intrusive of two subjective mental workload techniques: The NASA TLX and workload profile

BACKGROUND

Today's work environments have high cognitive demands, and mental workload is one of the main causes of work stress, human errors, and accidents. While several mental workload studies have compared the mental workload perceived by groups of experienced participants to that perceived by novice groups, no comparisons have been made between the same individuals performing the same tasks at different times.

OBJECTIVE

This work aims to compare NASA Task Load Index (NASA-TLX) to Workload Profile (WP) in terms of their sensitivity. The comparison considers the impact of experience and task differentiation in the same individual once a degree of experience has been developed in the execution of the same tasks. It also considers the acceptability and intrusivity of the techniques.

METHODS

The sample consisted of 30 participants who performed four tasks in two sessions. The first session was performed when participants had no experience; the second session was performed after a time of practice. Mental workload was assessed after each session. Statistical methods were used to compare the results.

RESULTS

The NASA-TLX proved to be more sensitive to experience, while the WP showed greater sensitivity to task differentiation. In addition, while both techniques featured a similar degree of intrusivity, the NASA-TLX received greater acceptability.

CONCLUSION

The acceptability of WP is low due to the high complexity of its dimensions and clarifying explanations of these may be necessary to increase acceptability. Future research proposals should be expanded to consider mental workload when designing work environments in current manufacturing environments.

Assessing the physiological effect of non-driving-related task performance in conditionally automated driving systems: A systematic review and meta-analysis protocol

Background

Level 3 automated driving systems involve the continuous performance of the driving task by artificial intelligence within set environmental conditions, such as a straight highway. The driver's role in Level 3 is to resume responsibility of the driving task in response to any departure from these conditions. As automation increases, a driver's attention may divert towards non-driving-related tasks (NDRTs), making transitions of control between the system and user more challenging. Safety features such as physiological monitoring thus become important with increasing vehicle automation. However, to date there has been no attempt to synthesise the evidence for the effect of NDRT engagement on drivers' physiological responses in Level 3 automation.

Methods

A comprehensive search of the electronic databases MEDLINE, EMBASE, Web of Science, PsycINFO, and IEEE Explore will be conducted. Empirical studies assessing the effect of NDRT engagement on at least one physiological parameter during Level 3 automation, in comparison with a control group or baseline condition will be included. Screening will take place in two stages, and the process will be outlined within a PRISMA flow diagram. Relevant physiological data will be extracted from studies and analysed using a series of meta-analyses by outcome. A risk of bias assessment will also be completed on the sample.

Conclusion

This review will be the first to appraise the evidence for the physiological effect of NDRT engagement during Level 3 automation, and will have implications for future empirical research and the development of driver state monitoring systems.

The effects of dual-task interference on visual search and verbal memory

The operational costs of multitasking are more pressing given the increase in wearable technologies (head-up displays; HUDs) that facilitate multitasking. Often multitasking comes with performance costs, where the addition of more tasks impairs the performance of the tasks. The current study explored the extent to which multitasking interference can be characterised in simulated environments, as opposed to risky and harsh environments in real operational contexts. Forty-eight participants completed several trials where they performed a visual search task while navigating a simulated environment. There were three conditions: a standalone memory task, a standalone search task, and both tasks simultaneously. Results revealed significant dual-task interference when comparing the dual-task to each of the single-tasks. Results were corroborated by subjective workload and stress metrics. The results could prove useful for designing systems for individuals who routinely multitask in operational environments. Specifically, by furthering the understanding of their performance capabilities and trade-offs due to multitasking.Practitioner summary: Due to the demands of multitasking in operational environments, quantifying the degree of information lost on each task individually will aid in the understanding of the deficits of multitasking performance. This study shows that deficits in multi-tasking (via a HUD) can be understood in simulated environments to a similar degree as real-world tasks.

Relationship Between Dual-Task Walking and Level of Conflict Between Gait and Concurrent Tasks in Adolescents

This study aimed to determine the role of resource conflict in dual-task (DT) effects on gait and concurrent tasks in children and adolescents. Gait was evaluated with and without concurrent tasks (visual-manual, visual-vocal and auditory-vocal). The roles of condition (single vs dual) and type of concurrent task in DT effect were tested by Repeated Measured of ANOVA. Relative changes from single to DT conditions were compared using One-Way ANOVA. There were significant reductions in gait speed, cadence, and stride length, and increases in double support time, step time and variability in step time, and no change in variability in stride length, step width, and concurrent task performance from single to DT conditions. DT effects on gait parameters and concurrent tasks were comparable across DT conditions.

Virtual accident curb risk habituation in workers by restoring sensory responses to real-world warning

In high-risk work environments, workers become habituated to hazards they frequently encounter, subsequently underestimating risk and engaging in unsafe behaviors. This phenomenon has been termed "risk habituation" and identified as a vital root cause of fatalities and injuries at workplaces. Providing an effective intervention that curbs workers' risk habituation is critical in preventing occupational injuries and fatalities. However, there exists no empirically supported intervention for curbing risk habituation. To this end, here we investigated how experiencing an accident in a virtual reality (VR) environment affects workers' risk habituation toward repeatedly exposed workplace hazards. We examined an underlying mechanism of risk habituation at the sensory level and evaluated the effect of the accident intervention through electroencephalography (EEG). The results of pre- and posttreatment analyses indicate experiencing the virtual accident effectively curbs risk habituation at both the behavioral and sensory level. The findings open new vistas for occupational safety training.

Exploring the Peak-End Effects in Air Traffic Controllers' Mental Workload Ratings

OBJECTIVE

This study examined whether professional air traffic controllers (ATCos) were subject to peak-end effects in reporting their mental workload after performing an air traffic control task, and in predicting their mental workload in future scenarios.

BACKGROUND

In affective experience studies, people's evaluation of a period of experience is strongly influenced by the most intense (peak) point and the endpoint. However, whether the effects exist in mental workload evaluations made by professional operators is still not known.

METHOD

In Study 1, 20 ATCos performed air traffic control scenarios on high-fidelity radar simulators and reported their mental workload. We used a 2 (high peak, low peak) × 2 (high end, low end) within-subject design. In Study 2, another group of 43 ATCos completed a survey asking them to predict their mental workload given the same air traffic control scenarios.

RESULTS

In Study 1, ATCos reported higher mental workload after completing the high-peak and the high-end scenarios. In contrast, in Study 2, ATCos predicted the peak workload effect but not the end workload effect when asked to predict their experience in dealing with the same scenarios.

CONCLUSION

Peak and end effects exist in subjective mental workload evaluation, but experts only had meta-cognitive awareness of the peak effect, and not the end effect.

APPLICATION

Researchers and practitioners that use subjective workload estimates for work design decisions need to be aware of the potential impact of peak and end task demand effects on subjective mental workload ratings provided by expert operators.

A Survey on Affective and Cognitive VR

In Virtual Reality (VR), users can be immersed in emotionally intense and cognitively engaging experiences. Yet, despite strong interest from scholars and a large amount of work associating VR and Affective and Cognitive States (ACS), there is a clear lack of structured and systematic form in which this research can be classified. We define "Affective and Cognitive VR" to relate to works which (1) induce ACS, (2) recognize ACS, or (3) exploit ACS by adapting virtual environments based on ACS measures. This survey clarifies the different models of ACS, presents the methods for measuring them with their respective advantages and drawbacks in VR, and showcases Affective and Cognitive VR studies done in an Immersive Virtual Environment (IVE) in a non-clinical context. Our article covers the main research lines in Affective and Cognitive VR. We provide a comprehensive list of references with the analysis of 63 research articles and summarize future works directions.

Distractions by work-related activities: The impact of ride-hailing app and radio system on male taxi drivers

Use of ride-hailing mobile apps has surged and reshaped the taxi industry. These apps allow real-time taxi-customer matching of taxi dispatch system. However, there are also increasing concerns for driver distractions as a result of these ride-hailing systems. This study aims to investigate the effects of distractions by different ride-hailing systems on the driving performance of taxi drivers using the driving simulator experiment. In this investigation, fifty-one male taxi drivers were recruited. During the experiment, the road environment (urban street versus motorway), driving task (free-flow driving versus car-following), and distraction type (no distraction, auditory distraction by radio system, and visual-manual distraction by mobile app) were varied. Repeated measures ANOVA and random parameter generalized linear models were adopted to evaluate the distracted driving performance accounting for correlations among different observations of a same driver. Results indicate that distraction by mobile app impairs driving performance to a larger extent than traditional radio systems, in terms of the lateral control in the free-flow motorway condition and the speed control in the free-flow urban condition. In addition, for car-following task on urban street, compensatory behaviour (speed reduction) is more prevalent when distracted by mobile app while driving, compared to that of radio system. Additionally, no significant difference in subjective workload between distractions by mobile app and radio system were found. Several driver characteristics such as experience, driving records, and perception variables also influence driving performances. The findings are expected to facilitate the development of safer ride-hailing systems, as well as driver training and road safety policy.

Multimodal interaction: Input-output modality combinations for identification tasks in augmented reality

Multimodal interaction (MMI) is being widely implemented, especially in new technologies such as augmented reality (AR) systems since it is presumed to support a more natural, efficient, and flexible form of interaction. However, limited research has been done to investigate the proper application of MMI in AR. More specifically, the effects of combining different input and output modalities during MMI in AR are still not fully understood. Therefore, this study aims to examine the independent and combined effects of different input and output modalities during a typical AR task. 20 young adults participated in a controlled experiment in which they were asked to perform a simple identification task using an AR device in different input (speech, gesture, multimodal) and output (VV-VA, VV-NA, NV-VA, NV-NA) conditions. Results showed that there were differences in the influence of input and output modalities on task performance, workload, perceived appropriateness, and user preference. Interaction effects between the input and output conditions on the performance metrics were also evident in this study, suggesting that although multimodal input is generally preferred by the users, it should be implemented with caution since its effectiveness is highly influenced by the processing code of the system output. This study, which is the first of its kind, has revealed several new implications regarding the application of MMI in AR systems.

A Systematic Review and Meta-Analysis of Takeover Performance During Conditionally Automated Driving

OBJECTIVE

The aim of this paper was to synthesize the experimental research on factors that affect takeover performance during conditionally automated driving.

BACKGROUND

For conditionally automated driving, the automated driving system (ADS) can handle the entire dynamic driving task but only for limited domains. When the system reaches a limit, the driver is responsible for taking over vehicle control, which may be affected by how much time they are provided to take over, what they were doing prior to the takeover, or the type of information provided to them during the takeover.

METHOD

Out of 8446 articles identified by a systematic literature search, 48 articles containing 51 experiments were included in the meta-analysis. Coded independent variables were time budget, non-driving related task engagement and resource demands, and information support during the takeover. Coded dependent variables were takeover timing and quality measures.

RESULTS

Engaging in non-driving related tasks results in degraded takeover performance, particularly if it has overlapping resource demands with the driving task. Weak evidence suggests takeover performance is impaired with shorter time budgets. Current implementations of information support did not affect takeover performance.

CONCLUSION

Future research and implementation should focus on providing the driver more time to take over while automation is active and should further explore information support.

APPLICATION

The results of the current paper indicate the need for the development and deployment of vehicle-to-everything (V2X) services and driver monitoring.

The "Effort Elephant" in the Room: What Is Effort, Anyway?

Despite decades of research in the fields of judgment and decision-making, social psychology, cognitive psychology, human-machine interaction, behavioral economics, and neuroscience, we still do not know what "cognitive effort" is. The definitions in use are often imprecise and sometimes diametrically opposed. Researchers with different assumptions talk past each other, and many aspects of effort conservation remain untested and difficult to measure. In this article, we explain why effort is so difficult to pin down and why it is important that researchers develop consensus on precise definitions. Next, we describe major "hidden" sources of miscommunication: areas in which researchers disagree in their underlying assumptions about the nature of effort without realizing it. We briefly review a number of methods used to both measure and manipulate the effortfulness of thinking and highlight why they often produce contradictory findings. We conclude by reviewing existing perspectives on cognitive effort and integrating them to suggest a common framework for communicating about effort as a limited cognitive resource.

Assessing mental workload with wearable devices - Reliability and applicability of heart rate and motion measurements

Wearable devices are increasingly used for assessing physiological data. Industry 4.0 aims to achieve the real-time assessment of the workers' condition to adapt processes including the current mental workload. Mental workload can be assessed via physiological data. This paper researches the potential of wearable devices for mental workload assessment by utilizing heart rate and motion data collected with a smartwatch. A laboratory study was conducted with four levels of mental workload, ranging from none to high and during sitting and stepping activities. When sitting, a difference in the heart rate and motion data from the smartwatch was only found between no mental workload and any mental workload task. For the stepping condition, differences were found for the movement data. Based on these results, wearable devices could be useful in the future for detecting whether a mental demanding task is currently performed during low levels of physical activity.

Crossing the street in front of an autonomous vehicle: An investigation of eye contact between drivengers and vulnerable road users

Communication between road users is a major key to coordinate movement and increase roadway safety. The aim of this work was to grasp how pedestrians (Experiment A), cyclists (Experiment B), and kick scooter users (Experiment C) sought to visually communicate with drivengers when they would face autonomous vehicles (AVs). In each experiment, participants (n = 462, n = 279, and n = 202, respectively) were asked to imagine themselves in described situations of encounters between a specific type of vulnerable road user (e.g., pedestrian) and a human driver in an approaching car. The human driver state and the communicative means of the approaching car through an external Human-Machine Interface (eHMI) were manipulated between the scenarios. The participants were prompted to rate from “never” to “always” (6-point Likert scale) the frequency with which they would seek eye contact with the human driver either in order to express their willingness to cross or to make their effective decision to cross. Our findings revealed that a passive human driver in an AV with no visual checking on the road triggered a decline in vulnerable road users’ desire to communicate by eye contact (Experiments A–C). Moreover, the results of Experiment C demonstrated that the speed screen, the text message screen, and the vibrating mobile app eHMI signals diminished kick scooter users’ desire to communicate visually with the human driver, with some age-based differences. This suggested a better comprehension of the approaching car’s intentions by the kick scooter users, driven by the features of the eHMI.

Attentional Demand of Motor Speech Encoding: Evidence From Parkinson's Disease

PURPOSE

While the involvement of attention in utterance planning is well established at the conceptual and lexical levels, the attentional demands of postlexical processes are still debated. This study investigates the involvement of attentional resources on motor speech encoding during utterance production in the context of Parkinson's disease (PD), a population allowing to assess if the attentional demands observed in a dual-task paradigm (the dual-task costs [DTCs]) are explained by postlexical difficulties and not solely by executive impairment.

METHOD

Speech production was analyzed in a dual-task paradigm with 30 participants presenting with motor speech disorders due to hypokinetic dysarthria in the context of PD. The dual-task comprised an automatic speech task in which participants recited the days of the week and two nonverbal tasks evaluating processing speed and inhibition. The severity of dysarthria and performance in several executive tests (inhibition, verbal fluency, and cognitive shifting) were used as potential predictors of the DTCs.

RESULTS

Individuals with PD exhibited a DTC on the nonverbal tasks and on the speech task when the secondary task was inhibition (the most difficult one). Additionally, the severity of dysarthria and a poorer performance in cognitive shifting predicted a more severe DTC on speech rate. Finally, modulation of the magnitude of the DTCs was observed, depending on the difficulty of the nonverbal secondary task.

CONCLUSION

The results suggest that, in PD, postlexical processes require attentional resources and cognitive shifting is related to dual-task performance in speech.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.21265893.

What breaks the flow of reading? A study on characteristics of attentional disruption during digital reading

Reading is increasingly taking place on digital media, which are vectors of attentional disruption. This manuscript aims to characterize attentional disruption during reading on a computer screen in an ecological environment. To this end, we collected information relating to reader interruptions (number, type, duration, position, mental effort, and valence) and self-caught mind wandering (occurrence, position) throughout the reading session for high and low media multitaskers in their own specific ecological environment, at home. Comprehension of the narrative text was assessed both with surface and inferential questions. In total, 74 participants (M = 22.16, SD = 2.35) took part in the experiment. They reported attentional disruptions on average every 4 mins during reading. Moreover, there were more attentional disruptions during the first half of the text. Most interruptions were short and little mental effort was required to process them. We made a distinction between media-related and media-unrelated related interruptions. Multiple linear regression analyses showed that media-unrelated interruptions were actually related to better performance for both inferential and surface level questions. Furthermore, media-related interruptions were more frequent for high than low media multitaskers. Pleasure experienced when reading the text was also a significant predictor of comprehension. The results are discussed with regard to Long-Term Working Memory and strategies that the readers could have implemented to recover the thread of their reading.

Mobile electroencephalography captures differences of walking over even and uneven terrain but not of single and dual-task gait

Walking on natural terrain while performing a dual-task, such as typing on a smartphone is a common behavior. Since dual-tasking and terrain change gait characteristics, it is of interest to understand how altered gait is reflected by changes in gait-associated neural signatures. A study was performed with 64-channel electroencephalography (EEG) of healthy volunteers, which was recorded while they walked over uneven and even terrain outdoors with and without performing a concurrent task (self-paced button pressing with both thumbs). Data from n = 19 participants (M = 24 years, 13 females) were analyzed regarding gait-phase related power modulations (GPM) and gait performance (stride time and stride time-variability). GPMs changed significantly with terrain, but not with the task. Descriptively, a greater beta power decrease following right-heel strikes was observed on uneven compared to even terrain. No evidence of an interaction was observed. Beta band power reduction following the initial contact of the right foot was more pronounced on uneven than on even terrain. Stride times were longer on uneven compared to even terrain and during dual- compared to single-task gait, but no significant interaction was observed. Stride time variability increased on uneven terrain compared to even terrain but not during single- compared to dual-tasking. The results reflect that as the terrain difficulty increases, the strides become slower and more irregular, whereas a secondary task slows stride duration only. Mobile EEG captures GPM differences linked to terrain changes, suggesting that the altered gait control demands and associated cortical processes can be identified. This and further studies may help to lay the foundation for protocols assessing the cognitive demand of natural gait on the motor system.

Effects of levels of automation and non-driving related tasks on driver performance and workload: A review of literature and meta-analysis

This study assessed the effects of different levels of automation and non-driving related tasks (NDRT) on driver performance and workload. A systematic literature review was conducted in March 2021 using Compendex, Google Scholar, Web of Science, and Scopus databases. Forty-five studies met the inclusion criteria. A meta-analysis was conducted and Cochrane risk of bias tool and Cochran's Q test were used to assess risk of bias and homogeneity of the effect sizes respectively. Results suggested that drivers exhibited safer performance when dealing with critical incidents in manual driving than partially automated driving (PAD) and highly automated driving (HAD) conditions. However, drivers reported higher workload in the manual driving mode as compared to the HAD and PAD conditions. Haptic, auditory, and visual-auditory takeover request modalities are preferred over the visual-only modality to improve takeover time. Use of handheld NDRTs significantly degraded driver performance as compared to NDRTs performed on mounted devices.

User Experience and Physiological Response in Human-Robot Collaboration: A Preliminary Investigation

Within the context of Industry 4.0 and of the new emerging Industry 5.0, human factors are becoming increasingly important, especially in Human-Robot Collaboration (HRC). This paper provides a novel study focused on the human aspects involved in industrial HRC by exploring the effects of various HRC setting factors. In particular, this paper aims at investigating the impact of industrial HRC on user experience, affective state, and stress, assessed through both subjective measures (i.e., questionnaires) and objective ones (i.e., physiological signals). A collaborative assembly task was implemented with different configurations, in which the robot movement speed, the distance between the operator and the robot workspace, and the control of the task execution time were varied. Forty-two participants were involved in the study and provided feedbacks on interaction quality and their affective state. Participants’ physiological responses (i.e., electrodermal activity and heart rate) were also collected non-invasively to monitor the amount of stress generated by the interaction. Analysis of both subjective and objective responses revealed how the configuration factors considered influence them. Robot movement speed and control of the task execution time resulted to be the most influential factors. The results also showed the need for customization of HRC to improve ergonomics, both psychological and physical, and the well-being of the operator.

Chinese handwriting while driving: Effects of handwritten box size on in-vehicle information systems usability and driver distraction

OBJECTIVE

Handwritten box size (HBS) is an essential Chinese handwriting interface element when interacting with touchscreen-based in-vehicle information systems (IVISs) since it is compactly bound up with driver distraction besides usability issues. Miscellaneous HBSs are commercially available on IVISs, yet the details of how the drivers interact with them in an in-vehicle display situation remain sparsely examined. Therefore, this study set out to investigate the effects of HBS on IVISs usability (task completion time, number of errors, number of protruding strokes, and NASA-TLX, a subjective workload assessment tool) and driver distraction (mean speed, lane position variation, total glance time, number of glances, mean glance time, and number of glances exceeding 1.6 s). Ultimately, the appropriate HBS on IVISs is determined.

METHODS

A simulated driving experiment involving thirty drivers was launched. The primary task was lane-keeping with speed ranging from 40 to 60 km/h, and the secondary task was entering a 5-character text by Chinese handwriting input under five different HBS conditions: 25 × 25 mm, 30 × 30 mm, 35 × 35 mm, 40 × 40 mm, and 45 × 45 mm. A battery of one-way repeated measure analyses of variance (r-ANOVA) was used to examine which HBS can maximize IVISs usability and minimize driver distraction with the smallest HBS.

RESULTS

Generally, the issues of IVISs usability and driver distraction improved progressively as the HBS increased to a specific size (40 × 40 mm in this study), at which they got to the asymptotes. Specifically, HBS below 40 × 40 mm was associated with longer text input time, more errors and protruding strokes, extended eyes-off-road time, excessive off-road glances, and deteriorative lateral driving performance. Nevertheless, there were no significant differences in mean glance time and longitudinal driving performance. No improvement measures were observed for HBS above 40 × 40 mm, except for a higher perceived workload.

CONCLUSIONS

Overall, the appropriate HBS of in-vehicle Chinese handwriting was found to be 40 × 40 mm. Considering that the in-vehicle human-machine interface (HMI) has limited display space and increasing visual complexity, these findings may help develop evidence-based design guidelines for driver-friendly IVISs and prevent distracted-related traffic injuries.

Dual-task interference as a function of varying motor and cognitive demands

Multitasking is a critical feature of our daily lives. Using a dual-task paradigm, this experiment explored adults’ abilities to simultaneously engage in everyday motor and cognitive activities, counting while walking, under conditions varying the difficulty of each of these tasks. Motor difficulty was manipulated by having participants walk forward versus backward, and cognitive difficulty was manipulated by having participants count forward versus backward, employing either a serial 2 s or serial 3 s task. All of these manipulations were performed in single-task conditions (walk only, count only) and dual-task conditions (walk and count simultaneously). Both motor performance variables (cycle time, stride length, walking velocity) and cognitive variables (counting fluency, counting accuracy) were assessed in these conditions. Analyses of single-task conditions revealed that both motor and cognitive manipulations predictably influenced performance. Analyses of dual-task performance revealed influences of motor and cognitive factors on both motor and cognitive performance. Most centrally, dual-task costs (normalized difference between single- and dual-task conditions) for motor variables revealed that such costs occurred primarily for temporal or spatiotemporal gait parameters (cycle time, walking velocity) and were driven by cognitive manipulations. Dual-task cost analyses for cognitive measures revealed negative dual-task costs, or dual-task benefits, for cognitive performance. Finally, the effects of dual-task manipulations were correlated for motor and cognitive measures, indicating dual-task performance as a significant individual difference variable. These findings are discussed with reference to theories of attentional allocation, as well as the possible role of auditory–motor entrainment in dual-task conditions.

Effects of communication style, anthropomorphic setting and individual differences on older adults using voice assistants in a health context

Background

Voice assistants enable older adults to communicate regarding their health as well as facilitate ageing in place. This study investigated the effects of communication style, anthropomorphic setting, and individual differences on the trust, acceptance, and mental workload of older adults using a voice assistant when communicating health issues.

Methods

This is a mixed-methods study utilising both quantitative and qualitative methods. One hundred and six older adults (M = 71.8 years, SD = 4.6 years) participated in a 2 (communication style: social- vs. task-oriented; between-subject)$$\times$$ × 2 (anthropomorphic setting: ordinary profession vs. medical background; within-subject) mixed design experiment. The study used multivariate analysis of variance (MANOVA) to examine the effects of communication style, anthropomorphic setting of the voice assistant, and participants’ use frequency of digital devices on the trust, technology acceptance, and mental workload of older adults using a voice assistant in a health context. End-of-study interviews regarding voice assistant use were conducted with participants. Qualitative content analyses were used to assess the interview findings about the communication content, the more trustworthy anthropomorphic setting, and suggestions for the voice assistant.

Results

Communication style, anthropomorphic setting, and individual differences all had statistically significant effects on older adults’ evaluations of the voice assistant. Compared with a task-oriented voice assistant, older adults preferred a social-oriented voice assistant in terms of trust in ability, integrity, and technology acceptance. Older adults also had better evaluations for a voice assistant with a medical background in terms of trust in ability, integrity, technology acceptance, and mental workload. In addition, older adults with more experience using digital products provided more positive evaluations in terms of trust in ability, integrity, and technology acceptance.

Conclusions

This study suggests that when designing a voice assistant for older adults in the health context, using a social-oriented communication style and providing an anthropomorphic setting in which the voice assistant has a medical background are effective ways to improve the trust and acceptance of older adults of voice assistants in an internet-of-things environment.

Reducing passive driver fatigue through a suitable secondary motor task by means of an interactive seating system

OBJECTIVE

The primary objective of the study was to evaluate the effect of a secondary motor task induced by an interactive seating system (IASS) on passive driver fatigue in a monotonous simulated driving task. The effect was compared to that of a state-of-the-art massage seating system (MS), which may reduce monotony through additional tactile stimuli. The secondary objective was to compare the user experience of both systems.

METHOD

The independent variables were three conditions: one with the IASS, another with the MS, and a control without intervention. The study included seven dependent variables in total: a rating of subjective fatigue, three parameters measuring lane keeping ability, and three parameters reflecting fatigue-related eye movements. The duration of the simulator ride was 40 min in each condition. The study included thirty-five subjects.

RESULTS

The assessment of subjective fatigue and lane keeping showed that the use of the IASS resulted in significantly lower passive driver fatigue compared to the massage and control conditions. The alerting effects of the IASS were also reflected by an increased eyelid distance. Frequency and duration of blinks, however, showed no clear patterns of fatigue over time in any of the conditions. Thus, both parameters did not seem be suitable to capture passive driver fatigue in this study. Regarding user experience, the subjects preferred the IASS over the MS as well.

CONCLUSION

The IASS showed a strong potential as an effective measure against passive driver fatigue within monotonous driving situations. The MS, on the other hand, induced no measurable effects.

Ambient Light Conveying Reliability Improves Drivers’ Takeover Performance without Increasing Mental Workload

Drivers of L3 automated vehicles (AVs) are not required to continuously monitor the AV system. However, they must be prepared to take over when requested. Therefore, it is necessary to design an in-vehicle environment that allows drivers to adapt their levels of preparedness to the likelihood of control transition. This study evaluates ambient in-vehicle lighting that continuously communicates the current level of AV reliability, specifically on how it could influence drivers’ take-over performance and mental workload (MW). We conducted an experiment in a driving simulator with 42 participants who experienced 10 take-over requests (TORs). The experimental group experienced a four-stage ambient light display that communicated the current level of AV reliability, which was not provided to the control group. The experimental group demonstrated better take-over performance, based on lower vehicle jerks. Notably, perceived MW did not differ between the groups, and the EEG indices of MW (frontal theta power, parietal alpha power, Task–Load Index) did not differ between the groups. These findings suggest that communicating the current level of reliability using ambient light might help drivers be better prepared for TORs and perform better without increasing their MW.

On doing multi-act arithmetic: A multitrait-multimethod approach of performance dimensions in integrated multitasking

Here we present a systematic plan to the experimental study of test-retest reliability in the multitasking domain, adopting the multitrait-multimethod (MTMM) approach to evaluate the psychometric properties of performance in Düker-type speeded multiple-act mental arithmetic. These form of tasks capacitate the experimental analysis of integrated multi-step processing by combining multiple mental operations in flexible ways in the service of the overarching goal of completing the task. A particular focus was on scoring methodology, particularly measures of response speed variability. To this end, we present data of two experiments with regard to (a) test-retest reliability, (b) between-measures correlational structure, (c) and stability (test-retest practice effects). Finally, we compared participants with high versus low performance variability to assess ability-related differences in measurement precision (typically used as proxy to "simulate" patient populations), which is especially relevant in the applied fields of clinical neuropsychology. The participants performed two classic integrated multi-act arithmetic tasks, combining addition and verification (Exp. 1) and addition and comparison (Exp. 2). The results revealed excellent test-retest reliability for the standard and the variability measures. The analysis of between-measures correlational structure revealed the typical pattern of convergent and discriminant relationships, and also, that absolute response speed variability was highly correlated with average speed (r > 0.85), indicating that these measures mainly deliver redundant information. In contrast, speed-adjusted (relativized) variability revealed discriminant validity being correlated to a much lesser degree with average speed, indicating that this measure delivers additional information not already provided by the speed measure. Furthermore, speed-adjusted variability was virtually unaffected by test-retest practice, which makes this measure interesting in situations with repeated testing.

Bimodal EEG-fNIRS in Neuroergonomics. Current Evidence and Prospects for Future Research

Neuroergonomics focuses on the brain signatures and associated mental states underlying behavior to design human-machine interfaces enhancing performance in the cognitive and physical domains. Brain imaging techniques such as functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) have been considered key methods for achieving this goal. Recent research stresses the value of combining EEG and fNIRS in improving these interface systems' mental state decoding abilities, but little is known about whether these improvements generalize over different paradigms and methodologies, nor about the potentialities for using these systems in the real world. We review 33 studies comparing mental state decoding accuracy between bimodal EEG-fNIRS and unimodal EEG and fNIRS in several subdomains of neuroergonomics. In light of these studies, we also consider the challenges of exploiting wearable versions of these systems in real-world contexts. Overall the studies reviewed suggest that bimodal EEG-fNIRS outperforms unimodal EEG or fNIRS despite major differences in their conceptual and methodological aspects. Much work however remains to be done to reach practical applications of bimodal EEG-fNIRS in naturalistic conditions. We consider these points to identify aspects of bimodal EEG-fNIRS research in which progress is expected or desired.

Cognitive performance and electroencephalographic variations in air traffic controllers under various mental workload and time of day

The aim of this study was to investigate the effects of mental workload (MWL) and time of day on cognitive performance and electroencephalographic (EEG) parameters of air traffic controllers. EEG signals recorded while 20 professional air traffic controllers performed cognitive tasks [A-X Continuous Performance Test (AX-CPT) and 3-back working memory task] after they were exposed to two levels of task difficulty (high and low MWL) in the morning and afternoon. Significant decreases in cognitive performance were found when the levels of task difficulty increased in both tasks. The results confirmed the sensitivity of the theta and beta activities to levels of task difficulty in the 3-back task, while they were not affected in the AX-CPT. Theta and beta activities were influenced by time of day in the AX-CPT. The findings provide guidance for application of changes in EEG parameters when MWL level is manipulated during the day that could be implemented in future for the development of real-time monitoring systems to improve aviation safety.

Task difficulty and physiological measures of mental workload in air traffic control: a scoping review

This study provides a systematic synthesis of empirical research on mental workload (MWL) in air traffic control (ATC). MWL is a key concept in research on innovative technologies, because the assessment of MWL is crucial to the evaluation of such technologies. Our specific focus was on physiological measures of MWL. The used search strategy identified 39 peer-reviewed publications that analysed ATC tasks, examined different levels of difficulty of the ATC task, and considered at least one physiological measure of MWL. Positive relations between measures of MWL and task difficulty were observed most frequently, indicating that the measures indeed allowed the assessment of MWL. The most commonly used physiological measures were brain measures (EEG and fNIR) and heart rate measures. The review revealed a need for more precise descriptions of crucial experimental parameters in order to permit a transition of the field towards more interactive and dynamic types of analysis. Practitioner summary: Research on innovative technology in air traffic control (ATC) depends on assessments of mental workload (MWL). We reviewed empirical research on MWL in ATC. Brain and heart measures often allow assessments of MWL. Better descriptions of experiments are needed to allow comparisons among studies and more dynamic and interactive analyses.

Analysis of mental effort and its subjective and psychophysiological indicators for gas transport dispatchers

BACKGROUND: The paper presents some results of a field study concerning occupational effort in dispatchers’ activity in gas transport field. The opportunity, aim and necessity of the study resulted from the present occupational safety and health (OSH) law requirements. OBJECTIVE: The study aimed to assess the occupational effort and its indicators, in order to emphasize the risk /demand factors and to establish measures for occupational safety and health management system in order to protect the employees’ health, safety and well-being at work. METHODS: The methodology had a multidisciplinary, ergonomic character, consisting in: analysis of the work content and conditions; assessment of the effort (mental and physical) and work capacity; assessment of work fatigue. RESULTS: The results showed the levels of mental (neuropsychic) effort in the dispatchers’ studied activity, the risk factors that determine fatigue at work, and the risk factors that cannot be eliminated or reduced. CONCLUSIONS: For the dispatching activity, the occupational effort (namely its mental/neuropsychic component) is situated at a high level determined by the nature and content of the work task.

Evaluation of a New Lightweight EEG Technology for Translational Applications of Passive Brain-Computer Interfaces

Technologies like passive brain-computer interfaces (BCI) can enhance human-machine interaction. Anyhow, there are still shortcomings in terms of easiness of use, reliability, and generalizability that prevent passive-BCI from entering real-life situations. The current work aimed to technologically and methodologically design a new gel-free passive-BCI system for out-of-the-lab employment. The choice of the water-based electrodes and the design of a new lightweight headset met the need for easy-to-wear, comfortable, and highly acceptable technology. The proposed system showed high reliability in both laboratory and realistic settings, performing not significantly different from the gold standard based on gel electrodes. In both cases, the proposed system allowed effective discrimination (AUC > 0.9) between low and high levels of workload, vigilance, and stress even for high temporal resolution (<10 s). Finally, the generalizability of the proposed system has been tested through a cross-task calibration. The system calibrated with the data recorded during the laboratory tasks was able to discriminate the targeted human factors during the realistic task reaching AUC values higher than 0.8 at 40 s of temporal resolution in case of vigilance and workload, and 20 s of temporal resolution for the stress monitoring. These results pave the way for ecologic use of the system, where calibration data of the realistic task are difficult to obtain.

Danger, high voltage! Using EEG and EOG measurements for cognitive overload detection in a simulated industrial context

Industrial settings will be characterized by far-reaching production automation brought about by advancements in robotics and artificial intelligence. As a consequence, human assembly workers will need to adapt quickly to new and more complex assembly procedures, which are most likely to increase cognitive workload, or potentially induce overload. Measurement and optimization protocols need to be developed in order to be able to monitor workers' cognitive load. Previous studies have used electroencephalographic (EEG, measuring brain activity) and electrooculographic (EOG, measuring eye movements) signals, using basic computer-based static tasks and without creating an experience of overload. In this study, EEG and EOG data was collected of 46 participants performing an ecologically valid assembly task while inducing three levels of cognitive load (low, high and overload). The lower individual alpha frequency (IAF) was identified as a promising marker for discriminating between different levels of cognitive load and overload.

Visual Demands of Walking Are Reflected in Eye-Blink-Evoked EEG-Activity

Blinking is a natural user-induced response which paces visual information processing. This study investigates whether blinks are viable for segmenting continuous electroencephalography (EEG) activity, for inferring cognitive demands in ecologically valid work environments. We report the blink-related EEG measures of participants who performed auditory tasks either standing, walking on grass, or whilst completing an obstacle course. Blink-related EEG activity discriminated between different levels of cognitive demand during walking. Both behavioral parameters (e.g., blink duration or head motion) and blink-related EEG activity varied with walking conditions. Larger occipital N1 was observed during walking, relative to standing and traversing an obstacle course, which reflects differences in bottom-up visual perception. In contrast, the amplitudes of top-down components (N2, P3) significantly decreased with increasing walking demands, which reflected narrowing attention. This is consistent with blink-related EEG, specifically in Theta and Alpha power that, respectively, increased and decreased with increasing demands of the walking task. This work presents a novel and robust analytical approach to evaluate the cognitive demands experienced in natural work settings, which precludes the use of artificial task manipulations for data segmentation.

Development of a Methodology for Assessing Workload within the Air Traffic Control Environment in the Czech Republic

The increase in civil aviation traffic and, in general, in aviation traffic going through airspace or a military terminal control area, and the increase in military operations in temporarily reserved areas bring higher requirements for airspace throughput and for the workload of military air traffic controllers. For an objective assessment of the military air traffic controllers’ workload, it is desirable to set the maximum level of workload that can be required of such personnel. This assessment is also important for planning staffing and training. In the civil air traffic control environment, the workload of air traffic controllers is clearly determined by the complexity and density of air traffic, i.e., the throughput capacity of sectors. However, this method is not suitable for measuring the workload of military air traffic controllers, because the nature of military flight activities requires solving different situations in the airspace and thus generates a different workload. One way of obtaining more objective data on the actual workload of military air traffic controllers is to accurately determine the difficulty of individual air traffic control activities, i.e., the most common activities carried out by military air traffic controllers in the course of their duty. The difficulty of a selected air traffic control activity will be represented by a weight. A method for determining this weight is presented, including the proposal of specific weights for the calculation of the military air traffic controllers’ workload during simulation training, using the functionality “Workload”.

Multimodal Natural Human–Computer Interfaces for Computer-Aided Design: A Review Paper

Computer-aided design (CAD) systems have advanced to become a critical tool in product design. Nevertheless, they still primarily rely on the traditional mouse and keyboard interface. This limits the naturalness and intuitiveness of the 3D modeling process. Recently, a multimodal human–computer interface (HCI) has been proposed as the next-generation interaction paradigm. Widening the use of a multimodal HCI provides new opportunities for realizing natural interactions in 3D modeling. In this study, we conducted a literature review of a multimodal HCI for CAD to summarize the state-of-the-art research and establish a solid foundation for future research. We explore and categorize the requirements for natural HCIs and discuss paradigms for their implementation in CAD. Following this, factors to evaluate the system performance and user experience of a natural HCI are summarized and analyzed. We conclude by discussing challenges and key research directions for a natural HCI in product design to inspire future studies.

Designing for Confidence: The Impact of Visualizing Artificial Intelligence Decisions

Explainable artificial intelligence aims to bring transparency to artificial intelligence (AI) systems by translating, simplifying, and visualizing its decisions. While society remains skeptical about AI systems, studies show that transparent and explainable AI systems can help improve the Human-AI trust relationship. This manuscript presents two studies that assess three AI decision visualization attribution models that manipulate morphological clarity (MC) and two information presentation-order methods to determine each visualization’s impact on the Human-AI trust relationship through increased confidence and cognitive fit (CF). The first study, N = 206 (Avg. age = 37.87 ± 10.51, Male = 123), utilized information presentation methods and visualizations delivered through an online experiment to explore trust in AI by asking participants to complete a visual decision-making task. The second study, N = 19 (24.9 ± 8.3 years old, Male = 10), utilized eye-tracking technology and the same stimuli presentation methods to investigate if cognitive load, inferred through pupillometry measures, mediated the confidence-trust relationship. The results indicate that low MC positively impacts Human-AI trust and that the presentation order of information within an interface in terms of adjacency further influences user trust in AI. We conclude that while adjacency and MC significantly affect cognitive load, cognitive load alone does not mediate the confidence-trust relationship. Our findings interpreted through a combination of CF, situation awareness, and ecological interface design have implications for the design of future AI systems, which may facilitate better collaboration between humans and AI-based decision agents.

Frontal, Sensorimotor, and Posterior Parietal Regions Are Involved in Dual-Task Walking After Stroke

Background

Walking within the community requires the ability to walk while simultaneously completing other tasks. After a stroke, completing an additional task while walking is significantly impaired, and it is unclear how the functional activity of the brain may impact this.

Methods

Twenty individual in the chronic stage post-stroke participated in this study. Functional near-infrared spectroscopy (fNIRS) was used to measure prefrontal, pre-motor, sensorimotor, and posterior parietal cortices during walking and walking while completing secondary verbal tasks of varying difficulty. Changes in brain activity during these tasks were measured and relationships were accessed between brain activation changes and cognitive or motor abilities.

Results

Significantly larger activations were found for prefrontal, pre-motor, and posterior parietal cortices during dual-task walking. Increasing dual-task walking challenge did not result in an increase in brain activation in these regions. Higher general cognition related to lower increases in activation during the easier dual-task. With the harder dual-task, a trend was also found for higher activation and less motor impairment.

Conclusions

This is the first study to show that executive function, motor preparation/planning, and sensorimotor integration areas are all important for dual-task walking post-stroke. A lack of further brain activation increase with increasing challenge suggests a point at which a trade-off between brain activation and performance occurs. Further research is needed to determine if training would result in further increases in brain activity or improved performance.

Human Mental Workload: A Survey and a Novel Inclusive Definition

Human mental workload is arguably the most invoked multidimensional construct in Human Factors and Ergonomics, getting momentum also in Neuroscience and Neuroergonomics. Uncertainties exist in its characterization, motivating the design and development of computational models, thus recently and actively receiving support from the discipline of Computer Science. However, its role in human performance prediction is assured. This work is aimed at providing a synthesis of the current state of the art in human mental workload assessment through considerations, definitions, measurement techniques as well as applications, Findings suggest that, despite an increasing number of associated research works, a single, reliable and generally applicable framework for mental workload research does not yet appear fully established. One reason for this gap is the existence of a wide swath of operational definitions, built upon different theoretical assumptions which are rarely examined collectively. A second reason is that the three main classes of measures, which are self-report, task performance, and physiological indices, have been used in isolation or in pairs, but more rarely in conjunction all together. Multiple definitions complement each another and we propose a novel inclusive definition of mental workload to support the next generation of empirical-based research. Similarly, by comprehensively employing physiological, task-performance, and self-report measures, more robust assessments of mental workload can be achieved.

Subjective and objective assessments of mental workload for UAV operations

BACKGROUND

Unmanned Aerial Vehicles (UAVs) have created safety problems for the publics. Assessments of the mental workload for UAV operations are essential to realize the causes of UAV accidents.

OBJECTIVE

To test the following hypotheses: i. mission difficulty in UAV operation affects both subjective and objective measures of mental workload; ii. mission difficulty affects number of failures in UAV operation.

METHODS

Fourteen male adults participated as UAV operators after attending a UAV training course. They performed four flight missions of different difficulty levels. During their flight missions, their heart rate and inter-beat interval (IBI) were collected. Upon completing each flight mission, the participants gave subjective ratings of mental workload using three commonly adopted assessment tools. The time of flight and number of failures in flight operations were also recorded.

RESULTS

The results showed that mission difficulty affected the scores of all three assessment tools significantly. Mission difficulty also affected number of failures and IBI significantly. The scores of the three assessment tools were highly correlated (ρ= 0.7 to 0.83, p < 0.001) with one another. The results of the three subjective ratings were also consistent with that of the IBI data.

CONCLUSIONS

High mental workload in UAV operation could lead to poor flight performance.

The Cycling Brain in the Workplace: Does Workload Modulate the Menstrual Cycle Effect on Cognition?

Recent decades have witnessed increased research efforts to clarify how the menstrual cycle influence females’ cognitive and emotional functions. Despite noticeable progress, the research field faces the challenges of inconsistency and low generalizability of research findings. Females of reproductive ages are a heterogeneous population. Generalizing the results of female undergraduates to women in the workplace might be problematic. Furthermore, the critical cognitive processes for daily life and work deserve additional research efforts for improved ecological validity. Thus, this study investigates cognitive performance across the menstrual cycle using a sample of young nurses with similar duties. We developed a mini-computerized cognitive battery to assess four mental skills critical for nursing work: cognitive flexibility, divided attention, response inhibition, and working memory. Participants completed the cognitive battery at menses, late-follicular, and mid-luteal phases. In addition, they were classified into low- and high workload groups according to their subjective workload ratings. Our results demonstrate a general mid-luteal cognitive advantage. Besides, this study reveals preliminary evidence that workload modulates the menstrual cycle effect on cognition. Only females of low workload manifest the mid-luteal cognitive advantage on divided attention and response inhibition, implying that a suitable workload threshold might be necessary for regular neuro-steroid interactions. Thus, this study advocates the significance of research focusing on the cycling brain under workloads.

Cognitive inhibition tasks interfere with dual-task walking and increase prefrontal cortical activity more than working memory tasks in young and older adults

BACKGROUND

Prior work suggests there may be greater reliance on executive function for walking in older people. The pre-frontal cortex (PFC), which controls aspects of executive function, is known to be active during dual-task walking (DTW). However, there is debate on how PFC activity during DTW is impacted by ageing and the requirements of the cognitive task.

RESEARCH QUESTION

Functional near infrared spectroscopy, was used to investigate how PFC activity during walking was affected by (i) healthy ageing; and (ii) dual-tasks that utilise inhibition or working memory aspects of executive function.

METHODS

Young (n = 26, 16 females, mean 20.9 years) and older (n = 26, 16 females, mean 70.3 years) adults performed five conditions: normal walking; Reciting Alternate Letters of the alphabet (RAL, requiring cognitive inhibition and working memory) during standing and walking; and serial subtraction by threes (SS3, requiring working memory alone) during standing and walking. Walking speed, cognitive performance, the PFC haemodynamic response, and fear of falling ratings were analysed using linear mixed-effects modelling.

RESULTS

Compared to quiet standing, PFC activity increased during normal walking for older adults but decreased for young adults (p < 0.01). Across both groups, fear of falling contributed to higher PFC activity levels when walking (p < 0.01). PFC activity increased during DTW, and this increase was greater when performing RAL compared to the SS3 task (p < 0.01). Although the rate of correct responses was higher for RAL, walking speed reduced more with RAL than SS3 in the young group (p = 0.01), and the rate of correct responses reduced more when walking with RAL than SS3 in the older group (p < 0.01).

SIGNIFICANCE

Older adults have increased levels of PFC activation during walking compared to younger adults and fear of falling is a cofounding factor. The interference between gait and a concurrent cognitive task is higher when the cognitive task requires inhibition.

Conflict monitoring or multi-tasking? Tracking within-task performance in single-item and multi-item Stroop tasks

Cognitive control is applied in situations that require overriding a habitual and automatic response. The conflict monitoring hypothesis and the Expected Value of Control (EVC) theory as its extension posit a control system responsible for detecting conflicting occasions and adapting to them dynamically within a task. Here we evaluate this prediction in two versions of one of the most popular tasks in cognitive control, namely the Stroop task. We hypothesized that nearby-items interference combines with task interference in the multi-item version effectively turning it into a multi-task that may challenge cognitive control. Adopting an alternative methodology tracking within-task performance, we compared the classical multi-item version of the Stroop task and its single-item counterpart in adults and children. The results revealed a within-task performance decline only in the multi-item version of the task, in both incongruent and neutral conditions, modulated by the presumed maturity of the control system. These findings suggest capacity constraints in control implementation and allocation under conditions requiring parallel execution of multiple cognitive tasks. Task complexity and demands seem to modulate effects on performance. We discuss implications for cognitive control as well as substantial concerns regarding the calculation and use of indices of interference based on the commonly used multi-item version of the Stroop task.

Design of Proactive Interaction for In-Vehicle Robots Based on Transparency

Based on the transparency theory, this study investigates the appropriate amount of transparency information expressed by the in-vehicle robot under two channels of voice and visual in a proactive interaction scenario. The experiments are to test and evaluate different transparency levels and combinations of information in different channels of the in-vehicle robot, based on a driving simulator to collect subjective and objective data, which focuses on users' safety, usability, trust, and emotion dimensions under driving conditions. The results show that appropriate transparency expression is able to improve drivers' driving control and subjective evaluation and that drivers need a different amount of transparency information in different types of tasks.

Affective Response Categories—Toward Personalized Reactions in Affect-Adaptive Tutoring Systems

Affect-adaptive tutoring systems detect the current emotional state of the learner and are capable of adequately responding by adapting the learning experience. Adaptations could be employed to manipulate the emotional state in a direction favorable to the learning process; for example, contextual help can be offered to mitigate frustration, or lesson plans can be accelerated to avoid boredom. Safety-critical situations, in which wrong decisions and behaviors can have fatal consequences, may particularly benefit from affect-adaptive tutoring systems, because accounting for affecting responses during training may help develop coping strategies and improve resilience. Effective adaptation, however, can only be accomplished when knowing which emotions benefit high learning performance in such systems. The results of preliminary studies indicate interindividual differences in the relationship between emotion and performance that require consideration by an affect-adaptive system. To that end, this article introduces the concept of Affective Response Categories (ARCs) that can be used to categorize learners based on their emotion-performance relationship. In an experimental study, N = 50 subjects (33% female, 19–57 years, M = 32.75, SD = 9.8) performed a simulated airspace surveillance task. Emotional valence was detected using facial expression analysis, and pupil diameters were used to indicate emotional arousal. A cluster analysis was performed to group subjects into ARCs based on their individual correlations of valence and performance as well as arousal and performance. Three different clusters were identified, one of which showed no correlations between emotion and performance. The performance of subjects in the other two clusters benefitted from negative arousal and differed only in the valence-performance correlation, which was positive or negative. Based on the identified clusters, the initial ARC model was revised. We then discuss the resulting model, outline future research, and derive implications for the larger context of the field of adaptive tutoring systems. Furthermore, potential benefits of the proposed concept are discussed and ethical issues are identified and addressed.