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EEG-based cognitive load estimation during the use of a virtual wheelchair simulator

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Introduction Driving a powered wheelchair is a complex task that requires the integration of motor, visual, and cognitive skills. The development of assistive technologies without appropriate assessment methods that help bridge the gap between users and developers may lead to abandonment and reduced engagement. Most assessments rely on explicit measures, such as performance metrics, or subjective tools like interviews and questionnaires. In contrast, implicit measures allow continuous inference of mental states during task execution. This study proposes the use of blink indices derived from electroencephalographic (EEG) signals as implicit metrics to estimate cognitive load during the use of a virtual reality wheelchair training simulator. Methods A total of 25 participants (14 females and 11 males; mean age 26.50 ± 5.7 years) completed a predefined route using a virtual wheelchair simulator. Blink parameters, including frequency, duration, and velocity, were extracted from EEG signals during task performance. After completing the simulation, participants responded to the NASA Task Load Index (NASA-TLX) to assess subjective cognitive load, as well as the System Usability Scale (SUS) and the Igroup Presence Questionnaire (IPQ). Results The findings showed that higher mental-visual demand was associated with decreases in blink frequency, duration, and velocity. Correlation analyses between NASA-TLX scores and blink parameters revealed weak to moderate associations. These results suggest partial convergence between subjective and physiological measures of cognitive load. Discussion Blink-based indices derived from EEG signals provide relevant information regarding cognitive demand during wheelchair simulator use. However, blink parameters alone are insufficient to reliably infer cognitive load. When combined with subjective questionnaires, implicit physiological metrics may offer a more comprehensive assessment than questionnaires alone, supporting the development and refinement of assistive training technologies.

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Ensuring human safety has been one of the most critical considerations within the field of human–robot interaction. To explore the effects of working with autonomous robots on human coworkers’ perceived workload and job performance, two experiments were conducted in this study. Eight participants were recruited in the first experiment. Results revealed an increase in both subjective and objective workload measurements: compared to the baseline “no robot” to “empty payload” condition, the sum of NASA Task Load Index (NASA-TLX) scores increased from 129.3 (58.8) to 147.6 (53.7) ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$p$</tex-math></inline-formula> -value = 0.041) and the pupil diameter increased from 4.07 (0.64) mm to 4.11 (0.67) mm; while working with a full payload robot, the sum of NASA-TLX scores increased to 151.7 (55.9) ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$p$</tex-math></inline-formula> -value = 0.010) and the pupil diameter increased to 4.12 (0.66) mm. Increased task completion time (3.1% for empty payload condition and 6.6% for full payload condition) showed a decrease in human productivity. However, this slight human output reduction was compensated by the substantial gain from the robot. Similar effects of autonomous mobile robots on participants’ NASA-TLX scores and task completion time were observed in the second experiment, where eight participants performed the order picking and sorting tasks in a high-fidelity grocery store setting. Results from the study suggested the feasibility of applying fully autonomous mobile robots in Wholesale and Retail Trade settings to improve human–robot team productivity while prioritizing physical safety and reasonable increases in mental workload.

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Carga cognitiva e sua correlação com piscadas durante o uso de um simulador de cadeira de rodas
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Driving a wheelchair is difficult and complex, where it requires motor, visual and cognitive skills. There are simulators aimed mainly at users without or with little experience of using this assistive technology as a form of safe training. However, the real wheelchair and the simulator need to be developed or improved so that the users feel adapted and motivated to use them. Developing technologies to assist people without using assessments that help to understand and bring users closer to developers leads to giving up and discouraging the use of these tools. Many of these assessments are made using subjective metrics, such as interviews or questionnaires; and objective metrics are often related to user performance. Generally, these subjective metrics are classified as explicit, which are the responses that the user is aware of. These metrics can often not reflect people’s genuine opinions and feelings. In contrast, implicit measures infer mental content based on tasks, that can be evaluated continuously while the task is being performed. In this perspective, the present work aimed to assess the cognitive load during the use of the virtual reality training tool, the wheelchair simulator. The study proposes the use of implicit metrics, specifically, the blink indexes derived from an EEG signal. In summary, the study analysed implicit and explicit metrics of a task performed in the wheelchair simulator in a virtual environment. The explicit metrics were derived from questionnaires on usability, presence, cognitive load and performance. The implicit metrics, on the other hand, were the characteristics of the frequency, duration and velocity of the blinks collected during the experiment. The results were consistent with the reports found in the literature, where, the cognitive load that requires a mental-visual demand is related to the decrease in the frequency, duration and velocity of the blink. The results of the correlation analyses between the NASA-TLX scores (subjective cognitive load assessment) and the blink parameters were moderate and weak. Thus, at the moment, for the application presented, it is concluded that evaluating only the blinks is not enough to infer the cognitive load, however it is a metric that applied in conjunction with questionnaires can show more relevant information than just the application of questionnaires.

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  • Research Article
  • Cite Count Icon 26
  • 10.1111/iju.14315
Development and validation of a porcine organ model for training in essential laparoscopic surgical skills.
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ObjectivesTo develop a wet laboratory training model for learning core laparoscopic surgical skills and evaluating learners’ competency level outside the operating room.MethodsParticipants completed three tasks (task 1: tissue dissection around the aorta; task 2: tissue dissection and division of the renal artery; task 3: renal parenchymal closure). Each performance was video recorded and subsequently evaluated by two experts, according to the Global Operative Assessment of Laparoscopic Skills and task‐specific metrics that we developed (Assessment Sheet of Laparoscopic Skills in Wet Lab score). Mean scores were used for analyses. The subjective mental workload was also assessed (NASA Task Load Index).ResultsThe 54 participants included 32 urologists, eight young trainees and 14 medical students. A total of 13 participants were categorized as experts (≥50 laparoscopic surgeries), eight as intermediates (10–49) and 33 as novices (0–9). There were significant differences in the Global Operative Assessment of Laparoscopic Skills and Assessment Sheet of Laparoscopic Skills in Wet Lab scores among the three groups in all three tasks. Higher NASA Task Load Index scores were observed in novices, and there were significant differences in tasks 1 (Kruskal–Wallis test, P = 0.0004) and 2 (P = 0.0002), and marginal differences in task 3 (P = 0.0745) among the three groups.ConclusionsOur training model has good construct validity, and differences in the NASA Task Load Index score reflect previous laparoscopic surgical experiences. Our findings show the ability to assess both laparoscopic surgical skills and mental workloads, which could help educators comprehend trainees’ level outside the operating room. Given the decreasing opportunity to carry out pure laparoscopic surgeries because of the dissemination of robotic surgery, especially in urology, our model can offer practical training opportunities.

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