Simulators are pivotal in advancing mobility technology, yet human adaptation in the context of these technologies remains underexplored. This study investigates the role of core executive functions (working memory, inhibitory control, and cognitive flexibility) in adaptive performance within driving simulators based on a scoping review identifying a research gap and conducting a driving simulator study addressing it. Results from the empirical study revealed no significant influence of working memory or inhibitory control, while cognitive flexibility showed a partial positive effect, highlighting its possible enhancing role in adapting to coordinative changes within simulated environments. Findings expand the scarce literature and underscore the need for further exploration, e.g., of how change complexity moderates these relationships. By differentiating executive functions and linking them to adaptive performance, this work advances the theoretical understanding of adaptation in the context of emerging technology. Furthermore, it may inform future research on potential training approaches targeting cognitive flexibility.
Individual differences in cognitive abilities may influence how people form and adjust trust in automated systems, yet the mechanisms underlying this relationship remain poorly understood. This study investigated how three foundational cognitive abilities — working memory (WM), attention control (AC), and fluid intelligence (Gf) — shape trust dynamics, particularly focusing on trust decline and recovery after automation failures. Participants (N = 111) completed cognitive tests measuring WM, AC, and Gf before performing a dual-task paradigm where they monitored an automated memory aid exhibiting varying reliability levels (100%-65%-100%) while completing an arithmetic task. Results revealed that WM and Gf positively predicted trust recovery after automation failures, while AC influenced long-term trust calibration, with high-AC individuals showing more nuanced trust adjustments reflecting system reliability history. Trust decline was uniform across ability levels, suggesting that trust loss may occur rapidly after salient failures. The relationship between abilities and trust may have been partially mediated by automation schemas, with WM negatively correlating with all-or-none thinking about automation. These findings suggest different cognitive abilities play distinct roles in trust dynamics: WM supports monitoring automation performance, Gf enables effective schema updating, and AC facilitates appropriate deployment of these resources for trust calibration. This work advances our understanding of trust mechanisms and has implications for designing automation interfaces that accommodate individual cognitive differences.
This study investigated the utility of heart rate variability (HRV) metrics derived from electrocardiogram (ECG) signals for assessing motion sickness (MS) during real-world driving. While motion sickness is commonly evaluated through subjective reports or multimodal physiological measurements, previous studies have predominantly relied on simulator-based experiments or multimodal physiological sensing, which limit ecological validity and practical deployment in everyday vehicles. In this study, twenty-four female participants were exposed to systematically varied acceleration and deceleration profiles across 13 predefined driving conditions in an electric vehicle. Motion sickness symptoms were measured using the Misery Scale (MISC), and ECG data were segmented into 120-s epochs to extract heart rate, the low-frequency to high-frequency (LF/HF) ratio, and pNN50 (the percentage of successive normal-to-normal intervals differing by more than 50 ms). Using a threshold corresponding to symptom onset (MISC of 2 or above), pNN50 was significantly lower in the high-MS group than in the low-MS group (16.5% versus 24.6%, p < 0.001, Cohen's d = −0.53), indicating reduced parasympathetic (vagal) modulation in the presence of motion sickness symptoms. Heart rate did not differ significantly between groups, and the LF/HF ratio showed a statistically significant but negligible difference. Mean pNN50 values did not, however, decline monotonically across individual MISC scores, indicating that the metric distinguishes the presence of symptoms rather than grading their severity. These findings suggest that pNN50 is the most sensitive of the examined HRV indices and may reflect individual differences in susceptibility to motion sickness. The study demonstrates that motion sickness can be assessed using a single, widely accessible physiological signal such as ECG, providing a foundation for future wearable and in-vehicle motion sickness monitoring systems.
Studies suggest that computer workers may benefit from cycling workstations; however, little is known about the sex-specific mechanistic impacts of cycling on computer work-related risk factors. Twenty-six computer users (14 females) underwent two 60-min sessions of typing: one sitting, and one lightly cycling, while performance, symptoms and electromyography were recorded. Results show that males' typing speed was lower during cycling than sitting, while females' performance remained similar between conditions (Sex × Condition, p = 0.029). Neck/shoulder and visual discomfort were lower during cycling for both sexes, with females experiencing less neck/shoulder discomfort than males (Sex × Condition × Time, p = 0.006). Neck/shoulder muscle activation increased with time during sitting but decreased during cycling, especially in females. Low back muscle activity was higher during cycling, particularly in females (Sex × Condition × Time interaction, p = 0.046). Findings suggest sex-specific responses to cycling during computer work.
