Workload Assessment of Human-Machine Interface: A Simulator Study with Psychophysiological Measures

To assess the sensitivity of two physiological measures for discriminating between levels of cognitive demand under driving conditions across different age groups. Previous driving research presents a mixed picture concerning the sensitivity of physiological measures for differentiating tasks with presumed differences in mental workload. A total of 108 relatively healthy drivers balanced by gender and across three age groups (20-29, 40-49, 60-69) engaged in three difficulty levels of an auditory presentation-verbal response working memory task. Heart rate and skin conductance level (SCL) both increased in a statistically significant fashion with each incremental increase in cognitive demand, whereas driving performance measures did not provide incremental discrimination. SCL was lower in the 40s and 60s age groups; however, the pattern of incremental increase with higher demand was consistent for heart rate and SCL across all age groups. Although each measure was quite sensitive at the group level, considering both SCL and heart rate improved detection of periods of heightened cognitive demand at the individual level. The data provide clear evidence that two basic physiological measures can be utilized under field conditions to differentiate multiple levels of objectively defined changes in cognitive demand. Methodological considerations, including task engagement, may account for some of the inconsistencies in previous research. These findings increase the confidence with which these measures may be applied to assess relative differences in mental workload when developing and optimizing human machine interface (HMI) designs and in exploring their potential role in advanced workload detection and augmented cognition systems.

ABSTRACTTouchscreen human–machine interfaces (HMIs) are commonly employed as the primary control interface and touch-point of vehicles. However, there has been very little theoretical work to model the demand associated with such devices in the automotive domain. Instead, touchscreen HMIs intended for deployment within vehicles tend to undergo time-consuming and expensive empirical testing and user trials, typically requiring fully functioning prototypes, test rigs, and extensive experimental protocols. While such testing is invaluable and must remain within the normal design/development cycle, there are clear benefits, both fiscal and practical, to the theoretical modeling of human performance. We describe the development of a preliminary model of human performance that makes a priori predictions of the visual demand (total glance time, number of glances, and mean glance duration) elicited by in-vehicle touchscreen HMI designs, when used concurrently with driving. The model incorporates information theoretic components based on Hick–Hyman Law decision/search time and Fitts’ Law pointing time and considers anticipation afforded by structuring and repeated exposure to an interface. Encouraging validation results, obtained by applying the model to a real-world prototype touchscreen HMI, suggest that it may provide an effective design and evaluation tool, capable of making valuable predictions regarding the limits of visual demand/performance associated with in-vehicle HMIs, much earlier in the design cycle than traditional design evaluation techniques. Further validation work is required to explore the behavior associated with more complex tasks requiring multiple screen interactions, as well as other HMI design elements and interaction techniques. Results are discussed in the context of facilitating the design of in-vehicle touchscreen HMI to minimize visual demand.

The current paper presents the results of the evaluation of a novel human machine interface for supervision and guidance of multiple highly automated unmanned aircraft. Accidents of unmanned aircraft are often related to deficiencies in the design of the human machine interface. Many of these deficiencies are a consequence of insufficient consideration of human factors engineering principles in the early stages of system development. Therefore, in the design of the current human machine interface, empirically validated human factors methods were applied in order to optimally support a remote pilot in supervising and guiding multiple highly automated unmanned aircraft. An information management concept was developed that allows for an increase in the number of UAS that are being supervised without considerably increasing display complexity. In order to evaluate the human machine interface, two within-subj ect simulation studies were conducted. In both studies, pilots were asked to supervise and guide a varying number of UAS in several experimental scenarios using the new human machine interface. Following the experimental scenarios, a structured interview regarding the design of the human machine interface was conducted. The objective of the first study was to gather initial data on the general usability of the interface. The aim of the second simulation study was to investigate how increasing the number of UAS from one up to five affects the time that a pilot needs to acquire and change specific system parameters of any UAS under supervision. Further, the impact of increasing the number of UAS on pilot workload and situation awareness was assessed. The results of the interviews suggest that the design concept of the human machine interface is feasible and easy to understand. The information management concept was described as reasonable and logical. Important information was accessible quickly and (critical) system states could easily be identified. No significant effects of increasing the number of UASs to be supervised on reaction, workload or situation awareness were observed. The findings suggest that the information management concept is reasonable and usable.

Modeling and predicting age differences in driver mental workload and performance may help the in-vehicle system design to reduce or prevent information overloading on older drivers. However, few computational models exist that account for age differences in mental workload. We propose a new computational modeling approach to model workload and performance–a queuing network approach based on queuing network theory of human performance (Liu, 1996, 1997) and neuroscience discoveries. This modeling approach is composed of a simulation model of a queuing network architecture and a set of mathematical equations implemented in the simulation model to quantify the age differences. The model successfully accounts for the age differences in mental workload and performance between young and older drivers in an experimental study in driving. Further usage and implementation of this model in designing adaptive in-vehicle systems to assist older drivers are discussed.

Environmental noise may interfere with the reading experience by increasing cognitive load and psychophysiological arousal, yet these effects are difficult to perceive and communicate in real time. This study presents Reading Noise, an interactive installation that combines physiological sensing and sound-driven visualization to externalize perceived noise-related disturbance and psychophysiological strain during reading. In a controlled experiment, 46 participants completed reading tasks under four levels of background conversational noise (0–30, 31–60, 61–90, and >90 dB) while ambient sound level, electrodermal activity (EDA), and electrocardiogram (ECG) were recorded in real time. Following data quality screening, inferential statistical analyses were performed on the analyzable physiological subset (n = 16). Based on these data, a hybrid mapping strategy combining rule-based assignment and LMM-informed exploratory calibration was developed to map acoustic and physiological changes onto dynamic text-based visual parameters, including deformation intensity, jitter, and motion instability, for real-time feedback. Within the analyzable subset, noise level was associated with significant changes in the recorded physiological indicators (all p < 0.05): skin conductance level (SCL) and skin conductance responses per minute (SCRs/min) increased (4.69 ± 2.13 to 5.93 ± 2.19 μS; 1.49 ± 1.59 to 2.51 ± 2.13), whereas the percentage of successive RR intervals differing by more than 50 ms (pNN50) and the root mean square of successive differences (RMSSD) decreased (15.84 ± 16.52% to 10.57 ± 11.35%; 36.63 ± 17.62 to 29.67 ± 16.66 ms). Subjective cognitive load also increased significantly (2.06 ± 0.29 to 6.38 ± 0.31). A follow-up installation study with 24 cross-disciplinary participants, with reported group interaction observations drawn from a 12-participant subset, suggested that the installation may facilitate shared interpretation of attention-related disruption and cognitive strain, indicating the potential of physiology-informed visual translation as a boundary object approach for empathetic, sound-mediated communication.

Evaluation of physiological responses to mental workload in n-back and arithmetic tasks

The objective of this study was to test the feasibility of using wearable sensors and wireless technology to measure the autonomic function and stress level in the ambulatory setting. Autonomic function was studied acquiring ECG tracings by means of a wearable sensorized chest strap. Galvanic skin response (GSR) was measured as an indicator of stress level by two electrodes positioned on the palm of the non dominant hand and a wireless acquisition module in a wrist support. Data were acquired in a group of young adolescents with anorexia nervosa (AN) as compared to controls in resting conditions. From ECG the tachogram, the mean RR intervals (meanRR), the root mean square of successive differences (RMSSD) the power of low frequency (LF) and high frequency (HF) bands and the LF/HF ratio were assessed. From GSR mean, median, variance, standard deviation, area under the curve of the sampled signal and delta between maximum and minimum conductance values were computed. All AN patients showed reduced HR and increased meanRR and RMSSD. HF increase, LF decrease and LF/HF reduction were suggestive of prevalence of parasympathetic over sympathetic activity. Additionally, AN showed a decreased GSR variance, standard deviation and delta value with respect to controls. The results of this study show that wearable sensors used in this study were feasible, unobtrusive and therefore extremely suitable for young patients providing the means for future monitoring in the home setting which may be preferable in this population burdened by high cardiovascular morbidity and mortality.

A-123 Problem Solving and Mental Workload in Binge and Non-Binge Drinking College Students

ObjectivesIn order to investigate the applicability of routine 10s electrocardiogram (ECG) recordings for time-domain heart rate variability (HRV) calculation we explored to what extent these (ultra-)short recordings capture the “actual” HRV.MethodsThe standard deviation of normal-to-normal intervals (SDNN) and the root mean square of successive differences (RMSSD) were measured in 3,387 adults. SDNN and RMSSD were assessed from (ultra)short recordings of 10s(3x), 30s, and 120s and compared to 240s–300s (gold standard) measurements. Pearson’s correlation coefficients (r), Bland-Altman 95% limits of agreement and Cohen’s d statistics were used as agreement analysis techniques.ResultsAgreement between the separate 10s recordings and the 240s-300s recording was already substantial (r = 0.758–0.764/Bias = 0.398–0.416/d = 0.855–0.894 for SDNN; r = 0.853–0.862/Bias = 0.079–0.096/d = 0.150–0.171 for RMSSD), and improved further when three 10s periods were averaged (r = 0.863/Bias = 0.406/d = 0.874 for SDNN; r = 0.941/Bias = 0.088/d = 0.167 for RMSSD). Agreement increased with recording length and reached near perfect agreement at 120s (r = 0.956/Bias = 0.064/d = 0.137 for SDNN; r = 0.986/Bias = 0.014/d = 0.027 for RMSSD). For all recording lengths and agreement measures, RMSSD outperformed SDNN.ConclusionsOur results confirm that it is unnecessary to use recordings longer than 120s to obtain accurate measures of RMSSD and SDNN in the time domain. Even a single 10s (standard ECG) recording yields a valid RMSSD measurement, although an average over multiple 10s ECGs is preferable. For SDNN we would recommend either 30s or multiple 10s ECGs. Future research projects using time-domain HRV parameters, e.g. genetic epidemiological studies, could calculate HRV from (ultra-)short ECGs enabling such projects to be performed at a large scale.

PURPOSE: The purpose of this study is to investigate the effect of the physical therapy treatment room environment using microwave diathermy on the autonomic nervous system of human body. METHODS: Participants were 24 healthy adults. Standard deviation of all normal R-R intervals(SDNN), root mean square of successive differences(RMSSD), low frequency(LF), high frequency(HF), LF/HF ratio were compared in microwave irradiation and non-irradiation group. Data were analyzed in Wilcoxon's signed-ranks test and Mann-Whitney U test. RESULTS: Standard deviation of all normal R-R intervals (SDNN), root mean square of successive differences (RMSSD), low frequency(LF), high frequency(HF), LF/HF ratio were not significantly different in microwave irradiation group. Standard deviation of all normal R-R intervals(SDNN), root mean square of successive differences (RMSSD), low frequency(LF), high frequency(HF), LF/HF ratio were not significantly different in microwave non-irradiation group. Standard deviation of all normal R-R intervals(SDNN), root mean square of successive differences (RMSSD), low frequency(LF), high frequency(HF), LF/HF ratio were not significantly different between two groups. CONCLUSION: There was no significant change in the sympathetic nervous system and parasympathetic nervous system regardless of the presence of microwave irradiation. There was no significant change in the autonomic nervous system adaptability regardless of the presence of microwave irradiation.According to this study, microwave diathermy does not have significant effect on the autonomic nervous system.Future study is necessary to investigate the long term effect of the physical therapy treatment room environment using microwave diathermy on the autonomic nervous system of the human body.

Introduction: Given the growing evidence of reduced heart rate variability in psychiatric diseases associated with emotional instability, we investigated cardiovascular autonomic modulation in patients with borderline personality disorder (BPD) during resting state, parasympathetic stimulation (metronomic breathing), and sympathetic stimulation (mental arithmetic stress test). Methods: In 29 BPD outpatients and 30 controls, we recorded RR-intervals (RRI), blood pressure, skin conductance levels, and respiratory frequency during resting state, metronomic breathing, stress anticipation, stress exposure, and stress recovery. We calculated baroreflex sensitivity (BRS) and parameters of heart rate variability, including the root mean square of successive differences (RMSSD), an index of cardiovagal modulation. Results: During resting state, BPD patients showed higher blood pressure and shorter RRI, as well as lower RMSSD and BRS than controls. Metronomic breathing increased RMSSD and BRS in BPD patients. During the stress exposure, BRS significantly decreased in controls, but not in BPD patients. Furthermore, BPD patients showed less cardioacceleration in response to stress exposure than controls. During stress recovery, we found increases in RMSSD and BRS in controls, but not in BPD patients. Conclusion: Our data show reduced cardiovascular autonomic modulation in BPD patients during resting state, psychophysiological relaxation, and stress exposure. The results indicate a vagal modulation deficit in this cohort. Breathing techniques, such as metronomic breathing, might be helpful to reduce stress and to increase vagal tone in BPD patients.

BackgroundLong-term effects of ambient fine particulate matter (PM2.5) exposure on mortality and morbidity are well established. The study aims to evaluate how short-term indoor PM2.5 exposure affects physiological responses and understand potential mechanisms mediating the cognitive outcomes in working-age adults. MethodsThis real-world randomized single-blind crossover intervention study was conducted in an urban office setting, with desk-based air purifiers used as the intervention. Participants (N = 40) were exposed to average PM2.5 levels of 18.0 μg/m3 in control and 3.7 μg/m3 in intervention conditions. Cognitive tests, heart rate variability (HRV), and electrodermal activity (EDA) measures were conducted after 5 h of exposure. Self-reported mental effort, exhaustion, and task difficulty were collected after the cognitive tests. ResultsParticipants in the intervention condition had significantly higher HRV during cognitive testing, particularly in the standard deviation of normal-to-normal intervals (SDNN), root mean square of successive differences (RMSSD), and high-frequency power (HF) indices. Mediation analysis revealed that elevated PM2.5 exposure reduced HRV indices, which mediated the effect on two executive function-related cognitive skills out of 16 assessed skills. No significant differences were found in EDA, self-reported task difficulty, or exhaustion, but self-reported mental effort was higher in the control condition. ConclusionsLower indoor PM2.5 level was associated with reduced mental effort and higher HRV during cognitive testing. Furthermore, the association between indoor PM2.5 exposure and executive function might be mediated through cardiovagal responses. These findings provide insights on the mechanisms through which fine particle exposure adversely affects the autonomic nervous system and how this in turn affects cognition. The potential cardiovascular and cognitive health benefits of PM2.5 reduction warrants further research.

The responsibility and role of human drivers during automated driving might change dynamically. In such cases, human-machine interface (HMI) transparency becomes crucial to facilitate driving safety, as the states of the automated vehicle have to be communicated correctly and efficiently. However, there is no standardized transparency assessment method to evaluate the understanding of human drivers toward the HMI. In this study, we defined functional transparency (FT) and, based on this definition, proposed a transparency assessment method as a preliminary step toward the objective measurement for HMI understanding. The proposed method was verified in an online survey where HMIs of different vehicle manufacturers were adopted and their transparencies assessed. Even though no significant result was found among HMI designs, FT was found to be significantly higher for participants more experienced with SAE Level 2 automated vehicles, suggesting that more experienced users understand the HMIs better. Further identification tests revealed that more icons in BMW’s and VW’s HMI designs were correctly used to evaluate the state of longitudinal and lateral control. This study provides a novel method for assessing transparency and minimizing confusion during automated driving, which could greatly assist the HMI design process in the future.

While epidemiological studies have examined the effects of exposure to particulate matter with diameter ≤2.5μm (PM2.5) on heart rate variability (HRV) on a daily basis, there is a need for more granular data to better understand the ultrashort-term effects of PM2.5 on HRV. This study aimed to investigate the minute-level association between PM2.5 exposure and HRV using real-time personal monitoring data, focusing on time-lagged effects in vulnerable populations. We collected minute-by-minute data of PM2.5 and HRV using a wearable device from 73 individuals, with 3 days of continuous observations per participant (total 315,360 observations). PM2.5 and electrocardiogram (ECG)-derived HRV indices, including the standard deviation of normal-to-normal intervals (SDNN) and the root mean square of successive differences (RMSSD), were continuously measured for five days using wearable devices. Distributed lag non-linear and linear mixed-effects models were used to evaluate exposure-response relationships. PM2.5 exposure was significantly associated with acute HRV reductions within 180min. SDNN decreased by -8.04% (95% CI: 11.10% to -4.88%) at the initial lag following exposure, peaking at approximately 49min and gradually attenuating thereafter, and RMSSD decreased by -4.17% (95% CI: 7.23% to -1.00%) at the initial lag, with a similar attenuation pattern beyond 38min. More pronounced effects occurred during nighttime (18:00-06:00), with SDNN decreasing by -13.9% (95% CI: 17.81% to -9.80%) and RMSSD by -7.43% (95% CI: 11.13% to -3.57%). Females exhibited a more immediate HRV decline at the initial lag (SDNN: 10.24%, RMSSD: 6.39%) compared to males (SDNN: 4.44%, RMSSD: 8.61%). Patients with arrhythmia showed the greatest reductions at the initial lag (SDNN: 11.42%, RMSSD: 15.95%). This study highlights the immediate autonomic impact of PM2.5 exposure, emphasizing its differential effects by time of day, sex, and health status. Findings underscore the importance of personal air pollution monitoring and targeted interventions for high-risk populations.

Aerobic exercise requires a redistribution of blood flow to active tissue. The autonomic nervous system contributes to this redistribution of blood flow, which could impact heart rate variability (HRV) following exercise. However, little is known about the impact of exercise intensity and dose on post exercise HRV. The purpose of this study was to investigate HRV following aerobic exercise at different intensities and doses. We hypothesized that higher intensities and doses are associated with lower HRV values following exercise. To address this, 10 recreationally active young adults (5 females, 4 males, age = 28 ± 5 years, BMI = 23.06 ± 2.11 kg/m2) completed a maximal oxygen uptake (VO2max) treadmill test and 3 experimental study days in randomized order where they exercised at 1) 30% VO2max for 30 minutes (30 EX), 2) 70% VO2max for 30 minutes (70 EX), and 3) 70% VO2max for a duration that resulted in energy expenditure equal to the 30 EX visit (70 EXEE). Participants were instrumented with a 3-lead electrocardiogram (ECG) and HRV was measured at 25 minutes and 45 minutes post exercise for all study days. HRV was quantified as the root mean square of successive differences (RMSSD), high frequency (HF) power, low frequency (LF) power, the ratio of LF to HF (LF/HF), and the standard deviation of RR intervals (SDRR). During the post exercise period, heart rate (HR) differed by condition and time (time: P = 0.01, condition: P < 0.01, interaction: P < 0.01) such that HR was lower after 30 EX at both 25 minutes (55 ± 6 bpm) and 45 minutes (57 ± 9 bpm) compared to 70 EX (25 minutes = 73 ± 7 bpm, 45 minutes = 69 ± 4 bpm; P < 0.01 for both). At 25 minutes, HR was lower after 30 EX (55 ± 6 bpm) than 70 EXEE (67 ± 9 bpm; P < 0.01). Post exercise RMSSD differed by condition (time: P = 0.13, condition: P < 0.01, interaction: P < 0.01) such that RMSSD was lower 25 minutes after 70 EX (38 ± 19 ms) compared with 30 EX (95 ± 32 ms; P < 0.01). RMSSD was also lower 45 minutes after 70 EX (41 ± 12 ms) compared with 30 EX (66 ± 23 ms; P ≤ 0.05). RMSSD was lower 25 minutes after 70 EXEE (38 ± 19 ms) compared with 30 EX (95 ± 32 ms, P < 0.05). Post exercise HF power differed by condition and time (time: P < 0.05, condition: P < 0.01, interaction: P = 0.53) such that at 25 min, HF power was lower after 70 EX (893 ± 1300 ms2) compared with 30 EX (4119 ± 2288 ms2; P < 0.01), as well as 70 EXEE (1380 ± 1833 ms2) compared with 30 EX (4119 ± 2288 ms2; P < 0.01). The effect of exercise on SDRR differed by condition and time (time: P < 0.01, condition: P < 0.01, interaction: P = 0.53) such that at 25 min, SDRR was lower after 70 EX (47 ± 22 ms) compared with 30 EX (83 ± 26 ms; P < 0.01), as well as 70 EXEE (50 ± 22 ms) compared with 30 EX (83 ± 26 ms; P < 0.01). There were no differences between study days for post exercise LF or LF/HF ratio (P > 0.05 for all). There were also no differences between 70 EX and 70 EXEE for any measure of HR or HRV (P > 0.05 for all). These results indicate that exercise intensity can independently, and in combination with dose, affect HR and HRV after exercise. Specifically, higher intensity exercise resulted in higher HR and lower HRV 25 minutes after exercise. However, at 45 minutes post exercise, there were dose and intensity interactions only on RMSSD and HR. This implies that intensity is more impactful than dose on HR and HRV following exercise, and that some effects may resolve within 45 minutes of exercise. Funding: Wisconsin Alumni Research Foundation, NIH HL118154 This abstract was presented at the American Physiology Summit 2025 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.