Gaze entropy metrics for mental workload estimation are heterogenous during hands-off level 2 automation.

As the level of vehicle automation increases, drivers are more likely to engage in non-driving related tasks which take their hands, eyes, and/or mind away from the driving task. Consequently, there has been increased interest in creating Driver Monitoring Systems (DMS) that are valid and reliable for detecting elements of driver state. Workload is one element of driver state that has remained elusive within the literature. Whilst here has been promising work in estimating mental workload using gaze-based metrics, the literature has placed too much emphasis on point estimate differences. Whilst these are useful for establishing whether effects exist, they ignore the inherent variability within individuals and between different drivers. The current work builds on this by using a Bayesian distributional modelling approach to quantify the within and between participants variability in Information Theoretical gaze metrics. Drivers (N = 38) undertook two experimental drives in hands-off Level 2 automation with their hands and feet away from operational controls. During both drives, their priority was to monitor the road before a critical takeover. During one drive participants had to complete a secondary cognitive task (2-back) during the hands-off Level 2 automation. Changes in Stationary Gaze Entropy and Gaze Transition Entropy were assessed for conditions with and without the 2-back to investigate whether consistent differences between workload conditions could be found across the sample. Stationary Gaze Entropy proved a reliable indicator of mental workload; 92 % of the population were predicted to show a decrease when completing 2-back during hands-off Level 2 automated driving. Conversely, Gaze Transition Entropy showed substantial heterogeneity; only 66 % of the population were predicted to have similar decreases. Furthermore, age was a strong predictor of the heterogeneity of the average causal effect that high mental workload had on eye movements. These results indicate that, whilst certain elements of Information Theoretic metrics can be used to estimate mental workload by DMS, future research needs to focus on the heterogeneity of these processes. Understanding this heterogeneity has important implications toward the design of future DMS and thus the safety of drivers using automated vehicle functions. It must be ensured that metrics used to detect mental workload are valid (accurately detecting a particular driver state) as well as reliable (consistently detecting this driver state across a population).

An innovative sit-standing seat in urban buses: A new design to prevent falls and non-collision injuries.

BACKGROUND: Due to the rapid growth of metropolises and the insufficiency of public transportation, nowadays, many people travel on these vehicles in a standing position. This position leads to discomfort and the risk of falling or non-collision incidents for the passengers. OBJECTIVE: The present study was conducted to analyze an innovative sit-standing seat to prevent falls and non-collision injuries in standing passengers. METHODS: A total of sixteen participated in this study. EMG signal and Borg scale were used to assess muscle activity and discomfort, respectively. RESULTS: The mean Borg scale score for perceived discomfort was lower in the sit-standing position than the standing position in all body organs, except for the hips. Also, in the sit-standing position compared to the standing position, the muscle activity of the soleus and medial gastrocnemius muscles was significantly lower in the constant velocity and entire phases in both legs, lower in the right leg in the acceleration phase and lower in the left leg in the deceleration phase. CONCLUSIONS: So, this seat can be used as an innovative idea to improve the ergonomic condition of standing passengers to prevent falls and non-collision injuries on transit buses.

Determination of critical time points in non-collision incidents of elderly passengers in standing position on urban bus.

Objective: Due to the reduced physical ability of elderly, the occurrence of non-collision incidents is higher for these passengers in standing position. Therefore, the purpose of the present study is to determine the critical time points of non-collision incidents using the level of leg muscle activity in elderly standing passengers on urban bus.Methods: To determine the critical time points in the occurrence of non-collision incidents, the level of muscular activity of the standing passengers was analyzed using a surface electromyography (surface EMG) device during the movement scenario of the bus. The results of assessing the leg muscle activity was analyzed in SPSS software.Results: The contraction pattern of the leg muscles in standing passengers was consistent with Newton's First Law. The results showed that the level of muscular activity decreased in the right leg muscles when changing the phase of bus motion from acceleration to constant velocity. This level of muscular activity in the left leg muscles increased when constant velocity changed to deceleration. These changes were quite significant in the medial gastrocnemius and soleus muscles (P < 0.05).Conclusions: According to these findings, it was found that the acceleration and deceleration phases, especially the starting and changing phases of bus motion, are the most critical time points in the occurrence of non-collision incidents in elderly standing passengers on urban bus.

Assessment of occupational safety, health, and ergonomics issues in agriculture in some cities of Iran.

BACKGROUND: Iran has a variety of climates which support agriculture in different seasons. Hence, a significant proportion of people, especially in rural areas, are engaged in farming. Agriculture is considered one of the most insecure job sectors in developing and developed countries. OBJECTIVE: Since there is no comprehensive study on safety, health, and ergonomics issues in Iran's agriculture, it is necessary to use checkpoints to assess occupational safety, health, and ergonomics issues in Iran's agriculture. METHODS: In this study, 430 villages from seven provinces of Iran were selected to study safety, health, and ergonomics in agriculture using ergonomic checkpoints. The checkpoints were collected with the help of rural health centers. RESULTS: The results of the study showed that the villages of Kurdistan Province had the best safety, health, and working conditions (66.12%); and Khuzestan province villages had the worst safety, health, and working conditions (38.16%). Among the ergonomic checkpoints in agriculture, the control of hazardous chemicals (CHC) index with 71.41% and work organization and work schedule (WOWS) index with 35.25% represented the best and worst ergonomic conditions of the study villages, respectively. Furthermore, the general index of ergonomics in agriculture for the study villages was 53.64%. Therefore, Khuzestan Province and the WOWS index top the priorities for corrective actions to improve the safety, health and working conditions in agriculture. CONCLUSIONS: The ergonomics indices in Iranian agriculture are important, and should be prioritized for corrective actions.