A Novel EEG-Based Assessment of Distraction in Simulated Driving under Different Road and Traffic Conditions.

The drivers' distraction plays a crucial role in road safety as it is one of the main impacting causes of road accidents. The phenomenon of distraction encompasses both psychological and environmental factors and, therefore, addressing the complex interplay contributing to human distraction in automotive is crucial for developing technologies and interventions for improving road safety. In scientific literature, different works were proposed for the distraction characterization in automotive, but there is still the lack of a univocal measure to assess the degree of distraction, nor a gold-standard tool that allows to "detect" eventual events, road traffic, and additional driving tasks that might contribute to the drivers' distraction. Therefore, the present study aimed at developing an EEG-based "Distraction index" obtained by the combination of the driver's mental workload and attention neurometrics and investigating and validating its reliability by analyzing together subjective and behavioral measures. A total of 25 licensed drivers were involved in this study, where they had to drive in two different scenarios, i.e., City and Highway, while different secondary tasks were alternatively proposed in addition to the main one to modulate the driver's attentional demand. The statistical analysis demonstrated the reliability of the proposed EEG-based distraction index in identifying the drivers' distraction when driving along different roads and traffic conditions (all p < 0.001). More importantly, the proposed index was demonstrated to be reliable in identifying which are the most impacting additional driving tasks on the drivers' distraction (all p < 0.01).

Neurophysiological mental fatigue assessment for developing user-centered Artificial Intelligence as a solution for autonomous driving.

The human factor plays a key role in the automotive field since most accidents are due to drivers' unsafe and risky behaviors. The industry is now pursuing two main solutions to deal with this concern: in the short term, there is the development of systems monitoring drivers' psychophysical states, such as inattention and fatigue, and in the medium-long term, there is the development of fully autonomous driving. This second solution is promoted by recent technological progress in terms of Artificial Intelligence and sensing systems aimed at making vehicles more and more accurately aware of their "surroundings." However, even with an autonomous vehicle, the driver should be able to take control of the vehicle when needed, especially during the current transition from the lower (SAE < 3) to the highest level (SAE = 5) of autonomous driving. In this scenario, the vehicle has to be aware not only of its "surroundings" but also of the driver's psychophysical state, i.e., a user-centered Artificial Intelligence. The neurophysiological approach is one the most effective in detecting improper mental states. This is particularly true if considering that the more automatic the driving will be, the less available the vehicular data related to the driver's driving style. The present study aimed at employing a holistic approach, considering simultaneously several neurophysiological parameters, in particular, electroencephalographic, electrooculographic, photopletismographic, and electrodermal activity data to assess the driver's mental fatigue in real time and to detect the onset of fatigue increasing. This would ideally work as an information/trigger channel for the vehicle AI. In all, 26 professional drivers were engaged in a 45-min-lasting realistic driving task in simulated conditions, during which the previously listed biosignals were recorded. Behavioral (reaction times) and subjective measures were also collected to validate the experimental design and to support the neurophysiological results discussion. Results showed that the most sensitive and timely parameters were those related to brain activity. To a lesser extent, those related to ocular parameters were also sensitive to the onset of mental fatigue, but with a delayed effect. The other investigated parameters did not significantly change during the experimental session.

A Neuroergonomic Approach Fostered by Wearable EEG for the Multimodal Assessment of Drivers Trainees.

When assessing trainees' progresses during a driving training program, instructors can only rely on the evaluation of a trainee's explicit behavior and their performance, without having any insight about the training effects at a cognitive level. However, being able to drive does not imply knowing how to drive safely in a complex scenario such as the road traffic. Indeed, the latter point involves mental aspects, such as the ability to manage and allocate one's mental effort appropriately, which are difficult to assess objectively. In this scenario, this study investigates the validity of deploying an electroencephalographic neurometric of mental effort, obtained through a wearable electroencephalographic device, to improve the assessment of the trainee. The study engaged 22 young people, without or with limited driving experience. They were asked to drive along five different but similar urban routes, while their brain activity was recorded through electroencephalography. Moreover, driving performance, subjective and reaction times measures were collected for a multimodal analysis. In terms of subjective and performance measures, no driving improvement could be detected either through the driver's subjective measures or through their driving performance. On the other side, through the electroencephalographic neurometric of mental effort, it was possible to catch their improvement in terms of mental performance, with a decrease in experienced mental demand after three repetitions of the driving training tasks. These results were confirmed by the analysis of reaction times, that significantly improved from the third repetition as well. Therefore, being able to measure when a task is less mentally demanding, and so more automatic, allows to deduce the degree of users training, becoming capable of handling additional tasks and reacting to unexpected events.

Neurophysiological Assessment of An Innovative Maritime Safety System in Terms of Ship Operators' Mental Workload, Stress, and Attention in the Full Mission Bridge Simulator.

The current industrial environment relies heavily on maritime transportation. Despite the continuous technological advances for the development of innovative safety software and hardware systems, there is a consistent gap in the scientific literature regarding the objective evaluation of the performance of maritime operators. The human factor is profoundly affected by changes in human performance or psychological state. The difficulty lies in the fact that the technology, tools, and protocols for investigating human performance are not fully mature or suitable for experimental investigation. The present research aims to integrate these two concepts by (i) objectively characterizing the psychological state of mariners, i.e., mental workload, stress, and attention, through their electroencephalographic (EEG) signal analysis, and (ii) validating an innovative safety framework countermeasure, defined as Human Risk-Informed Design (HURID), through the aforementioned neurophysiological approach. The proposed study involved 26 mariners within a high-fidelity bridge simulator while encountering collision risk in congested waters with and without the HURID. Subjective, behavioral, and neurophysiological data, i.e., EEG, were collected throughout the experimental activities. The results showed that the participants experienced a statistically significant higher mental workload and stress while performing the maritime activities without the HURID, while their attention level was statistically lower compared to the condition in which they performed the experiments with the HURID (all p < 0.05). Therefore, the presented study confirmed the effectiveness of the HURID during maritime operations in critical scenarios and led the way to extend the neurophysiological evaluation of the HFs of maritime operators during the performance of critical and/or standard shipboard tasks.

Listening Effort in Tinnitus: A Pilot Study Employing a Light EEG Headset and Skin Conductance Assessment during the Listening to a Continuous Speech Stimulus under Different SNR Conditions.

Background noise elicits listening effort. What else is tinnitus if not an endogenous background noise? From such reasoning, we hypothesized the occurrence of increased listening effort in tinnitus patients during listening tasks. Such a hypothesis was tested by investigating some indices of listening effort through electroencephalographic and skin conductance, particularly parietal and frontal alpha and electrodermal activity (EDA). Furthermore, tinnitus distress questionnaires (THI and TQ12-I) were employed. Parietal alpha values were positively correlated to TQ12-I scores, and both were negatively correlated to EDA; Pre-stimulus frontal alpha correlated with the THI score in our pilot study; finally, results showed a general trend of increased frontal alpha activity in the tinnitus group in comparison to the control group. Parietal alpha during the listening to stimuli, positively correlated to the TQ12-I, appears to reflect a higher listening effort in tinnitus patients and the perception of tinnitus symptoms. The negative correlation between both listening effort (parietal alpha) and tinnitus symptoms perception (TQ12-I scores) with EDA levels could be explained by a less responsive sympathetic nervous system to prepare the body to expend increased energy during the "fight or flight" response, due to pauperization of energy from tinnitus perception.

Assessment of the Impact of Low-dose Ionizing Radiation Exposure on Health Care Workers: A Study of Methods Used from a Scoping Review.

ABSTRACT: Healthcare workers may be exposed to ionizing radiation. Ionizing radiations are an important occupational risk factor for the potential damage they can cause to workers' health. Actually, the attention is focused on diseases caused by damage to radiosensitive organs. The aim of our study is to evaluate the methods used for the assessment of the impact of exposure to low-dose ionizing radiation in a population of healthcare workers (HCWs). The electronic database PubMed was searched by title, abstract, and medical subheadings (MeSH) terms. The extracted data were arranged into tables by dividing bibliographic reference, exposure, and statistical analysis information. The quality assessment was performed with the use of the Newcastle-Ottawa Quality Assessment Scale. The search strategy involved retrieving 15 studies (eight cohorts and seven cross-sectional studies). The univariate tests have been performed in 14 studies (93.3%), and Chi-square and T-test were the most commonly used. Multivariate tests have been performed in 11 studies (73.3%), and the most commonly performed were Logistic and Poisson Regressions. The most rated organ was the thyroid gland (six studies). The annual cumulative effective dose was the most used method to assess the dose rate (seven studies). Due to the characteristics of pathologies involved, a retrospective cohort study with an adequate control group and use of the annual cumulative effective dose to account for exposure could be useful features to obtain the best possible evidence. All the elements were found rarely in studies considered. The need is highlighted for more in-depth studies to investigate this topic.

Assessment of dietary supplement consumption among Italian university students: The multicenter DiSCo study.

OBJECTIVES: The aim of this study was to analyze the consumption of dietary supplements (DSs) and related sociodemographic characteristics or behaviors in Italian undergraduates. METHODS: A questionnaire-based, cross-sectional study was carried out between October 2021 and May 2022 involving undergraduates from 12 public universities. The use of DSs in the previous 6 mo, the aim and reason for use, the purchasing channel, and related adverse effects were explored and compared by sex. A logistic regression was performed to highlight possible associations between sociodemographic, anthropometric, and behavioral characteristics of participants and supplement consumption. RESULTS: The use of DSs was reported by 71.5% of the 2165 respondents. Supplementation was related to sex (odds ratio [OR] 0.690; 95% confidence interval [CI], 0.516-0.924, for men), vegetarian or vegan (OR 4.814; 95% CI, 1.669-13.887) and other particular diet regimens (OR 1.819; 95% CI, 1.282-2.580), sport (OR 1.688; 95% CI, 1.116-2.553), and type of sport (OR 0.629; 95% CI, 0.423-0.936, for team sports). Women were more likely to use DSs following a doctor's prescription and to buy them in a pharmacy (P < 0.001) but reported more adverse effects (P = 0.018) than men. The main aim pursued was general health; proteins, amino acids, and non-caffeinated energy supplements were consumed to improve physical performance and caffeinated energy supplements for mental performance. CONCLUSIONS: Diet supplementation was common in the sample examined, especially in women, and associated with particular dietary regimens and sports, especially individual sports. Female consumers follow specialists' indications more than males. These results highlight the need for educational interventions about diet supplementation for this category of users.

Real-time Pilot Crew's Mental Workload and Arousal Assessment During Simulated Flights for Training Evaluation: a Case Study.

Training assessment is usually done by evaluating information derived from instructor's supervision related to the pilot's operational performance and behavior. However, this approach lacks objective measures, especially regarding the pilots' mental states while accomplishing the flight training tasks. The study therefore aimed at developing and testing a method for gathering and analyzing in real-time pilots' brain activity and skin conductance to improve the training evaluation. In this regard, Novice pilots' neurophysiological signals were acquired throughout multi-crew training sessions. The results demonstrated how the methodology proposed was able to endow real-time pilots' mental workload and arousal assessment for i) better evaluating training progress and operational behavior during the training session, and ii) for objectively comparing different training sessions.

Healthcare Management, avoidable mortality, telemedicine to improve health of the diabetic population.

BACKGROUND: Worldwide the International Diabetes Federation (IDF) estimated that in 2021 9.2% of adults (536.6 million, between 20 and 79 years of age) are diabetic and 32.6% under 60 years (6.7 million) die because of diabetes. This disease is set to become the leading cause of disability and mortality by 2030. In Italy, the prevalence of Diabetes is about 5%; in the pre-pandemic period, from 2010 to 2019, diabetes was responsible for 3% of deaths recorded, while during the pandemic in 2020, these deaths increased to about 4%. The present work aimed to measure the outcomes obtained from the ICPs (integrated care pathways) implemented by a Health Local Authority according to the model of the Lazio region and its impact on avoidable mortality, i.e., those deaths potentially avoidable with primary prevention interventions, early diagnosis and targeted therapies, adequate hygienic conditions and proper health care. MATERIALS AND METHODS: Data from 1675 patients enrolled in the diagnostic treatment pathway were analyzed, 471 with type 1 diabetes and the remainder with type 2 (mean age 17.5 and 69, respectively). 987 patients with type 2 diabetes also had comorbidities: in 43% obesity, 56% dyslipidemia, 61% hypertension, 29% COPD. In 54% they had at least 2 comorbidities. All patients enrolled in the ICPs were equipped with a glucometer and an app capable of recording results on capillary blood, 269 with type 1 diabetes were equipped with continuous and 198 insulin pump measurement devices. All enrolled patients recorded at least one daily blood glucose reading, one weekly weight reading, and recorded steps taken daily. They also underwent glycated hemoglobin monitoring, periodic visits and scheduled instrumental checks. A total of 5500 parameters were measured for patients with type 2 diabetes and 2345 for patients with type 1 diabetes. RESULTS: Analysis of medical records revealed that 93% of patients with type 1 diabetes were found to be adherent to the treatment pathway, adherence of patients with type 2 diabetes was recorded in 87% of enrolled cases. The analysis of accesses to the Emergency Department for decompensated diabetes saw only 21% of patients enrolled in the ICPs, but recording poor compliance. The mortality in enrolled patients was 1.9% compared with 4.3 percent in patients not enrolled in ICPs, and patients amputated for diabetic foot resulted in 82% of patients not enrolled in ICPs. Finally, it is noted that patients also enrolled in the telerehabilitation pathway or home care rehabilitation (28%), with the same conditions of severity of neuropathic and vasculopathic picture presented a reduction of 18% in leg or lower limb amputation compared to patients not enrolled or not adhering to ICPs, a reduction of 27% in metatarsal amputation and 34% in toes amputation. CONCLUSIONS: Telemonitoring of diabetic patients allows for greater patient empowerment with increased adherence, as well as a reduction in Emergency Department and inpatient admissions, thus resulting in ICPs being a tool for both standardization of quality of care and standardization of the average cost of the chronic patient with diabetic disease. Likewise, telerehabilitation can reduce the incidence of amputations from diabetic foot disease if associated with adherence to the proposed pathway with ICPs.

Assessment of bike handling during cycling individual time trials with a novel analytical technique adapted from motorcycle racing.

A methodology to study bike handling of cyclists during individual time trials (ITT) is presented. Lateral and longitudinal accelerations were estimated from GPS data of professional cyclists (n = 53) racing in two ITT of different length and technical content. Acceleration points were plotted on a plot (g-g diagram) and they were enclosed in an ellipse. A correlation analysis was conducted between the area of the ellipse and the final ITT ranking. It was hypothesised that a larger area was associated with a better performance. An analytical model for the bike-cyclist system dynamics was used to conduct a parametric analysis on the influence of riding position on the shape of the g-g diagram. A moderate (n = 27, r = -0.40, p = 0.038) and a very large (n = 26, r = -0.83, p < 0.0001) association were found between the area of the enclosing ellipse and the final ranking in the two ITT. Interestingly, this association was larger in the shorter race with higher technical content. The analytical model suggested that maximal decelerations are highly influenced by the cycling position, road slope and speed. This investigation, for the first time, explores a novel methodology that can provide insights into bike handling, a large unexplored area of cycling performance.

Wearable Technologies for Mental Workload, Stress, and Emotional State Assessment during Working-Like Tasks: A Comparison with Laboratory Technologies.

The capability of monitoring user's performance represents a crucial aspect to improve safety and efficiency of several human-related activities. Human errors are indeed among the major causes of work-related accidents. Assessing human factors (HFs) could prevent these accidents through specific neurophysiological signals' evaluation but laboratory sensors require highly-specialized operators and imply a certain grade of invasiveness which could negatively interfere with the worker's activity. On the contrary, consumer wearables are characterized by their ease of use and their comfortability, other than being cheaper compared to laboratory technologies. Therefore, wearable sensors could represent an ideal substitute for laboratory technologies for a real-time assessment of human performances in ecological settings. The present study aimed at assessing the reliability and capability of consumer wearable devices (i.e., Empatica E4 and Muse 2) in discriminating specific mental states compared to laboratory equipment. The electrooculographic (EOG), electrodermal activity (EDA) and photoplethysmographic (PPG) signals were acquired from a group of 17 volunteers who took part to the experimental protocol in which different working scenarios were simulated to induce different levels of mental workload, stress, and emotional state. The results demonstrated that the parameters computed by the consumer wearable and laboratory sensors were positively and significantly correlated and exhibited the same evidences in terms of mental states discrimination.