Driver Attention Assessment Using Physiological Measures from EEG, ECG, and EDA Signals †

In this paper, we consider the evaluation of the mental attention state of individuals driving in a simulated environment. We tested a pool of subjects while driving on a highway and trying to overcome various obstacles placed along the course in both manual and autonomous driving scenarios. Most systems described in the literature use cameras to evaluate features such as blink rate and gaze direction. In this study, we instead analyse the subjects' Electrodermal activity (EDA) Skin Potential Response (SPR), their Electrocardiogram (ECG), and their Electroencephalogram (EEG). From these signals we extract a number of physiological measures, including eye blink rate and beta frequency band power from EEG, heart rate from ECG, and SPR features, then investigate their capability to assess the mental state and engagement level of the test subjects. In particular, and as confirmed by statistical tests, the signals reveal that in the manual scenario the subjects experienced a more challenged mental state and paid higher attention to driving tasks compared to the autonomous scenario. A different experiment in which subjects drove in three different setups, i.e., a manual driving scenario and two autonomous driving scenarios characterized by different vehicle settings, confirmed that manual driving is more mentally demanding than autonomous driving. Therefore, we can conclude that the proposed approach is an appropriate way to monitor driver attention

Vaccines against coronaviruses: The state of the art

The emerging epidemic caused by the new coronavirus SARS-CoV-2 represents the most important socio-health threat of the 21st century. The high contagiousness of the virus, the strong impact on the health system of the various countries and the absence to date of treatments able to improve the prognosis of the disease make the introduction of a vaccine indispensable, even though there are currently no approved human coronavirus vaccines. The aim of the study is to carry out a review of the medical literature concerning vaccine candidates for the main coronaviruses responsible for human epidemics, including recent advances in the development of a vaccine against COVID-19. This extensive review carried out on the vaccine candidates of the main epidemic coronaviruses of the past has shown that the studies in animal models suggest a high efficacy of potential vaccines in providing protection against viral challenges. Similar human studies have not yet been carried out, as the main trials are aimed at assessing mainly vaccine safety and immunogenicity. Whereas the severe acute respiratory syndrome (SARS-CoV) epidemic ended almost two decades ago and the Middle East respiratory syndrome (MERS-CoV) epidemic is now better controlled, as it is less contagious due to the high lethality of the virus, the current SARS-CoV-2 pandemic represents a problem that is certainly more compelling, which pushes us to accelerate the studies not only for the production of vaccines but also for innovative pharmacological treatments. SARS-CoV-2 vaccines might come too late to affect the first wave of this pandemic, but they might be useful if additional subsequent waves occur or in a post-pandemic perspective in which the virus continues to circulate as a seasonal virus

Supervised learning techniques for stress detection in car drivers

6noIn this paper we propose the application of supervised learning techniques to recognize stress situations in drivers by analyzing their Skin Potential Response (SPR) and the Electrocardiogram (ECG). A sensing device is used to acquire the SPR from both hands of the drivers, and the ECG from their chest. We also consider a motion artifact removal algorithm that allows the generation of a single cleaned SPR signal, starting from the two SPR signals, which could be characterized by artifacts due to vibrations or movements of the hands on the wheel. From both the cleaned SPR and the ECG signals we compute some statistical features that are used as input to six Machine Learning Algorithms for stress or non-stress episodes classification. The SPR and ECG signals are also used as input to Deep Learning Algorithms, thus allowing us to compare the performance of the different classifiers. The experiments have been carried out in a firm specialized in developing professional car driving simulators. In particular, a dynamic driving simulator has been used, with subjects driving along a straight road affected by some unanticipated stress-evoking events, located at different positions. We obtain an accuracy of 88.13% in stress recognition using a Long Short-Term Memory (LSTM) network.openopenZontone P.; Affanni A.; Bernardini R.; Del Linz L.; Piras A.; Rinaldo R.Zontone, P.; Affanni, A.; Bernardini, R.; Del Linz, L.; Piras, A.; Rinaldo, R

Stress evaluation in simulated autonomous and manual driving through the analysis of skin potential response and electrocardiogram signals

The evaluation of car drivers\u2019 stress condition is gaining interest as research on Autonomous Driving Systems (ADS) progresses. The analysis of the stress response can be used to assess the acceptability of ADS and to compare the driving styles of different autonomous drive algorithms. In this contribution, we present a system based on the analysis of the Electrodermal Activity Skin Potential Response (SPR) signal, aimed to reveal the driver\u2019s stress induced by different driving situations. We reduce motion artifacts by processing two SPR signals, recorded from the hands of the subjects, and outputting a single clean SPR signal. Statistical features of signal blocks are sent to a Supervised Learning Algorithm, which classifies between stress and normal driving (non-stress) conditions. We present the results obtained from an experiment using a professional driving simulator, where a group of people is asked to undergo manual and autonomous driving on a highway, facing some unexpected events meant to generate stress. The results of our experiment show that the subjects generally appear more stressed during manual driving, indicating that the autonomous drive can possibly be well received by the public. During autonomous driving, however, significant peaks of the SPR signal are evident during unexpected events. By examining the electrocardiogram signal, the average heart rate is generally higher in the manual case compared to the autonomous case. This further supports our previous findings, even if it may be due, in part, to the physical activity involved in manual driving

Detection of SARS-CoV-2 on hospital surfaces

The COVID-19 pandemic, affecting 213 countries, with more than 10 million cases and over 500,000 deaths is still causing serious health, social and economic emergency worldwide. Italian Northern regions are among the most badly affected areas. Surfaces represent matrices to which particular attention should be paid for prevention and control of SARS-CoV-2 transmission. A few studies have highlighted virus presence on surfaces. We report the evidence of its presence on hospital surfaces, in a single room hosting a patient whose nose-pharyngeal swab resulted positive for SARS-CoV-2 RNA at the admission. The surfaces sampling was carried out using pre-wetted swabs followed by extraction and amplification of viral RNA by reverse Real-Time Polymerase Chain Reaction (rRT-PCR). A total of 4/15 (26.66%) surfaces were positive for SARS-CoV-2 RNA: the right bed rail, the call button, the bed trapeze bar, the stethoscope; moreover, the patient’s inner surgical mask was positive, showing the emission of the virus from the patient. This study is a further confirmation that the surfaces represent a potential vehicle of transmission. This supports the need for strict adherence to hand and environmental hygiene. (www.actabiomedica.it)

Reorganization of Active Surveillance of Acute Flaccid Paralysis (AFP) in Emilia-Romagna, Italy: a two-step Public Health intervention

BACKGROUND AND AIM OF THE WORK: The International Health Regulations Emergency Committee declared in 2014 that poliovirus circulation is a public health emergency of international concern. In 2017 and 2018 Italy was classified at intermediate risk of poliovirus reintroduction based on suboptimal poliovirus surveillance. Acute flaccid paralysis active surveillance is the gold standard in the polio eradication process. The aims of this study were to investigate the causes of reduced acute flaccid paralysis case reporting in Emilia-Romagna in the last few years (step 1) and to study a public health intervention to restore an adequate level of acute flaccid paralysis surveillance in that region (step 2). METHODS: In the first step a context analysis was performed by analysing the 2015-2017 Hospital Discharge Registers in Emilia-Romagna with the ICD-9-CM differential diagnosis codes for acute flaccid paralysis. Data from context analysis was then used to plan a new regional collaborative network of acute flaccid paralysis active surveillance. RESULTS: The active surveillance network was, at the end of the study, composed by 49 doctors from both hospital administrations and clinical wards from 4 University Hospitals and 7 Local Health Authorities throughout the Region. In 15 months, 7 acute flaccid paralysis cases have been reported; 85,7% received a full clinical and virological investigation and 83,3% completed the 60 day's follow-up. The mean response to each e-mail was 48,5% (SD 7,5%). CONCLUSIONS: In 2019, the Emilia-Romagna's active surveillance system reached the sensitivity, completeness of case investigation and follow-up required to achieve the minimum levels for certification standard surveillance

Therapeutic strategies against COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel coronavirus that mainly affects the upper and lower respiratory tract and is responsible for extremely different degrees of disease, ranging from flu-like symptoms to atypical pneumonia that may evolve to acute respiratory distress syndrome and, ultimately, death. No specific therapy for SARS-CoV-2 has yet been identified, but since the beginning of the outbreak, several pre-existing therapeutics have been reconsidered for the treatment of infected patients. The aim of this article is to discuss current therapeutics against SARS-CoV-2. A literature review was performed using PubMed, collecting data from English-language articles published until June 20th, 2020. Literature analysis showed that with the acquisition of more in-depth knowledge on the characteristics of SARS-CoV-2 and the pathogenesis of the different clinical manifestations, a more rationale use of available drugs has become possible. However, the road to defining which drugs are effective and which schedules of administration must be used to maximize efficacy and minimize adverse events is still very long. To date, it is only clear that no drug can alone cope with all the problems posed by SARS-CoV-2 infection and effective antivirals and inflammatory drugs must be given together to reduce COVID-19 clinical manifestations. Moreover, choice of therapy must always be tailored on clinical manifestations and, when they occur, drugs able to fight coagulopathy and venous thromboembolism that may contribute to respiratory deterioration must be prescribed. (www.actabiomedica.com)

Epidemiology of SARS-CoV-2 Infection Evaluated by Immunochromatographic Rapid Testing for the Determination of IgM and IgG Against SARS-CoV-2 in a Cohort of Mask Wearing Workers in the Metal-Mechanical Sector in an Area With a High Incidence of COVID-19

Background: Although the diagnosis of new coronavirus 2019 (COVID-19) is made through the identification of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in respiratory secretions by means of molecular methods, a more accurate estimation of SARS-CoV-2 circulation can be obtained by seroprevalence studies. The main aim of this study was to evaluate the true epidemiology of SARS-CoV-2 infection among workers in the metal-mechanical sector who never stopped working during the pandemic period in an area with a high incidence of COVID-19 and to define whether and how they could continue the work without appreciable risks during a second wave. Methods: A total of 815 metal-mechanical workers who had never stopped working even during the pandemic period in three different factories in the Emilia-Romagna Region, Italy, and who had always used face masks during working hours, underwent a capillary blood rapid test for the determination of IgM and IgG against SARS-CoV-2 (COVID-19 IgG/IgM Rapid test, PrimaLab, Modena, Italy). In the event of a positive test, a nasopharyngeal was performed and tested for the presence of SARS-CoV-2. Results: The detection of serum IgG/IgM against SARS-CoV-2 was significantly more common among workers employed in Parma (21/345, 6.1%) than among those employed in Calerno (7/242, 2.9%) or in Spilamberto (3/228, 1.3%) (p <0.001). The analysis of the role of the different variables as predictors of seropositivity for IgG/IgM against SARS-CoV-2 revealed that the presence of specific antibodies was strictly associated with a previous history of COVID-19-like symptoms (odds ratio [OR] 3.95, 95% confidence interval [CI] 1.9–8.2) and household members with COVID-19-like symptoms (OR 2.20, 95% CI 1.04–4.82). Conclusion: This study shows that seropositivity to SARS-CoV-2 is low even among employees who did not interrupt their work during the lockdown phase in a region with a high incidence of COVID-19. The use of face masks appears effective in the avoidance of the transmission of SARS-CoV-2 in factories even in the presence of asymptomatic or mildly symptomatic workers, suggesting that work activities can continue if adequate infection control measures are used during a second wave

Hospital discharges-based search of acute flaccid paralysis cases 2007-2016 in Italy and comparison with the National Surveillance System for monitoring the risk of polio reintroduction

Background Acute flaccid paralysis (AFP) surveillance has been adopted globally as a key strategy for monitoring the progress of the polio eradication initiative. Hereby, to evaluate the completeness of the ascertainment of AFP cases in Italy, a hospital-discharges based search was carried out. Methods AFP cases occurring between 2007 and 2016 among children under 15 years of age were searched in the Italian Hospital Discharge Records (HDR) database using specific ICD-9-CM diagnostic codes. AFP cases identified between 2015 and 2016 were then compared with those notified to the National Surveillance System (NSS). Results Over a 10-year period, 4163 hospital discharges with diagnosis of AFP were reported in Italy. Among these, 956 (23.0%) were acute infective polyneuritis, 1803 (43.3%) myopathy, and 1408 (33.8%) encephalitis, myelitis and encephalomyelitis. During the study period, a decreasing trend was observed for all diagnoses and overall the annual incidence rate (IR) declined from 5.5 to 4.5 per 100,000 children. Comparing NSS with HDR data in 2015-2016, we found a remarkable underreporting, being AFP cases from NSS only 14% of those recorded in HDR. In particular, the acute infective polyneuritis cases reported to NSS accounted for 42.6% of those detected in HDR, while only 0.9% of myopathy cases and 13.1% of encephalitis/myelitis/encephalomyelitis cases have been notified to NSS. The highest AFP IRs per 100,000 children calculated on HDR data were identified in Liguria (17.4), Sicily (5.7), and Veneto (5.1) Regions; regarding the AFP notified to the NSS, 11 out of 21 Regions failed to reach the number of expected cases (based on 1/100,000 rate), and the highest discrepancies were observed in the Northern Regions. Overall, the national AFP rate was equal to 0.6, therefore did not reach the target value. Conclusions AFP surveillance data are the final measure of a country's progress towards polio eradication. The historical data obtained by the HDR have been useful to assess the completeness of the notification data and to identify the Regions with a low AFP ascertainment rate in order to improve the national surveillance system

Comparative assessment of drivers' stress induced by autonomous and manual driving with heart rate variability parameters and machine learning analysis of electrodermal activity

12openopenZontone, P; Affanni, A; Bernardini, R; Brisinda, D; Del Linz, L; Formaggia, F; Minen, D; Minen, M; Savorgnan, C; Piras, A; Rinaldo, R; Fenici, RZontone, P; Affanni, A; Bernardini, R; Brisinda, D; Del Linz, L; Formaggia, F; Minen, D; Minen, M; Savorgnan, C; Piras, A; Rinaldo, R; Fenici,