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,

The progression of hemophilic arthropathy: The role of biomarkers

Background: Hemophilia A and B are X-linked congenital bleeding disorders characterized by recurrent hemarthroses leading to specific changes in the synovium and cartilage, which finally result in the destruction of the joint: this process is called hemophilic arthropathy (HA). This review highlights the most prominent molecular biomarkers found in the literature to discuss their potential use in the clinical practice to monitor bleeding, to assess the progression of the HA and the effectiveness of treatments. Methods: A review of the literature was performed on PubMed and Embase, from 3 to 7 August 2020. Study selection and data extraction were achieved independently by two authors and the following inclusion criteria were determined a priori: English language, available full text and articles published in peer-reviewed journal. In addition, further articles were identified by checking the bibliography of relevant articles and searching for the studies cited in all the articles examined. Results: Eligible studies obtained at the end of the search and screen process were seventy-three (73). Conclusions: Despite the surge of interest in the clinical use of biomarkers, current literature underlines the lack of their standardization and their potential use in the clinical practice preserving the role of physical examination and imaging in early diagnosis

Antimicrobial knowledge and confidence amongst final year medical students in Australia

Introduction: Inappropriate use of antimicrobials is one of the major modifiable contributors to antimicrobial resistance. There is currently no validated survey tool available to assess knowledge and confidence of medical students in infectious diseases (ID) compared to other diseases states, and little is known about this topic. Materials and methods: A cross-sectional survey of final year medical students attending universities around Australia was conducted between August and September, 2015. A survey unique from other published studies was developed to survey satisfaction in education, confidence and knowledge in ID, and how this compared to these factors in cardiovascular diseases. Results: Reliability and validity was demonstrated in the survey tool used. Students were more likely to rate university education as sufficient for cardiovascular diseases (91.3%) compared to ID (72.5%), and were more confident in their knowledge of cardiovascular diseases compared to ID (74.38% vs. 53.76%). Students tended to answer more cardiovascular disease related clinical questions correctly (mean score 78%), compared to questions on antimicrobial use (mean score 45%). Conclusions: Poor knowledge and confidence amongst final year medical students in Australia were observed in ID. Antimicrobial stewardship agenda should include the provision of additional training in antimicrobial prescribing to the future medical workforce

Car Driver's Sympathetic Reaction Detection through Electrodermal Activity and Electrocardiogram Measurements

Objective: in this paper we propose a system to detect a subject's sympathetic reaction, which is related to unexpected or challenging events during a car drive. Methods: we use the Electrocardiogram (ECG) signal and the Skin Potential Response (SPR) signal, which has several advantages with respect to other Electrodermal (EDA) signals. We record one SPR signal for each hand, and use an algorithm that, selecting the smoother signal, is able to remove motion artifacts. We extract statistical features from the ECG and SPR signals in order to classify signal segments and identify the presence or absence of emotional events via a Supervised Learning Algorithm. The experiments were carried out in a company which specializes in driving simulator equipment, using a motorized platform and a driving simulator. Different subjects were tested with this setup, with different challenging events happening on predetermined locations on the track. Results: we obtain an Accuracy as high as 79.10% for signal blocks and as high as 91.27% for events. Conclusion: results demonstrate the good performance of the presented system in detecting sympathetic reactions, and the effectiveness of the motion artifact removal procedure. Significance: our work demonstrates the possibility to classify the emotional state of the driver, using the ECG and EDA signals and a slightly invasive setup. In particular, the proposed use of SPR and of the motion artifact removal procedure are crucial for the effectiveness of the system

User Engagement in Mental Health Apps:A Review of Measurement, Reporting, and Validity

Objective: Despite the potential benefits of mobile mental health apps, real-world results indicate engagement issues because of low uptake and sustained use. This review examined how studies have measured and reported on user engagement indicators (UEIs) for mental health apps. Methods: A systematic review of multiple databases was performed in July 2018 for studies of mental health apps for depression, bipolar disorder, schizophrenia, and anxiety that reported on UEIs, namely usability, user satisfaction, acceptability, and feasibility. The subjective and objective criteria used to assess UEIs, among other data, were extracted from each study. Results: Of 925 results, 40 studies were eligible. Every study reported positive results for the usability, satisfaction, acceptability, or feasibility of the app. Of the 40 studies, 36 (90%) employed 371 indistinct subjective criteria that were assessed with surveys, interviews, or both, and 23 studies used custom subjective scales, rather than preexisting standardized assessment tools. A total of 25 studies (63%) used objective criteria—with 71 indistinct measures. No two studies used the same combination of subjective or objective criteria to assess UEIs of the app. Conclusions: The high heterogeneity and use of custom criteria to assess mental health apps in terms of usability, user satisfaction, acceptability, or feasibility present a challenge for understanding real-world low uptake of these apps. Every study reviewed claimed that UEIs for the app were rated highly, which suggests a need for the field to focus on engagement by creating reporting standards and more carefully considering claims

Simultaneous real-time assessment of sportive pilots’ stress and performance related to vehicle behaviour, during racing with the DIM professional simulator

Abstract book of EH

An MPC approach to the design of motion cueing algorithms for driving simulators

Driving simulators play an important role in the development of new vehicles and advanced driver assistance devices. In fact, on the one hand, having a human driver on a driving simulator allows automotive OEMs to bridge the gap between virtual prototyping and on-road testing during the vehicle development phase. On the other hand, novel driver assistance systems (such as advanced accident avoidance systems) can be safely tested by having the driver operating the vehicle in a virtual, highly realistic environment, while being exposed to hazardous situations. In both applications, it is crucial to faithfully reproduce in the simulator the drivers perception of forces acting on the vehicle and its acceleration. The strategy used to operate the simulator platform within its limited working space to provide the driver with the most realistic perception goes under the name of motion cueing. In this paper we describe a novel approach to motion cueing design that is based on Model Predictive Control techniques. Two features characterize the algorithm, namely, the use of a detailed model of the human vestibular system and a predictive strategy based on the availability of a virtual driver. Differently from classical schemes based on washout filters, such features allows a better implementation of tilt coordination and to handle more efficiently the platform limits

Assisted / autonomous vs. human driving assessment on the DiM driving simulator using objective / subjective characterization.

The present work represents a qualitative investigation of a methodology, based on Driving Simulator session, which could give interesting indications to the vehicle development teams for autonomous and assisted driving about the efficiency/comfortability of the driving intelligence in realistic highway driving scenarios. To prove the methodology, we have preliminarily performed a test with 13 participants. The number is still not statistically significative, and the results of the present work are to be intended for a) investigation and tuning of the methodology and b) for the researchers to understand if, applying signal processing developed in previous works and given a bigger number of participants, the approach could scientifically provide innovative and quantitative indexes for classifying autonomous driving algorithms