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

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

Study on the Next Generation Motion Cueing for Driving Simulators

In the last years the interest about dynamic driving simulators is increasing and new commercial solutions are arising. One of the most debated and difficult problem is the motion cueing strategy , i.e. a strategy to give the driver the most realistic perception using the acceleration of the mechanical system. In this paper we exploit a novel direction in the motion cueing design based on Model Predictive Control techniques combined with the modeling of the human perceptive sensors. We propose an ad hoc implementation of the MPC algorithm designed to handle the typical difficulties of a motion cueing strategy, i.e. limited working space, conflicting cues and tilt coordination. The procedure is developed to take advantage of a virtual driver to predict trajectories and enhance performance

Clinical validation of a novel wearable system for real-time telemetric transmission of transient changes of cardiac autonomic modulation induced by psychophysiological and physical stress

Background: Although clinical assessment of cardiac autonomic modulation (CAM) usually relies on off-line heart rate variability analysis (HRVa), measured under stationary conditions according to guidelines, there is a growing interest, in sports medicine and psychophysiology, for the reliable evaluation of acute changes of CAM occurring under real-world dynamics (i.e. acute stress induced by competitions or critical situations). The aim of this study was to test, with a standardized clinical protocol inducing enhancement of sympathetic/vagal modulation, the reliability of a novel system for continuous monitoring and telemetric transmission of transient CAM changes (Vi- BioBox), provided by real-time calculation of time-variant HRV parameters and Skin Potential Response (SPR). Methods: All measurements were performed in the laboratory for clinical electrophysiology. The Vi-BioBox system (Vi-grade, Udine) consists of a wearable wireless mini-recording device connected to a textile electrode garment (Nuubo, Spain) and hands electrodes. 3 ECG and 2 SPR signal are continuously recorded (1 KHz sampling-rate) and streamed in real-time to Wintax4 (Magneti-Marelli) data logging for real-time calculation and monitoring of spectral HRV parameters and of the Root Mean Square value of two SPR signals (SPRRMS) with a proprietary custom software (Vi-BioSoft). 10 healthy volunteers (mean age 32.4±16.8 y, 50% males) underwent a 5-steps protocol: 1) 10-minutes baseline supine; 2) 10-minutes Head-up tilting 70° (HUTT); 3) 10-minutes supine recovery); 4) 20-minutes mental stress ("Mensa" preliminary Tests); 5) exercise-test at bicycle-ergometer. 12- lead ECG was continuously recorded also with Mortara Surveyor/X-Scribe and Time-variant HRV parameters were also calculated off-line with Kubios (3.0.2) software. Statistical analysis was performed with SPSS 21. Results: The quality of the Vi-BioBox signals was optimal for reproducible real-time calculation and monitoring of time-variant HRV parameters. Baseline SPRRMS activity ranged between 0.01 and 0.8 mV, with wide interindividual variability. A significant (p<0.05) increment (up to 2.6 mV) was induced by HUTT, but not by physical exercise. SPRRMS and LF/HF had similar trend along test session. Good agreement was found between HRV parameters calculated in real-time, their off-line recalculation with Kubios software and those obtained from Mortara telemetry. Conclusion: Real-time monitoring of time-variant spectral HRV parameters and of SPRRMS was reliable and reproducible. SPRRMS is an independent sensitive marker of sympathetic activation, which anticipates increments of VLF, LF and is useful to interpret CAM underlying of LF/HF changes. Real-time monitoring of CAM may be useful to improve the mechanistic understanding of acute psychophysiological stress-reactions, dysautonomic syncope, arrhythmic events initiation and for telemedicine (i.e. continuous remote monitoring of CAM in patients with heart failure)