scholarly journals ConTEXT: Context-aware Adaptive SMS Client for Drivers to Reduce Risky Driving Behaviors

Author(s):  
Inayat Khan ◽  
Shah Khusro

Abstract Text messaging while driving has been considered a dangerous activity that may lead to serious injuries and traffic fatalities. Several assistive technologies and solutions have been developed to simplify texting activity. However, due to inconsistent and complex interface design, lack of logical navigational order, lack of context, complicated text-entry layouts, and laborious activities, the existing texting-related activities can lead to accidents. This paper recognized the risky driving patterns using the real-time AutoLog application. Based on this risky driving behavior, we have proposed ConTEXT, a usable SMS client, to overcome the issues pertaining to the usability of textual activities on smartphones while driving. ConTEXT application is evaluated both empirically as well as through real-time AutoLog application. We have collected data from 117 drivers through a questionnaire. The results show that the data is found reliable also alpha scores for all factors seem internally consistent as it ranges from 0.70 to 0.79 which is good. Similarly, we have reported Principal Component Factor Analysis (PCFA), which was found satisfied and appropriate as the Eigenvalue for all the factors is greater than zero. Furthermore, results obtained from the AutoLog dataset show an improved user experience, better control over the touch screen with minimum visual, physical, and mental load.

Author(s):  
Sheila G. Klauer ◽  
Tina B. Sayer ◽  
Peter Baynes ◽  
Gayatri Ankem

Introduction. Motor vehicle crashes remain the leading cause of fatalities among teens in the U.S. (National Center for Injury Prevention and Control, 2013). Prior research suggests that real-time and post hoc feedback can improve teen driver behavior. The Driver Coach Study (DCS) aimed to improve teens’ safe driving habits by providing them real-time feedback and post hoc feedback to a broader range of risky driving behaviors that have never been used in previous studies. Exposure data were also collected so that rates of risky driving behaviors over time could be assessed. Post hoc feedback, which included an electronic report card of risky driving behavior as well as video clips, was provided to both teens and parents via email and secure website link. Method. Ninety-two teen/parent dyads were recruited in southwest Virginia to have a data acquisition system (DAS) installed in their vehicles within two weeks of receiving their learner’s permit. Data were collected through the nine-month (minimum) learner’s permit phase plus seven months of provisional licensure. Feedback was only provided for the first six months of post licensure, then turned off to assess whether teenagers returned to unsafe driving behavior. Trained data coders reviewed 15 seconds of video surrounding each risky driving maneuver, and recorded driver errors such as poor vehicle control, poor speed selection, drowsiness, etc., for each event. Results. In this paper, the relationship between driver coaching and driver errors will be examined across the six-month feedback phase and also compared to the seventh month when feedback was turned off. Conclusions. This study has implications for the design of future monitoring and feedback systems, as it is currently unknown whether these devices can improve novice drivers’ crash rates.


2010 ◽  
Vol 69 (4) ◽  
pp. 233-238 ◽  
Author(s):  
Nolwenn Morisset ◽  
Florence Terrade ◽  
Alain Somat

Les recherches dans le domaine de la santé, et notamment en matière de conduite automobile, attestent que le jugement subjectif du risque (comparatif et absolu) et l’auto-efficacité perçue sont impliqués dans les comportements à risque. Cette étude avait pour objectif d’étudier l’influence de l’auto-efficacité perçue sur le jugement subjectif du risque, évalué au moyen d’une mesure indirecte, et de tester le rôle médiateur de ce facteur entre l’auto-efficacité perçue et les comportements auto-déclarés. Les participants, 90 hommes, lisaient deux scénarii décrivant les deux comportements les plus impliqués dans l’accidentologie: la vitesse et l’alcool au volant. Les résultats ne montrent pas de lien significatif entre l’auto-efficacité perçue et le score de jugement comparatif mais une relation significative avec les deux évaluations absolues du risque (autrui et soi). De plus, le jugement absolu du risque pour soi médiatise partiellement la relation entre auto-efficacité perçue et comportements auto-déclarés relatifs aux deux risques routiers étudiés.


Metabolites ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 265
Author(s):  
Ruchi Sharma ◽  
Wenzhe Zang ◽  
Menglian Zhou ◽  
Nicole Schafer ◽  
Lesa A. Begley ◽  
...  

Asthma is heterogeneous but accessible biomarkers to distinguish relevant phenotypes remain lacking, particularly in non-Type 2 (T2)-high asthma. Moreover, common clinical characteristics in both T2-high and T2-low asthma (e.g., atopy, obesity, inhaled steroid use) may confound interpretation of putative biomarkers and of underlying biology. This study aimed to identify volatile organic compounds (VOCs) in exhaled breath that distinguish not only asthmatic and non-asthmatic subjects, but also atopic non-asthmatic controls and also by variables that reflect clinical differences among asthmatic adults. A total of 73 participants (30 asthma, eight atopic non-asthma, and 35 non-asthma/non-atopic subjects) were recruited for this pilot study. A total of 79 breath samples were analyzed in real-time using an automated portable gas chromatography (GC) device developed in-house. GC-mass spectrometry was also used to identify the VOCs in breath. Machine learning, linear discriminant analysis, and principal component analysis were used to identify the biomarkers. Our results show that the portable GC was able to complete breath analysis in 30 min. A set of nine biomarkers distinguished asthma and non-asthma/non-atopic subjects, while sets of two and of four biomarkers, respectively, further distinguished asthmatic from atopic controls, and between atopic and non-atopic controls. Additional unique biomarkers were identified that discriminate subjects by blood eosinophil levels, obese status, inhaled corticosteroid treatment, and also acute upper respiratory illnesses within asthmatic groups. Our work demonstrates that breath VOC profiling can be a clinically accessible tool for asthma diagnosis and phenotyping. A portable GC system is a viable option for rapid assessment in asthma.


2021 ◽  
Vol 11 (16) ◽  
pp. 7197
Author(s):  
Yourui Tong ◽  
Bochen Jia ◽  
Shan Bao

Warning pedestrians of oncoming vehicles is critical to improving pedestrian safety. Due to the limitations of a pedestrian’s carrying capacity, it is crucial to find an effective solution to provide warnings to pedestrians in real-time. Limited numbers of studies focused on warning pedestrians of oncoming vehicles. Few studies focused on developing visual warning systems for pedestrians through wearable devices. In this study, various real-time projection algorithms were developed to provide accurate warning information in a timely way. A pilot study was completed to test the algorithm and the user interface design. The projection algorithms can update the warning information and correctly fit it into an easy-to-understand interface. By using this system, timely warning information can be sent to those pedestrians who have lower situational awareness or obstructed view to protect them from potential collisions. It can work well when the sightline is blocked by obstructions.


Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2869
Author(s):  
Jiaen Wu ◽  
Kiran Kuruvithadam ◽  
Alessandro Schaer ◽  
Richie Stoneham ◽  
George Chatzipirpiridis ◽  
...  

The deterioration of gait can be used as a biomarker for ageing and neurological diseases. Continuous gait monitoring and analysis are essential for early deficit detection and personalized rehabilitation. The use of mobile and wearable inertial sensor systems for gait monitoring and analysis have been well explored with promising results in the literature. However, most of these studies focus on technologies for the assessment of gait characteristics, few of them have considered the data acquisition bandwidth of the sensing system. Inadequate sampling frequency will sacrifice signal fidelity, thus leading to an inaccurate estimation especially for spatial gait parameters. In this work, we developed an inertial sensor based in-shoe gait analysis system for real-time gait monitoring and investigated the optimal sampling frequency to capture all the information on walking patterns. An exploratory validation study was performed using an optical motion capture system on four healthy adult subjects, where each person underwent five walking sessions, giving a total of 20 sessions. Percentage mean absolute errors (MAE%) obtained in stride time, stride length, stride velocity, and cadence while walking were 1.19%, 1.68%, 2.08%, and 1.23%, respectively. In addition, an eigenanalysis based graphical descriptor from raw gait cycle signals was proposed as a new gait metric that can be quantified by principal component analysis to differentiate gait patterns, which has great potential to be used as a powerful analytical tool for gait disorder diagnostics.


2020 ◽  
Vol 1 (2) ◽  
pp. 1-36
Author(s):  
Ranak Roy Chowdhury ◽  
Muhammad Abdullah Adnan ◽  
Rajesh K. Gupta

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