Emotion monitoring system for drivers

Kowalczuk, Zdzisław; Czubenko, Michał; Merta, Tomasz

doi:10.1016/j.ifacol.2019.08.071

Cited by 27 publications

(13 citation statements)

References 17 publications

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“…An FER analysis has been carried out to monitor driver's mood during the whole experiment. As mentioned in the previous Section, in order to identify the concentration through a FER methodology, some works ( [22,26]) suggest to identify the neutral expression. Furthermore, the present work also considered the assumption that emotion detection can reveal driver's distraction with particular criticality in the presence of anger, sadness, and emotional agitation, as stated by Dingus et al [30] in their work about crash risk factors, and, on the contrary, the concentration can be associated with the neutral expression.…”

Section: Methodsmentioning

confidence: 99%

“…FER implies the possibility of identifying other emotions and states of mind, such as boredom and excitement [18], or engagement and frustration [19]. Driver's attention [20] is no exception; though, only a few studies about attention detection through FER in the context of driving have been proposed; for instance, Craye et al [21] used an RGB-D sensor to develop a module for detecting driver distraction and recognizing its specific type, and Kowalczuk et al [22] introduced a system to monitor the impact of emotions on driver's attention and, consequently, on driving safety. Nonetheless, several works focused on uncovering the relationship between attention and specific action units (AUs), i.e., relaxation or contraction of one or more facial muscles [23], while others directly dealt with basic emotions.…”

Section: Introductionmentioning

confidence: 99%

“…Sharma et al [26] proposed a system to figure out the concentration level of students in front of a webcam, identifying concentration with the neutral facial expression. Furthermore, according to Kowalczuk et al [22], emotions are suppressed over time, hence emotion detection can reveal distraction in specific scenarios.…”

Section: Introductionmentioning

confidence: 99%

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Can ADAS Distract Driver’s Attention? An RGB-D Camera and Deep Learning-Based Analysis

et al. 2021

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Driver inattention is the primary cause of vehicle accidents; hence, manufacturers have introduced systems to support the driver and improve safety; nonetheless, advanced driver assistance systems (ADAS) must be properly designed not to become a potential source of distraction for the driver due to the provided feedback. In the present study, an experiment involving auditory and haptic ADAS has been conducted involving 11 participants, whose attention has been monitored during their driving experience. An RGB-D camera has been used to acquire the drivers’ face data. Subsequently, these images have been analyzed using a deep learning-based approach, i.e., a convolutional neural network (CNN) specifically trained to perform facial expression recognition (FER). Analyses to assess possible relationships between these results and both ADAS activations and event occurrences, i.e., accidents, have been carried out. A correlation between attention and accidents emerged, whilst facial expressions and ADAS activations resulted to be not correlated, thus no evidence that the designed ADAS are a possible source of distraction has been found. In addition to the experimental results, the proposed approach has proved to be an effective tool to monitor the driver through the usage of non-invasive techniques.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Can ADAS Distract Driver’s Attention? An RGB-D Camera and Deep Learning-Based Analysis

et al. 2021

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“…Human emotions are also useful in psychological studies, for example, to assess or understand consumer and social trends [ 13 ]. They have also been applied in assessing the level of safety of drivers [ 14 ] by monitoring their emotional state. They were also used in the computer science field to improve software engineering processes, overcoming the limitations of usability questionnaires and helping to provide more personalized web experiences.…”

Section: Introductionmentioning

confidence: 99%

Sensing Systems for Respiration Monitoring: A Technical Systematic Review

Vanegas

Igual

Plaza

2020

Sensors

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Respiratory monitoring is essential in sleep studies, sport training, patient monitoring, or health at work, among other applications. This paper presents a comprehensive systematic review of respiration sensing systems. After several systematic searches in scientific repositories, the 198 most relevant papers in this field were analyzed in detail. Different items were examined: sensing technique and sensor, respiration parameter, sensor location and size, general system setup, communication protocol, processing station, energy autonomy and power consumption, sensor validation, processing algorithm, performance evaluation, and analysis software. As a result, several trends and the remaining research challenges of respiration sensors were identified. Long-term evaluations and usability tests should be performed. Researchers designed custom experiments to validate the sensing systems, making it difficult to compare results. Therefore, another challenge is to have a common validation framework to fairly compare sensor performance. The implementation of energy-saving strategies, the incorporation of energy harvesting techniques, the calculation of volume parameters of breathing, or the effective integration of respiration sensors into clothing are other remaining research efforts. Addressing these and other challenges outlined in the paper is a required step to obtain a feasible, robust, affordable, and unobtrusive respiration sensing system.

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“…В литературе представлено достаточное количество результатов исследований, демонстрирующих механизмы и закономерности реализации невербальной коммуникации (Кузнецов, 2014; Проскурнич, 2017; Байгужин с соавт., 2019). Установлены критерии оценки эффективного распознавания средств невербальной коммуникации (Подвигина с соавт., 2019; Domínguez-Jiménez et al, 2020), например, успешно использующиеся в автоматизированных системах мониторинга и обеспечения безопасности (Kowalczuk et al, 2019;Lin et al, 2019).…”

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The Phenomenon of Emotional Contagion in Psychology and Psychophysiology

Kudryashov¹,

Simonyan²

2020

jpps

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Abstract. The authors present a theoretical analysis of the phenomenon of "emotional contagion". Aim. The purpose of the article is to establish the content of the phenomenon of “emotional contagion" as a non-verbal form of communication that affects the cognitive, motivational and emotional spheres of the personality. Materials and methods. A theoretical analysis of scientific and methodological works devoted to the psychophysiological aspects of the perception of emotional information in the context of “emotional contagion” was performed. Results. “Emotional contagion” is considered as a form of non-verbal communication when the direct interaction of communicants is minimized or eliminated. The content of modern biopsychosocial models (theories, concepts) of emotional contagion is presented that explain the possible mechanisms of its activity: the contagion theory, "inorganic viruses"; concepts of collective emotions, interpersonal limbic regulation; models of "emotional convention", mirror neurons. The directions of research and the scope of the application of "emotional contagion" in educational activities, psychotherapy, advertising industry, political science, demography are determined. The authors focus on the positive and negative effects of the techniques of “emotional contagion”: from individual exposure as part of corrective measures to the planetary scale and regulation of the demographic situation. Conclusion. The analysis of scientific research presented in the review actualizes the need to increase the psychophysiological resources of stress resistance to modern conditions.

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Emotion monitoring system for drivers

Cited by 27 publications

References 17 publications

Can ADAS Distract Driver’s Attention? An RGB-D Camera and Deep Learning-Based Analysis

Can ADAS Distract Driver’s Attention? An RGB-D Camera and Deep Learning-Based Analysis

Sensing Systems for Respiration Monitoring: A Technical Systematic Review

The Phenomenon of Emotional Contagion in Psychology and Psychophysiology

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