Towards a driver fatigue test based on the saccadic main sequence: A partial validation by subjective report data

Stasi, Leandro L. Di; Renner, Rebekka S.; Catena, Andrés; Cañas, José J.; Velichkovsky, Boris M.; Pannasch, Sebastian

doi:10.1016/j.trc.2011.07.002

Cited by 121 publications

(83 citation statements)

References 55 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Previous research has investigated the driving duration effect on physiological and performance decrement (Schleicher et al, 2008;Di Stasi et al, 2012;Wang & Pei, 2014;Gastaldi et al, 2014). However, most of the prior research has studied the effect of short driving duration, which is defined as below two hours (Schleicher et al, 2008;Di Stasi et al, 2012;Gastaldi et al, 2014). Wang and Pei (2014) investigated the effect of four hours of driving on performance measures; however, a study looking at the possibility of using other indicators has not yet been conducted.…”

Section: Introductionmentioning

confidence: 99%

Effect Of Driving Duration On Eeg Fluctuations

Puspasari¹,

Iridiastadi

Sutalaksana

et al. 2017

IJTech

View full text Add to dashboard Cite

Road accidents are a major issue in Indonesia, and their number increases every year. Based on previous studies, mental fatigue is one of the biggest factors leading to road accidents and is majorly affected by mental workload. Driving duration is one of the factors that triggers mental fatigue. The prior literature cites electroencephalogram (EEG) measurement as the gold standard for measuring fatigue. However, there has been only limited study to examine the EEG indicators that are affected by driving duration, and the prior research still contains disagreements regarding the best EEG parameter for use in measuring fatigue. Therefore, this study aimed to evaluate the effect of driving duration on EEG fluctuation and determine the best EEG parameter related to fatigue. Seven participants were asked to spend three hours driving in a medium-fidelity simulator. A one-way ANOVA and correlation analysis were performed to measure the effect of driving duration on the EEG indicators and determine the correlation of the indicators. A Receiver Operating Characteristics (ROC) curve was also utilized to determine the variable with the greatest correlation with the subjective sleepiness indices. The results showed that at the end of three hours' driving, there was an increment in delta and theta activities, followed by a decrement in alpha and beta activities. In addition, the correlation of all bands was significant, with positive results for the alpha-beta and theta-delta bands, and a negative result in relation to each other. Furthermore, the results from the ROC curve revealed the Relative Power Ratio (RPR) of theta, the RPR of alpha, and the ratio of θ/α+β to be the best indicators among others, demonstrating a high degree of accuracy (above 85%).

show abstract

Section: Introductionmentioning

confidence: 99%

Effect Of Driving Duration On Eeg Fluctuations

Puspasari¹,

Iridiastadi

Sutalaksana

et al. 2017

IJTech

View full text Add to dashboard Cite

show abstract

“…Concerning the amount of eye movements (Di Stasi et al 2012), saccades can be classified as very large val- ues when they are more than 300 pixels, while persistent fixations cause saccades of about 70 pixels. Generally, there could not be a null value of saccades, as the human eye needs for activity in order to maintain the image on the retina.…”

Section: Importance Given By the Driver To Objectsmentioning

confidence: 99%

“…These tools commonly used to assess the desirability of a product within a supermarket or the ease of use of particular software, can detect the visual strategies during the travel (Di Stasi et al 2012). …”

Section: Introductionmentioning

confidence: 99%

A Procedure for Evaluating the Influence of Road Context on Drivers’ Visual Behaviour

2016

View full text Add to dashboard Cite

Abstract. In this paper, we investigated drivers' visual behaviour while travelling a road regularly opened to traffic in order to evaluate the effectiveness of the traditional scientific models and propose, at the same time, further measures useful for understanding the complex phenomenon. As is known, drivers acquire the necessary information for knowing the road geometry by visually detecting certain areas of the surrounding context. Some models in the literature have shown in a simple and convincing way these mechanisms, but they are valid only with specific assumptions, often very restrictive, such as a two-lane road, horizontal sign clearly visible and no interaction with other vehicles. For this reason, in this study we wanted to investigate different conditions, by estimating the visual strategy of some regular drivers on a three-lane road in presence of other vehicles. The visual behaviour was surveyed with the Tobii Glasses Eye Tracker and the resulting raw data were further manipulated by us to extract more useful information for our purposes. In particular, we quantified the driver's dedicated attention to the various elements present inside the environmental context, both static (road edges, road signs, dashboard, etc.) and dynamic (other vehicles), meaning by this term those that could potentially collide with the trajectories of our vehicle. The achieved results, highlighting the limits of validity of some recent studies, contain some proposed indexes useful to give a better understanding of the visual behaviour in order to detect any eventual weakness of the road.

show abstract

“…Using these methods allows the researcher to make inferences about the connection between interface design and mental workload, which should provide useful information for the design of interfaces that minimise mental workload. An interesting example is a study, in which the authors investigated whether a break during a long drive helps the driver to recover from cognitive fatigue, measured as saccade peak velocities (Di Stasi et al, 2012). Although a break during a long drive may be a refreshing experience, the study revealed that it did not actually benefit the driver in terms of fatigue.…”

Section: Neurosciencementioning

confidence: 99%

“…This necessitates phenomenology, which is the study of the structures of experience (Heidegger, 1927;Husserl, 1913). Phenomenology can thus be used to clarify the contrast between experience and experiment, which for example helps in discussing the contradictory findings about fatigue and breaks in long driving (Di Stasi et al, 2012). An experimental result cannot be falsified or validated by experience, but it is in our experience in which we decide whether the results are meaningful and can be considered relevant.…”

Section: Subjectivismmentioning

confidence: 99%

Quick Affective Judgments

Jokinen

Silvennoinen

Perälä

et al. 2015

Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems

View full text Add to dashboard Cite

Esitetään Jyväskylän yliopiston informaatioteknologian tiedekunnan suostumuksella julkisesti tarkastettavaksi yliopiston Agora-rakennuksen auditoriossa 2 kesäkuun 6. päivänä 2015 kello 12.Academic dissertation to be publicly discussed, by permission of the Faculty of Information Technology of the University of Jyväskylä, in building Agora, auditorium 2, on June 6, 2015 at 12 o'clock noon. UNIVERSITY OF JYVÄSKYLÄ JYVÄSKYLÄ 2015User Researchers of human-technology interaction have started to emphasise the importance of technology users' experiences: experience is an important aspect of daily life, and thus it should be taken into account in human-technology interaction research and in design of new technologies. However, scientific study of conscious experience is difficult, and the field of user experience research is afflicted by incompatible definitions, assumptions, and guidelines for investigating users' experiences and designing for them. This problem is emphasised by the lack of foundational framework, which would allow for comparing the metascientific and methodological assumptions behind different accounts of user experience. Here, such an account is presented in the form of foundational analysis of human-technology interaction. The resulting methodological framework is used to review theories of user experience with a conclusion that while the topics investigated under the umbrella of user experience seem to be the correct ones, their operationalisation lacks proper psychological basis. As a result of the foundational analysis of user experience, one of the core concepts related to conscious experience, emotion, is introduced, and different psychological accounts for it are reviewed using the methodological framework. Appraisal theory of emotion is shown to provide methodologically the best option for studying emotional user experience. A review of empirical studies, included as the articles of this thesis, supports this conclusion. Emotional user experience is discussed in terms of (1) a competence-frustration model, (2) individual coping differences in human-technology interaction, (3) mental contents of emotional experience, and (4) the non-conscious cognitive processes associated with the appraisal process. These elaborations can be used to investigate what users experience emotionally when they interact with technology, and explain these experiences. Such investigations should provide valid knowledge structures for designers, who aim to create technologies with certain experience goals.Keywords: user experience, emotion, appraisal, mental content Author's address ACKNOWLEDGEMENTSAs I started my studies on emotion in human-technology interaction over four years ago, I wasn't that familiar with the topic, nor with the field of humantechnology interaction in general. What I've learned during my doctoral studies, and what I hopefully can teach to others, has not been achieved by myself alone, but with the help of multiple people: colleagues in academia, industrial partners, family members, study partic...

show abstract

Towards a driver fatigue test based on the saccadic main sequence: A partial validation by subjective report data

Cited by 121 publications

References 55 publications

Effect Of Driving Duration On Eeg Fluctuations

Effect Of Driving Duration On Eeg Fluctuations

A Procedure for Evaluating the Influence of Road Context on Drivers’ Visual Behaviour

Quick Affective Judgments

Contact Info

Product

Resources

About