Vehicle-based drowsy driver detection : current status and future prospects

DOT National Transportation Integrated Search

1994-01-01

Driver drowsiness is a major, though elusive, cause of traffic crashes. As part of its : IVHS/human factors program, NHTSA is supporting research to develop in-vehicle systems . : to continuously monitor driver alertness and performance. Scientific s...

Electrodermal Activity Based Wearable Device for Drowsy Drivers

NASA Astrophysics Data System (ADS)

Malathi, D.; Dorathi Jayaseeli, JD; Madhuri, S.; Senthilkumar, K.

2018-04-01

Road safety and road accident mortality rate are a serious concern for the government. With rise in fatal road accidents, who’s leading cause is the driver being drowsy behind the wheel, measures to alleviate this problem becomes the prime task. To meet the purpose, methods adopted must be of minimum discomfort for the driver, easy to install, provide good detection accuracy and timely alert to circumvent a probable accident. A good candidate to meet these specifications is EDA. As it detects the level of sweat which directly corresponds to the mental state of the person, using EDA for the purposes of driver safety forms a good option. The novelty of this project lies in making use of EDA as a measure to detect if a person is drowsy or not. Much of the challenge lies in building a device equipped with the necessary sensors and processing the data on real-time. The novelty of this work lies in development of an embedded device interfaced with sensors and actuators to detect and alert a driver when found drowsy using sweat as a parameter.

Challenges in detecting drowsiness based on driver’s behavior

NASA Astrophysics Data System (ADS)

Triyanti, V.; Iridiastadi, H.

2017-12-01

Drowsiness while driving has been a critical issue within the context of transportation safety. A number of approaches have been developed to reduce the risks of drowsy drivers. The mechanisms in detecting fatigue and sleepiness while driving has been categorized into three broad approaches, including vehicle-based, physiological-based, and behavior-based approaches. This paper will discuss recent studies in recognizing drowsy drivers based on their behaviors, particularly changes in eyes and facial characteristics. This paper will also address challenges in capturing aspects of natural expressions, driver responses, behavior, and task environment associated with sleepiness. Additionally, a number of technical aspects should be seriously considered, including correctly capturing face and eye characteristics from unwanted movements, unsuitable task environments, technological limitations, and individual differences.

Driver drowsiness classification using fuzzy wavelet-packet-based feature-extraction algorithm.

PubMed

Khushaba, Rami N; Kodagoda, Sarath; Lal, Sara; Dissanayake, Gamini

2011-01-01

Driver drowsiness and loss of vigilance are a major cause of road accidents. Monitoring physiological signals while driving provides the possibility of detecting and warning of drowsiness and fatigue. The aim of this paper is to maximize the amount of drowsiness-related information extracted from a set of electroencephalogram (EEG), electrooculogram (EOG), and electrocardiogram (ECG) signals during a simulation driving test. Specifically, we develop an efficient fuzzy mutual-information (MI)- based wavelet packet transform (FMIWPT) feature-extraction method for classifying the driver drowsiness state into one of predefined drowsiness levels. The proposed method estimates the required MI using a novel approach based on fuzzy memberships providing an accurate-information content-estimation measure. The quality of the extracted features was assessed on datasets collected from 31 drivers on a simulation test. The experimental results proved the significance of FMIWPT in extracting features that highly correlate with the different drowsiness levels achieving a classification accuracy of 95%-- 97% on an average across all subjects.

A Hybrid Approach to Detect Driver Drowsiness Utilizing Physiological Signals to Improve System Performance and Wearability.

PubMed

Awais, Muhammad; Badruddin, Nasreen; Drieberg, Micheal

2017-08-31

Driver drowsiness is a major cause of fatal accidents, injury, and property damage, and has become an area of substantial research attention in recent years. The present study proposes a method to detect drowsiness in drivers which integrates features of electrocardiography (ECG) and electroencephalography (EEG) to improve detection performance. The study measures differences between the alert and drowsy states from physiological data collected from 22 healthy subjects in a driving simulator-based study. A monotonous driving environment is used to induce drowsiness in the participants. Various time and frequency domain feature were extracted from EEG including time domain statistical descriptors, complexity measures and power spectral measures. Features extracted from the ECG signal included heart rate (HR) and heart rate variability (HRV), including low frequency (LF), high frequency (HF) and LF/HF ratio. Furthermore, subjective sleepiness scale is also assessed to study its relationship with drowsiness. We used paired t -tests to select only statistically significant features ( p < 0.05), that can differentiate between the alert and drowsy states effectively. Significant features of both modalities (EEG and ECG) are then combined to investigate the improvement in performance using support vector machine (SVM) classifier. The other main contribution of this paper is the study on channel reduction and its impact to the performance of detection. The proposed method demonstrated that combining EEG and ECG has improved the system's performance in discriminating between alert and drowsy states, instead of using them alone. Our channel reduction analysis revealed that an acceptable level of accuracy (80%) could be achieved by combining just two electrodes (one EEG and one ECG), indicating the feasibility of a system with improved wearability compared with existing systems involving many electrodes. Overall, our results demonstrate that the proposed method can be a viable solution for a practical driver drowsiness system that is both accurate and comfortable to wear.

A Hybrid Approach to Detect Driver Drowsiness Utilizing Physiological Signals to Improve System Performance and Wearability

PubMed Central

Badruddin, Nasreen

2017-01-01

Driver drowsiness is a major cause of fatal accidents, injury, and property damage, and has become an area of substantial research attention in recent years. The present study proposes a method to detect drowsiness in drivers which integrates features of electrocardiography (ECG) and electroencephalography (EEG) to improve detection performance. The study measures differences between the alert and drowsy states from physiological data collected from 22 healthy subjects in a driving simulator-based study. A monotonous driving environment is used to induce drowsiness in the participants. Various time and frequency domain feature were extracted from EEG including time domain statistical descriptors, complexity measures and power spectral measures. Features extracted from the ECG signal included heart rate (HR) and heart rate variability (HRV), including low frequency (LF), high frequency (HF) and LF/HF ratio. Furthermore, subjective sleepiness scale is also assessed to study its relationship with drowsiness. We used paired t-tests to select only statistically significant features (p < 0.05), that can differentiate between the alert and drowsy states effectively. Significant features of both modalities (EEG and ECG) are then combined to investigate the improvement in performance using support vector machine (SVM) classifier. The other main contribution of this paper is the study on channel reduction and its impact to the performance of detection. The proposed method demonstrated that combining EEG and ECG has improved the system’s performance in discriminating between alert and drowsy states, instead of using them alone. Our channel reduction analysis revealed that an acceptable level of accuracy (80%) could be achieved by combining just two electrodes (one EEG and one ECG), indicating the feasibility of a system with improved wearability compared with existing systems involving many electrodes. Overall, our results demonstrate that the proposed method can be a viable solution for a practical driver drowsiness system that is both accurate and comfortable to wear. PMID:28858220

Online Detection of Driver Fatigue Using Steering Wheel Angles for Real Driving Conditions.

PubMed

Li, Zuojin; Li, Shengbo Eben; Li, Renjie; Cheng, Bo; Shi, Jinliang

2017-03-02

This paper presents a drowsiness on-line detection system for monitoring driver fatigue level under real driving conditions, based on the data of steering wheel angles (SWA) collected from sensors mounted on the steering lever. The proposed system firstly extracts approximate entropy (ApEn)featuresfromfixedslidingwindowsonreal-timesteeringwheelanglestimeseries. Afterthat, this system linearizes the ApEn features series through an adaptive piecewise linear fitting using a given deviation. Then, the detection system calculates the warping distance between the linear features series of the sample data. Finally, this system uses the warping distance to determine the drowsiness state of the driver according to a designed binary decision classifier. The experimental data were collected from 14.68 h driving under real road conditions, including two fatigue levels: "wake" and "drowsy". The results show that the proposed system is capable of working online with an average 78.01% accuracy, 29.35% false detections of the "awake" state, and 15.15% false detections of the "drowsy" state. The results also confirm that the proposed method based on SWA signal is valuable for applications in preventing traffic accidents caused by driver fatigue.

Presenting a model for dynamic facial expression changes in detecting drivers’ drowsiness

PubMed Central

Karchani, Mohsen; Mazloumi, Adel; Saraji, Gebraeil Nasl; Gharagozlou, Faramarz; Nahvi, Ali; Haghighi, Khosro Sadeghniiat; Abadi, Bahador Makki; Foroshani, Abbas Rahimi

2015-01-01

Drowsiness while driving is a major cause of accidents. A driver fatigue detection system that is designed to sound an alarm, when appropriate, can prevent many accidents that sometime leads to the loss of life and property. In this paper, we classify drowsiness detection sensors and their strong and weak points. A compound model is proposed that uses image processing techniques to study the dynamic changes of the face to recognize drowsiness during driving. PMID:26120417

Drowsy driver mobile application: Development of a novel scleral-area detection method.

PubMed

Mohammad, Faisal; Mahadas, Kausalendra; Hung, George K

2017-10-01

A reliable and practical app for mobile devices was developed to detect driver drowsiness. It consisted of two main components: a Haar cascade classifier, provided by a computer vision framework called OpenCV, for face/eye detection; and a dedicated JAVA software code for image processing that was applied over a masked region circumscribing the eye. A binary threshold was performed over the masked region to provide a quantitative measure of the number of white pixels in the sclera, which represented the state of eye opening. A continuously low white-pixel count would indicate drowsiness, thereby triggering an alarm to alert the driver. This system was successfully implemented on: (1) a static face image, (2) two subjects under laboratory conditions, and (3) a subject in a vehicle environment. Copyright © 2017 Elsevier Ltd. All rights reserved.

Eye blink detection for different driver states in conditionally automated driving and manual driving using EOG and a driver camera.

PubMed

Schmidt, Jürgen; Laarousi, Rihab; Stolzmann, Wolfgang; Karrer-Gauß, Katja

2018-06-01

In this article, we examine the performance of different eye blink detection algorithms under various constraints. The goal of the present study was to evaluate the performance of an electrooculogram- and camera-based blink detection process in both manually and conditionally automated driving phases. A further comparison between alert and drowsy drivers was performed in order to evaluate the impact of drowsiness on the performance of blink detection algorithms in both driving modes. Data snippets from 14 monotonous manually driven sessions (mean 2 h 46 min) and 16 monotonous conditionally automated driven sessions (mean 2 h 45 min) were used. In addition to comparing two data-sampling frequencies for the electrooculogram measures (50 vs. 25 Hz) and four different signal-processing algorithms for the camera videos, we compared the blink detection performance of 24 reference groups. The analysis of the videos was based on very detailed definitions of eyelid closure events. The correct detection rates for the alert and manual driving phases (maximum 94%) decreased significantly in the drowsy (minus 2% or more) and conditionally automated (minus 9% or more) phases. Blinking behavior is therefore significantly impacted by drowsiness as well as by automated driving, resulting in less accurate blink detection.

Estimating Driving Performance Based on EEG Spectrum Analysis

NASA Astrophysics Data System (ADS)

Lin, Chin-Teng; Wu, Ruei-Cheng; Jung, Tzyy-Ping; Liang, Sheng-Fu; Huang, Teng-Yi

2005-12-01

The growing number of traffic accidents in recent years has become a serious concern to society. Accidents caused by driver's drowsiness behind the steering wheel have a high fatality rate because of the marked decline in the driver's abilities of perception, recognition, and vehicle control abilities while sleepy. Preventing such accidents caused by drowsiness is highly desirable but requires techniques for continuously detecting, estimating, and predicting the level of alertness of drivers and delivering effective feedbacks to maintain their maximum performance. This paper proposes an EEG-based drowsiness estimation system that combines electroencephalogram (EEG) log subband power spectrum, correlation analysis, principal component analysis, and linear regression models to indirectly estimate driver's drowsiness level in a virtual-reality-based driving simulator. Our results demonstrated that it is feasible to accurately estimate quantitatively driving performance, expressed as deviation between the center of the vehicle and the center of the cruising lane, in a realistic driving simulator.

Improving Driver Alertness through Music Selection Using a Mobile EEG to Detect Brainwaves

PubMed Central

Liu, Ning-Han; Chiang, Cheng-Yu; Hsu, Hsiang-Ming

2013-01-01

Driving safety has become a global topic of discussion with the recent development of the Smart Car concept. Many of the current car safety monitoring systems are based on image discrimination techniques, such as sensing the vehicle drifting from the main road, or changes in the driver's facial expressions. However, these techniques are either too simplistic or have a low success rate as image processing is easily affected by external factors, such as weather and illumination. We developed a drowsiness detection mechanism based on an electroencephalogram (EEG) reading collected from the driver with an off-the-shelf mobile sensor. This sensor employs wireless transmission technology and is suitable for wear by the driver of a vehicle. The following classification techniques were incorporated: Artificial Neural Networks, Support Vector Machine, and k Nearest Neighbor. These classifiers were integrated with integration functions after a genetic algorithm was first used to adjust the weighting for each classifier in the integration function. In addition, since past studies have shown effects of music on a person's state-of-mind, we propose a personalized music recommendation mechanism as a part of our system. Through the in-car stereo system, this music recommendation mechanism can help prevent a driver from becoming drowsy due to monotonous road conditions. Experimental results demonstrate the effectiveness of our proposed drowsiness detection method to determine a driver's state of mind, and the music recommendation system is therefore able to reduce drowsiness. PMID:23803789

Fusion of Optimized Indicators from Advanced Driver Assistance Systems (ADAS) for Driver Drowsiness Detection

PubMed Central

Daza, Iván G.; Bergasa, Luis M.; Bronte, Sebastián; Yebes, J. Javier; Almazán, Javier; Arroyo, Roberto

2014-01-01

This paper presents a non-intrusive approach for monitoring driver drowsiness using the fusion of several optimized indicators based on driver physical and driving performance measures, obtained from ADAS (Advanced Driver Assistant Systems) in simulated conditions. The paper is focused on real-time drowsiness detection technology rather than on long-term sleep/awake regulation prediction technology. We have developed our own vision system in order to obtain robust and optimized driver indicators able to be used in simulators and future real environments. These indicators are principally based on driver physical and driving performance skills. The fusion of several indicators, proposed in the literature, is evaluated using a neural network and a stochastic optimization method to obtain the best combination. We propose a new method for ground-truth generation based on a supervised Karolinska Sleepiness Scale (KSS). An extensive evaluation of indicators, derived from trials over a third generation simulator with several test subjects during different driving sessions, was performed. The main conclusions about the performance of single indicators and the best combinations of them are included, as well as the future works derived from this study. PMID:24412904

Driver drowsiness detection using multimodal sensor fusion

NASA Astrophysics Data System (ADS)

Andreeva, Elena O.; Aarabi, Parham; Philiastides, Marios G.; Mohajer, Keyvan; Emami, Majid

2004-04-01

This paper proposes a multi-modal sensor fusion algorithm for the estimation of driver drowsiness. Driver sleepiness is believed to be responsible for more than 30% of passenger car accidents and for 4% of all accident fatalities. In commercial vehicles, drowsiness is blamed for 58% of single truck accidents and 31% of commercial truck driver fatalities. This work proposes an innovative automatic sleep-onset detection system. Using multiple sensors, the driver"s body is studied as a mechanical structure of springs and dampeners. The sleep-detection system consists of highly sensitive triple-axial accelerometers to monitor the driver"s upper body in 3-D. The subject is modeled as a linear time-variant (LTV) system. An LMS adaptive filter estimation algorithm generates the transfer function (i.e. weight coefficients) for this LTV system. Separate coefficients are generated for the awake and asleep states of the subject. These coefficients are then used to train a neural network. Once trained, the neural network classifies the condition of the driver as either awake or asleep. The system has been tested on a total of 8 subjects. The tests were conducted on sleep-deprived individuals for the sleep state and on fully awake individuals for the awake state. When trained and tested on the same subject, the system detected sleep and awake states of the driver with a success rate of 95%. When the system was trained on three subjects and then retested on a fourth "unseen" subject, the classification rate dropped to 90%. Furthermore, it was attempted to correlate driver posture and sleepiness by observing how car vibrations propagate through a person"s body. Eight additional subjects were studied for this purpose. The results obtained in this experiment proved inconclusive which was attributed to significant differences in the individual habitual postures.

Improving Night Time Driving Safety Using Vision-Based Classification Techniques.

PubMed

Chien, Jong-Chih; Chen, Yong-Sheng; Lee, Jiann-Der

2017-09-24

The risks involved in nighttime driving include drowsy drivers and dangerous vehicles. Prominent among the more dangerous vehicles around at night are the larger vehicles which are usually moving faster at night on a highway. In addition, the risk level of driving around larger vehicles rises significantly when the driver's attention becomes distracted, even for a short period of time. For the purpose of alerting the driver and elevating his or her safety, in this paper we propose two components for any modern vision-based Advanced Drivers Assistance System (ADAS). These two components work separately for the single purpose of alerting the driver in dangerous situations. The purpose of the first component is to ascertain that the driver would be in a sufficiently wakeful state to receive and process warnings; this is the driver drowsiness detection component. The driver drowsiness detection component uses infrared images of the driver to analyze his eyes' movements using a MSR plus a simple heuristic. This component issues alerts to the driver when the driver's eyes show distraction and are closed for a longer than usual duration. Experimental results show that this component can detect closed eyes with an accuracy of 94.26% on average, which is comparable to previous results using more sophisticated methods. The purpose of the second component is to alert the driver when the driver's vehicle is moving around larger vehicles at dusk or night time. The large vehicle detection component accepts images from a regular video driving recorder as input. A bi-level system of classifiers, which included a novel MSR-enhanced KAZE-base Bag-of-Features classifier, is proposed to avoid false negatives. In both components, we propose an improved version of the Multi-Scale Retinex (MSR) algorithm to augment the contrast of the input. Several experiments were performed to test the effects of the MSR and each classifier, and the results are presented in experimental results section of this paper.

Assessment of a drowsy driver warning system for heavy-vehicle drivers : final report

DOT National Transportation Integrated Search

2009-04-01

Drowsiness has a globally negative impact on performance, slowing reaction time, decreasing situational awareness, and impairing judgment. A field operational test of an early prototype Drowsy Driver Warning System was conducted as a result of 12 yea...

Improving Night Time Driving Safety Using Vision-Based Classification Techniques

PubMed Central

Chien, Jong-Chih; Chen, Yong-Sheng; Lee, Jiann-Der

2017-01-01

The risks involved in nighttime driving include drowsy drivers and dangerous vehicles. Prominent among the more dangerous vehicles around at night are the larger vehicles which are usually moving faster at night on a highway. In addition, the risk level of driving around larger vehicles rises significantly when the driver’s attention becomes distracted, even for a short period of time. For the purpose of alerting the driver and elevating his or her safety, in this paper we propose two components for any modern vision-based Advanced Drivers Assistance System (ADAS). These two components work separately for the single purpose of alerting the driver in dangerous situations. The purpose of the first component is to ascertain that the driver would be in a sufficiently wakeful state to receive and process warnings; this is the driver drowsiness detection component. The driver drowsiness detection component uses infrared images of the driver to analyze his eyes’ movements using a MSR plus a simple heuristic. This component issues alerts to the driver when the driver’s eyes show distraction and are closed for a longer than usual duration. Experimental results show that this component can detect closed eyes with an accuracy of 94.26% on average, which is comparable to previous results using more sophisticated methods. The purpose of the second component is to alert the driver when the driver’s vehicle is moving around larger vehicles at dusk or night time. The large vehicle detection component accepts images from a regular video driving recorder as input. A bi-level system of classifiers, which included a novel MSR-enhanced KAZE-base Bag-of-Features classifier, is proposed to avoid false negatives. In both components, we propose an improved version of the Multi-Scale Retinex (MSR) algorithm to augment the contrast of the input. Several experiments were performed to test the effects of the MSR and each classifier, and the results are presented in experimental results section of this paper. PMID:28946643

Identification of common features of vehicle motion under drowsy/distracted driving: A case study in Wuhan, China.

PubMed

Chen, Zhijun; Wu, Chaozhong; Zhong, Ming; Lyu, Nengchao; Huang, Zhen

2015-08-01

Drowsy/distracted driving has become one of the leading causes of traffic crash. Only certain particular drowsy/distracted driving behaviors have been studied by previous studies, which are mainly based on dedicated sensor devices such as bio and visual sensors. The objective of this study is to extract the common features for identifying drowsy/distracted driving through a set of common vehicle motion parameters. An intelligent vehicle was used to collect vehicle motion parameters. Fifty licensed drivers (37 males and 13 females, M=32.5 years, SD=6.2) were recruited to carry out road experiments in Wuhan, China and collecting vehicle motion data under four driving scenarios including talking, watching roadside, drinking and under the influence of drowsiness. For the first scenario, the drivers were exposed to a set of questions and asked to repeat a few sentences that had been proved valid in inducing driving distraction. Watching roadside, drinking and driving under drowsiness were assessed by an observer and self-reporting from the drivers. The common features of vehicle motions under four types of drowsy/distracted driving were analyzed using descriptive statistics and then Wilcoxon rank sum test. The results indicated that there was a significant difference of lateral acceleration rates and yaw rate acceleration between "normal driving" and drowsy/distracted driving. Study results also shown that, under drowsy/distracted driving, the lateral acceleration rates and yaw rate acceleration were significantly larger from the normal driving. The lateral acceleration rates were shown to suddenly increase or decrease by more than 2.0m/s(3) and the yaw rate acceleration by more than 2.5°/s(2). The standard deviation of acceleration rate (SDA) and standard deviation of yaw rate acceleration (SDY) were identified to as the common features of vehicle motion for distinguishing the drowsy/distracted driving from the normal driving. In order to identify a time window for effectively extracting the two common features, a double-window method was used and the optimized "Parent Window" and "Child Window" were found to be 55s and 6s, respectively. The study results can be used to develop a driving assistant system, which can warn drivers when any one of the four types of drowsy/distracted driving is detected. Copyright © 2015. Published by Elsevier Ltd.

Driver Performance in the Moments Surrounding a Microsleep

PubMed Central

Boyle, Linda Ng; Tippin, Jon; Paul, Amit; Rizzo, Matthew

2009-01-01

This study examined if individuals who are at increased risk for drowsy-driving because of obstructive sleep apnea syndrome (OSAS), have impairments in driving performance in the moments during microsleep episodes as opposed to during periods of wakefulness. Twenty-four licensed drivers diagnosed with OSAS based on standard clinical and polysomnographic criteria, participated in an hour-long drive in a high-fidelity driving simulator with synchronous electroencephalographic (EEG) recordings for identification of microsleeps. The drivers showed significant deterioration in vehicle control during the microsleep episodes compared to driving performance in the absence of microsleeps on equivalent segments of roadway. The degree of performance decrement correlated with microsleep duration, particularly on curved roads. Results indicate that driving performance deteriorates during microsleep episodes. Detecting microsleeps in real-time and identifying how these episodes of transition between wakefulness and sleep impair driver performance is relevant to the design and implementation of countermeasures such as drowsy driver detection and alerting systems that use EEG technology. PMID:20090864

An assessment of driver drowsiness, distraction, and performance in a naturalistic setting

DOT National Transportation Integrated Search

2011-02-01

This report documents the results of a study to characterize episodes of driver drowsiness and to assess the impact of drowsiness on driving performance. This data mining effort performed additional analyses on the data collected in an earlier FMCSA ...

Online Detection of Driver Fatigue Using Steering Wheel Angles for Real Driving Conditions

PubMed Central

Li, Zuojin; Li, Shengbo Eben; Li, Renjie; Cheng, Bo; Shi, Jinliang

2017-01-01

This paper presents a drowsiness on-line detection system for monitoring driver fatigue level under real driving conditions, based on the data of steering wheel angles (SWA) collected from sensors mounted on the steering lever. The proposed system firstly extracts approximate entropy (ApEn) features from fixed sliding windows on real-time steering wheel angles time series. After that, this system linearizes the ApEn features series through an adaptive piecewise linear fitting using a given deviation. Then, the detection system calculates the warping distance between the linear features series of the sample data. Finally, this system uses the warping distance to determine the drowsiness state of the driver according to a designed binary decision classifier. The experimental data were collected from 14.68 h driving under real road conditions, including two fatigue levels: “wake” and “drowsy”. The results show that the proposed system is capable of working online with an average 78.01% accuracy, 29.35% false detections of the “awake” state, and 15.15% false detections of the “drowsy” state. The results also confirm that the proposed method based on SWA signal is valuable for applications in preventing traffic accidents caused by driver fatigue. PMID:28257094

Confronting Drowsy Driving: The American Academy of Sleep Medicine Perspective.

PubMed

Watson, Nathaniel F; Morgenthaler, Timothy; Chervin, Ronald; Carden, Kelly; Kirsch, Douglas; Kristo, David; Malhotra, Raman; Martin, Jennifer; Ramar, Kannan; Rosen, Ilene; Weaver, Terri; Wise, Merrill

2015-11-15

Drowsy driving is a serious public health concern which is often difficult for individual drivers to identify. While it is important for drivers to understand the causes of drowsy driving, there is still insufficient scientific knowledge and public education to prevent drowsy driving. As a result, the AASM is calling upon institutions and policy makers to increase public awareness and improve education on the issue, so our society can better recognize and prevent drowsy driving. The AASM has adopted a position statement to educate both healthcare providers and the general public about drowsy driving risks and countermeasures. © 2015 American Academy of Sleep Medicine.

Investigating Driver Fatigue versus Alertness Using the Granger Causality Network.

PubMed

Kong, Wanzeng; Lin, Weicheng; Babiloni, Fabio; Hu, Sanqing; Borghini, Gianluca

2015-08-05

Driving fatigue has been identified as one of the main factors affecting drivers' safety. The aim of this study was to analyze drivers' different mental states, such as alertness and drowsiness, and find out a neurometric indicator able to detect drivers' fatigue level in terms of brain networks. Twelve young, healthy subjects were recruited to take part in a driver fatigue experiment under different simulated driving conditions. The Electroencephalogram (EEG) signals of the subjects were recorded during the whole experiment and analyzed by using Granger-Causality-based brain effective networks. It was that the topology of the brain networks and the brain's ability to integrate information changed when subjects shifted from the alert to the drowsy stage. In particular, there was a significant difference in terms of strength of Granger causality (GC) in the frequency domain and the properties of the brain effective network i.e., causal flow, global efficiency and characteristic path length between such conditions. Also, some changes were more significant over the frontal brain lobes for the alpha frequency band. These findings might be used to detect drivers' fatigue levels, and as reference work for future studies.

Crashes & Fatalities Related To Driver Drowsiness/Fatigue

DOT National Transportation Integrated Search

1994-11-01

THIS REPORT SUMMARIZES RECENT NATIONAL STATISTICS ON THE INCIDENCE AND CHARACTERISTICS OF CRASHES INVOLVING DRIVER FATIGUE, DROWSINESS, OR "ASLEEP-AT-THE-WHEEL." FOR THE PURPOSES OF THIS REPORT, THESE TERMS ARE : CONSIDERED SYNONYMOUS. PRINCIPAL DATA...

Real-time driver drowsiness feedback improves driver alertness and self-reported driving performance.

PubMed

Aidman, Eugene; Chadunow, Carolyn; Johnson, Kayla; Reece, John

2015-08-01

Driver drowsiness has been implicated as a major causal factor in road accidents. Tools that allow remote monitoring and management of driver fatigue are used in the mining and road transport industries. Increasing drivers' own awareness of their drowsiness levels using such tools may also reduce risk of accidents. The study examined the effects of real-time blink-velocity-derived drowsiness feedback on driver performance and levels of alertness in a military setting. A sample of 15 Army Reserve personnel (1 female) aged 21-59 (M=41.3, SD=11.1) volunteered to being monitored by an infra-red oculography-based Optalert Alertness Monitoring System (OAMS) while they performed their regular driving tasks, including on-duty tasks and commuting to and from duty, for a continuous period of 4-8 weeks. For approximately half that period, blink-velocity-derived Johns Drowsiness Scale (JDS) scores were fed back to the driver in a counterbalanced repeated-measures design, resulting in a total of 419 driving periods under "feedback" and 385 periods under "no-feedback" condition. Overall, the provision of real-time feedback resulted in reduced drowsiness (lower JDS scores) and improved alertness and driving performance ratings. The effect was small and varied across the 24-h circadian cycle but it remained robust after controlling for time of day and driving task duration. Both the number of JDS peaks counted for each trip and their duration declined in the presence of drowsiness feedback, indicating a dynamic pattern that is consistent with a genuine, entropy-reducing feedback mechanism (as distinct from random re-alerting) behind the observed effect. Its mechanisms and practical utility have yet to be fully explored. Direct examination of the alternative, random re-alerting explanation of this feedback effect is an important step for future research. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Distraction and drowsiness in motorcoach drivers : research brief.

DOT National Transportation Integrated Search

2016-11-01

Motorcoach crasheswhen they occurcan involve multiple injuries and deaths, beyond what is typically experienced in light vehicle crashes. Driver error is often cited as a factor in these crashes, with distraction and drowsiness being primary co...

Confronting Drowsy Driving: The American Academy of Sleep Medicine Perspective

PubMed Central

Watson, Nathaniel F.; Morgenthaler, Timothy; Chervin, Ronald; Carden, Kelly; Kirsch, Douglas; Kristo, David; Malhotra, Raman; Martin, Jennifer; Ramar, Kannan; Rosen, Ilene; Weaver, Terri; Wise, Merrill

2015-01-01

Drowsy driving is a serious public health concern which is often difficult for individual drivers to identify. While it is important for drivers to understand the causes of drowsy driving, there is still insufficient scientific knowledge and public education to prevent drowsy driving. As a result, the AASM is calling upon institutions and policy makers to increase public awareness and improve education on the issue, so our society can better recognize and prevent drowsy driving. The AASM has adopted a position statement to educate both healthcare providers and the general public about drowsy driving risks and countermeasures. Citation: Watson NF, Morgenthaler T, Chervin R, Carden K, Kirsch D, Kristo D, Malhotra R, Martin J, Ramar K, Rosen I, Weaver T, Wise M. Confronting drowsy driving: the american academy of sleep medicine perspective. J Clin Sleep Med 2015;11(11):1335–1336. PMID:26414989

Real-time driver fatigue detection based on face alignment

NASA Astrophysics Data System (ADS)

Tao, Huanhuan; Zhang, Guiying; Zhao, Yong; Zhou, Yi

2017-07-01

The performance and robustness of fatigue detection largely decrease if the driver with glasses. To address this issue, this paper proposes a practical driver fatigue detection method based on face alignment at 3000 FPS algorithm. Firstly, the eye regions of the driver are localized by exploiting 6 landmarks surrounding each eye. Secondly, the HOG features of the extracted eye regions are calculated and put into SVM classifier to recognize the eye state. Finally, the value of PERCLOS is calculated to determine whether the driver is drowsy or not. An alarm will be generated if the eye is closed for a specified period of time. The accuracy and real-time on testing videos with different drivers demonstrate that the proposed algorithm is robust and obtain better accuracy for driver fatigue detection compared with some previous method.

Asleep at the Wheel-The Road to Addressing Drowsy Driving

DOT National Transportation Integrated Search

2017-01-25

Drowsy driving is a dangerous behavior that leads to thousands of deaths and injuries each year. It is also a controllable factor for drivers. Drivers are capable of modifying this behavior if given sufficient information and motivation. Our goal is ...

Automatic Detection of Driver Fatigue Using Driving Operation Information for Transportation Safety.

PubMed

Li, Zuojin; Chen, Liukui; Peng, Jun; Wu, Ying

2017-05-25

Fatigued driving is a major cause of road accidents. For this reason, the method in this paper is based on the steering wheel angles (SWA) and yaw angles (YA) information under real driving conditions to detect drivers' fatigue levels. It analyzes the operation features of SWA and YA under different fatigue statuses, then calculates the approximate entropy (ApEn) features of a short sliding window on time series. Using the nonlinear feature construction theory of dynamic time series, with the fatigue features as input, designs a "2-6-6-3" multi-level back propagation (BP) Neural Networks classifier to realize the fatigue detection. An approximately 15-h experiment is carried out on a real road, and the data retrieved are segmented and labeled with three fatigue levels after expert evaluation, namely "awake", "drowsy" and "very drowsy". The average accuracy of 88.02% in fatigue identification was achieved in the experiment, endorsing the value of the proposed method for engineering applications.

Measuring neurophysiological signals in aircraft pilots and car drivers for the assessment of mental workload, fatigue and drowsiness.

PubMed

Borghini, Gianluca; Astolfi, Laura; Vecchiato, Giovanni; Mattia, Donatella; Babiloni, Fabio

2014-07-01

This paper reviews published papers related to neurophysiological measurements (electroencephalography: EEG, electrooculography EOG; heart rate: HR) in pilots/drivers during their driving tasks. The aim is to summarise the main neurophysiological findings related to the measurements of pilot/driver's brain activity during drive performance and how particular aspects of this brain activity could be connected with the important concepts of "mental workload", "mental fatigue" or "situational awareness". Review of the literature suggests that exists a coherent sequence of changes for EEG, EOG and HR variables during the transition from normal drive, high mental workload and eventually mental fatigue and drowsiness. In particular, increased EEG power in theta band and a decrease in alpha band occurred in high mental workload. Successively, increased EEG power in theta as well as delta and alpha bands characterise the transition between mental workload and mental fatigue. Drowsiness is also characterised by increased blink rate and decreased HR values. The detection of such mental states is actually performed "offline" with accuracy around 90% but not online. A discussion on the possible future applications of findings provided by these neurophysiological measurements in order to improve the safety of the vehicles will be also presented. Copyright © 2012 Elsevier Ltd. All rights reserved.

Optical flow and driver's kinematics analysis for state of alert sensing.

PubMed

Jiménez-Pinto, Javier; Torres-Torriti, Miguel

2013-03-28

Road accident statistics from different countries show that a significant number of accidents occur due to driver's fatigue and lack of awareness to traffic conditions. In particular, about 60% of the accidents in which long haul truck and bus drivers are involved are attributed to drowsiness and fatigue. It is thus fundamental to improve non-invasive systems for sensing a driver's state of alert. One of the main challenges to correctly resolve the state of alert is measuring the percentage of eyelid closure over time (PERCLOS), despite the driver's head and body movements. In this paper, we propose a technique that involves optical flow and driver's kinematics analysis to improve the robustness of the driver's alert state measurement under pose changes using a single camera with near-infrared illumination. The proposed approach infers and keeps track of the driver's pose in 3D space in order to ensure that eyes can be located correctly, even after periods of partial occlusion, for example, when the driver stares away from the camera. Our experiments show the effectiveness of the approach with a correct eyes detection rate of 99.41%, on average. The results obtained with the proposed approach in an experiment involving fifteen persons under different levels of sleep deprivation also confirm the discriminability of the fatigue levels. In addition to the measurement of fatigue and drowsiness, the pose tracking capability of the proposed approach has potential applications in distraction assessment and alerting of machine operators.

Optical Flow and Driver's Kinematics Analysis for State of Alert Sensing

PubMed Central

Jiménez-Pinto, Javier; Torres-Torriti, Miguel

2013-01-01

Road accident statistics from different countries show that a significant number of accidents occur due to driver's fatigue and lack of awareness to traffic conditions. In particular, about 60% of the accidents in which long haul truck and bus drivers are involved are attributed to drowsiness and fatigue. It is thus fundamental to improve non-invasive systems for sensing a driver's state of alert. One of the main challenges to correctly resolve the state of alert is measuring the percentage of eyelid closure over time (PERCLOS), despite the driver's head and body movements. In this paper, we propose a technique that involves optical flow and driver's kinematics analysis to improve the robustness of the driver's alert state measurement under pose changes using a single camera with near-infrared illumination. The proposed approach infers and keeps track of the driver's pose in 3D space in order to ensure that eyes can be located correctly, even after periods of partial occlusion, for example, when the driver stares away from the camera. Our experiments show the effectiveness of the approach with a correct eyes detection rate of 99.41%, on average. The results obtained with the proposed approach in an experiment involving fifteen persons under different levels of sleep deprivation also confirm the discriminability of the fatigue levels. In addition to the measurement of fatigue and drowsiness, the pose tracking capability of the proposed approach has potential applications in distraction assessment and alerting of machine operators. PMID:23539029

THE SLEEP OF LONG-HAUL TRUCK DRIVERS

PubMed Central

Mitler, Merrill M.; Miller, James C.; Lipsitz, Jeffrey J.; Walsh, James K.; Wylie, C. Dennis

2008-01-01

Background Fatigue and sleep deprivation are important safety issues for long-haul truck drivers. Methods We conducted round-the-clock electrophysiologic and performance monitoring of four groups of 20 male truck drivers who were carrying revenue-producing loads. We compared four driving schedules, two in the United States (five 10-hour trips of day driving beginning about the same time each day or of night driving beginning about 2 hours earlier each day) and two in Canada (four 13-hour trips of late-night-to-morning driving beginning at about the same time each evening or of afternoon-to-night driving beginning 1 hour later each day). Results Drivers averaged 5.18 hours in bed per day and 4.78 hours of electrophysiologically verified sleep per day over the five-day study (range, 3.83 hours of sleep for those on the steady 13-hour night schedule to 5.38 hours of sleep for those on the steady 10-hour day schedule). These values compared with a mean (±SD) self-reported ideal amount of sleep of 7.1±1 hours a day. For 35 drivers (44 percent), naps augmented the sleep obtained by an average of 0.45±0.31 hour. No crashes or other vehicle mishaps occurred. Two drivers had undiagnosed sleep apnea, as detected by polysomnography. Two other drivers had one episode each of stage 1 sleep while driving, as detected by electroencephalography. Forty-five drivers (56 percent) had at least 1 six-minute interval of drowsiness while driving, as judged by analysis of video recordings of their faces; 1067 of the 1989 six-minute segments (54 percent) showing drowsy drivers involved just eight drivers. Conclusions Long-haul truck drivers in this study obtained less sleep than is required for alertness on the job. The greatest vulnerability to sleep or sleep-like states is in the late night and early morning. PMID:9287232

Design of a Fatigue Detection System for High-Speed Trains Based on Driver Vigilance Using a Wireless Wearable EEG.

PubMed

Zhang, Xiaoliang; Li, Jiali; Liu, Yugang; Zhang, Zutao; Wang, Zhuojun; Luo, Dianyuan; Zhou, Xiang; Zhu, Miankuan; Salman, Waleed; Hu, Guangdi; Wang, Chunbai

2017-03-01

The vigilance of the driver is important for railway safety, despite not being included in the safety management system (SMS) for high-speed train safety. In this paper, a novel fatigue detection system for high-speed train safety based on monitoring train driver vigilance using a wireless wearable electroencephalograph (EEG) is presented. This system is designed to detect whether the driver is drowsiness. The proposed system consists of three main parts: (1) a wireless wearable EEG collection; (2) train driver vigilance detection; and (3) early warning device for train driver. In the first part, an 8-channel wireless wearable brain-computer interface (BCI) device acquires the locomotive driver's brain EEG signal comfortably under high-speed train-driving conditions. The recorded data are transmitted to a personal computer (PC) via Bluetooth. In the second step, a support vector machine (SVM) classification algorithm is implemented to determine the vigilance level using the Fast Fourier transform (FFT) to extract the EEG power spectrum density (PSD). In addition, an early warning device begins to work if fatigue is detected. The simulation and test results demonstrate the feasibility of the proposed fatigue detection system for high-speed train safety.

Fatigued and drowsy driving: a survey of attitudes, opinions and behaviors.

PubMed

Vanlaar, Ward; Simpson, Herb; Mayhew, Dan; Robertson, Robyn

2008-01-01

There is evidence suggesting that the problem of fatigued or drowsy driving is an important contributor to road crashes. However, not much is known about public perceptions of the issue. The purpose of this study was to obtain information on attitudes, opinions, and professed practices related to fatigued or drowsy driving. The data were gathered by means of a public opinion poll among a representative sample of 750 Ontario drivers. A majority of drivers (58.6%) admitted that they occasionally drive while fatigued or drowsy. Of greater importance, 14.5% of respondents admitted that they had fallen asleep or "nodded off" while driving during the past year. Nearly 2% were involved in a fatigue or drowsy driving related crash in the past year. Respondents were also asked about measures they take to overcome fatigue or drowsiness. Results indicate that relatively ineffective measures such as opening the window or playing music are the most popular; the most effective preventive measure--taking a rest--is the least popular. The prevalence of the behavior, coupled with the ineffective prevention measures favored by the public suggest there is a need for increasing their level of awareness and knowledge about the problem. Results from this study further emphasize the importance of increasing the fatigued and drowsy driving knowledge base and the need to educate the public about it.

Asleep at the Wheel-The Road to Addressing Drowsy Driving.

PubMed

Higgins, J Stephen; Michael, Jeff; Austin, Rory; Åkerstedt, Torbjörn; Van Dongen, Hans P A; Watson, Nathaniel; Czeisler, Charles; Pack, Allan I; Rosekind, Mark R

2017-02-01

Drowsy driving is a dangerous behavior that leads to thousands of deaths and injuries each year. It is also a controllable factor for drivers. Drivers are capable of modifying this behavior if given sufficient information and motivation. Our goal is to establish a comprehensive and strategic effort to end drowsy driving crashes and deaths. This article highlights some of the conclusions of a unique recent meeting of sleep experts and highway safety professionals and describes the first steps the community has taken and plans to take in the future to address this issue. Published by Oxford University Press on behalf of Sleep Research Society (SRS) 2017. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Motivational factors associated with drowsy driving behavior: a qualitative investigation of college students.

PubMed

Beck, Kenneth H; Lee, Clark J; Weiner, Talia

2018-02-01

This qualitative investigation sought to identify the motivational factors that contribute to drowsy driving in college students and to discover important messaging strategies that may help prevent or reduce this behavior in this population. Four focus groups of college students. A large university in the Washington, DC, metropolitan area during the Fall 2016 term. Twenty-six undergraduate students between the ages of 18 and 25 years. Notes and transcripts from the focus group sessions were analyzed to identify recurring themes regarding attitudes, motivations, experiences, influences, and potential preventive messaging strategies related to drowsy driving. Although most participants had heard of drowsy driving and were concerned about it, they did not associate it with legal risks and were more concerned about alcohol-impaired and distracted driving as crash risks. Participants viewed drowsy driving as a normal and unavoidable part of their lives over which they had little control. For potential anti-drowsy driving messaging strategies, participants preferred messages delivered via audiovisual or social media that featured graphic and emotional portrayals of crashes and their consequences. Participants also voiced strong support for preventive messaging strategies equating various degrees of sleep deprivation to known impairing levels of alcohol, as well as messages providing cues to action to actual drowsy drivers on roadways. Increased enforcement, education, and public messaging campaigns are needed to increase knowledge and influence attitudes and opinions among young drivers about the dangers and social unacceptability of drowsy driving. Copyright © 2018 National Sleep Foundation. Published by Elsevier Inc. All rights reserved.

National survey of distracted and drowsy driving attitudes and behavior : 2002. Volume 3, Methods

DOT National Transportation Integrated Search

2003-03-01

This report represents the findings on distracted driving (including cell phone use) and drowsy driving. The data come from a pair of studies undertaken by National Highway Traffic Safety Administration (NHTSA) to better understand drivers behavio...

National survey of distracted and drowsy driving attitudes and behaviors : 2002. Volume 1, Findings

DOT National Transportation Integrated Search

2003-04-01

This report represents the findings on distracted driving (including cell phone use) and drowsy driving. The data come from a pair of studies undertaken by the National Highway Traffic Safety Administration (NHTSA) to better understand drivers' behav...

Investigating Driver Fatigue versus Alertness Using the Granger Causality Network

PubMed Central

Kong, Wanzeng; Lin, Weicheng; Babiloni, Fabio; Hu, Sanqing; Borghini, Gianluca

2015-01-01

Driving fatigue has been identified as one of the main factors affecting drivers’ safety. The aim of this study was to analyze drivers’ different mental states, such as alertness and drowsiness, and find out a neurometric indicator able to detect drivers’ fatigue level in terms of brain networks. Twelve young, healthy subjects were recruited to take part in a driver fatigue experiment under different simulated driving conditions. The Electroencephalogram (EEG) signals of the subjects were recorded during the whole experiment and analyzed by using Granger-Causality-based brain effective networks. It was that the topology of the brain networks and the brain’s ability to integrate information changed when subjects shifted from the alert to the drowsy stage. In particular, there was a significant difference in terms of strength of Granger causality (GC) in the frequency domain and the properties of the brain effective network i.e., causal flow, global efficiency and characteristic path length between such conditions. Also, some changes were more significant over the frontal brain lobes for the alpha frequency band. These findings might be used to detect drivers’ fatigue levels, and as reference work for future studies. PMID:26251909

Design of a Fatigue Detection System for High-Speed Trains Based on Driver Vigilance Using a Wireless Wearable EEG

PubMed Central

Zhang, Xiaoliang; Li, Jiali; Liu, Yugang; Zhang, Zutao; Wang, Zhuojun; Luo, Dianyuan; Zhou, Xiang; Zhu, Miankuan; Salman, Waleed; Hu, Guangdi; Wang, Chunbai

2017-01-01

The vigilance of the driver is important for railway safety, despite not being included in the safety management system (SMS) for high-speed train safety. In this paper, a novel fatigue detection system for high-speed train safety based on monitoring train driver vigilance using a wireless wearable electroencephalograph (EEG) is presented. This system is designed to detect whether the driver is drowsiness. The proposed system consists of three main parts: (1) a wireless wearable EEG collection; (2) train driver vigilance detection; and (3) early warning device for train driver. In the first part, an 8-channel wireless wearable brain-computer interface (BCI) device acquires the locomotive driver’s brain EEG signal comfortably under high-speed train-driving conditions. The recorded data are transmitted to a personal computer (PC) via Bluetooth. In the second step, a support vector machine (SVM) classification algorithm is implemented to determine the vigilance level using the Fast Fourier transform (FFT) to extract the EEG power spectrum density (PSD). In addition, an early warning device begins to work if fatigue is detected. The simulation and test results demonstrate the feasibility of the proposed fatigue detection system for high-speed train safety. PMID:28257073

A Fuzzy Model to Interpret Data of Drive Performances from Patients with Sleep Deprivation

PubMed Central

Sena, Pasquale; Attianese, Paolo; Carbone, Francesca; Pellegrino, Arcangelo; Pinto, Aldo; Villecco, Francesco

2012-01-01

The search for safe vehicles is increasing with both diffusion of high traffic density over the world and availability of new technologies providing sophisticated tools previously impossible to realize. Design and development of the necessary devices may be based on simulation tests that reduce cost allowing trials in many directions. A proper choice of the arrangement of the drive simulators, as much as of the parameters to be monitored, is of basic importance as they can address the design of devices somehow responsible for the drivers safety or, even their lives. This system setup, consisting of a free car simulator equipped with a monitoring system, collects in a nonintrusive way data of the car lateral position within the road lane and of its first derivative. Based on these measured parameters, the system is able to detect symptoms of drowsiness and sleepiness. The analysis is realized by a fuzzy inferential process that provides an immediate warning signal as soon as drowsiness is detected with a high level of certainty. Enhancement of reliability and minimisation of the false alarm rate are obtained by operating continuous comparison between learned driver typical modalities of operation on the control command of the vehicle the pattern recorded. PMID:22969834

Real-time monitoring of the human alertness level

NASA Astrophysics Data System (ADS)

Alvarez, Robin; del Pozo, Francisco; Hernando, Elena; Gomez, Eduardo; Jimenez, Antonio

2003-04-01

Many accidents are associated with a driver or machine operator's alertness level. Drowsiness often develops as a result of repetitive or monotonous tasks, uninterrupted by external stimuli. In order to enhance safety levels, it would be most desirable to monitor the individual's level of attention. In this work, changes in the power spectrum of the electroencephalographic signal (EEG) are associated with the subject's level of attention. This study reports on the initial research carried out in order to answer the following important questions: (i) Does a trend exist in the shape of the power spectrum, which will indicate the state of a subject's alertness state (drowsy, relaxed or alert)? (ii) What points on the cortex are most suitable to detect drowsiness and/or high alertness? (iii) What parameters in the power spectrum are most suitable to establish a workable alertness classification in human subjects? In this work, we answer these questions and combine power spectrum estimation and artificial neural network techniques to create a non-invasive and real - time system able to classify EEG into three levels of attention: High, Relaxed and Drowsiness. The classification is made every 10 seconds o more, a suitable time span for giving an alarm signal if the individual is with insufficient level of alertness. This time span is set by the user. The system was tested on twenty subjects. High and relaxed attention levels were measured in randomise hours of the day and drowsiness attention level was measured in the morning after one night of sleep deprivation.

Prediction of fatigue-related driver performance from EEG data by deep Riemannian model.

PubMed

Hajinoroozi, Mehdi; Jianqiu Zhang; Yufei Huang

2017-07-01

Prediction of the drivers' drowsy and alert states is important for safety purposes. The prediction of drivers' drowsy and alert states from electroencephalography (EEG) using shallow and deep Riemannian methods is presented. For shallow Riemannian methods, the minimum distance to Riemannian mean (mdm) and Log-Euclidian metric are investigated, where it is shown that Log-Euclidian metric outperforms the mdm algorithm. In addition the SPDNet, a deep Riemannian model, that takes the EEG covariance matrix as the input is investigated. It is shown that SPDNet outperforms all tested shallow and deep classification methods. Performance of SPDNet is 6.02% and 2.86% higher than the best performance by the conventional Euclidian classifiers and shallow Riemannian models, respectively.

The Accuracy of Eyelid Movement Parameters for Drowsiness Detection

PubMed Central

Wilkinson, Vanessa E.; Jackson, Melinda L.; Westlake, Justine; Stevens, Bronwyn; Barnes, Maree; Swann, Philip; Rajaratnam, Shantha M. W.; Howard, Mark E.

2013-01-01

Study Objectives: Drowsiness is a major risk factor for motor vehicle and occupational accidents. Real-time objective indicators of drowsiness could potentially identify drowsy individuals with the goal of intervening before an accident occurs. Several ocular measures are promising objective indicators of drowsiness; however, there is a lack of studies evaluating their accuracy for detecting behavioral impairment due to drowsiness in real time. Methods: In this study, eye movement parameters were measured during vigilance tasks following restricted sleep and in a rested state (n = 33 participants) at three testing points (n = 71 data points) to compare ocular measures to a gold standard measure of drowsiness (OSLER). The utility of these parameters for detecting drowsiness-related errors was evaluated using receiver operating characteristic curves (ROC) (adjusted by clustering for participant) and identification of optimal cutoff levels for identifying frequent drowsiness-related errors (4 missed signals in a minute using OSLER). Their accuracy was tested for detecting increasing frequencies of behavioral lapses on a different task (psychomotor vigilance task [PVT]). Results: Ocular variables which measured the average duration of eyelid closure (inter-event duration [IED]) and the ratio of the amplitude to velocity of eyelid closure were reliable indicators of frequent errors (area under the curve for ROC of 0.73 to 0.83, p < 0.05). IED produced a sensitivity and specificity of 71% and 88% for detecting ≥ 3 lapses (PVT) in a minute and 100% and 86% for ≥ 5 lapses. A composite measure of several eye movement characteristics (Johns Drowsiness Scale) provided sensitivities of 77% and 100% for detecting 3 and ≥ 5 lapses in a minute, with specificities of 85% and 83%, respectively. Conclusions: Ocular measures, particularly those measuring the average duration of episodes of eye closure are promising real-time indicators of drowsiness. Citation: Wilkinson VE; Jackson ML; Westlake J; Stevens B; Barnes M; Swann P; Rajaratnam SMW; Howard ME. The accuracy of eyelid movement parameters for drowsiness detection. J Clin Sleep Med 2013;9(12):1315-1324. PMID:24340294

The accuracy of eyelid movement parameters for drowsiness detection.

PubMed

Wilkinson, Vanessa E; Jackson, Melinda L; Westlake, Justine; Stevens, Bronwyn; Barnes, Maree; Swann, Philip; Rajaratnam, Shantha M W; Howard, Mark E

2013-12-15

Drowsiness is a major risk factor for motor vehicle and occupational accidents. Real-time objective indicators of drowsiness could potentially identify drowsy individuals with the goal of intervening before an accident occurs. Several ocular measures are promising objective indicators of drowsiness; however, there is a lack of studies evaluating their accuracy for detecting behavioral impairment due to drowsiness in real time. In this study, eye movement parameters were measured during vigilance tasks following restricted sleep and in a rested state (n = 33 participants) at three testing points (n = 71 data points) to compare ocular measures to a gold standard measure of drowsiness (OSLER). The utility of these parameters for detecting drowsiness-related errors was evaluated using receiver operating characteristic curves (ROC) (adjusted by clustering for participant) and identification of optimal cutoff levels for identifying frequent drowsiness-related errors (4 missed signals in a minute using OSLER). Their accuracy was tested for detecting increasing frequencies of behavioral lapses on a different task (psychomotor vigilance task [PVT]). Ocular variables which measured the average duration of eyelid closure (inter-event duration [IED]) and the ratio of the amplitude to velocity of eyelid closure were reliable indicators of frequent errors (area under the curve for ROC of 0.73 to 0.83, p < 0.05). IED produced a sensitivity and specificity of 71% and 88% for detecting ≥ 3 lapses (PVT) in a minute and 100% and 86% for ≥ 5 lapses. A composite measure of several eye movement characteristics (Johns Drowsiness Scale) provided sensitivities of 77% and 100% for detecting 3 and ≥ 5 lapses in a minute, with specificities of 85% and 83%, respectively. Ocular measures, particularly those measuring the average duration of episodes of eye closure are promising real-time indicators of drowsiness.

An innovative nonintrusive driver assistance system for vital signal monitoring.

PubMed

Sun, Ye; Yu, Xiong Bill

2014-11-01

This paper describes an in-vehicle nonintrusive biopotential measurement system for driver health monitoring and fatigue detection. Previous research has found that the physiological signals including eye features, electrocardiography (ECG), electroencephalography (EEG) and their secondary parameters such as heart rate and HR variability are good indicators of health state as well as driver fatigue. A conventional biopotential measurement system requires the electrodes to be in contact with human body. This not only interferes with the driver operation, but also is not feasible for long-term monitoring purpose. The driver assistance system in this paper can remotely detect the biopotential signals with no physical contact with human skin. With delicate sensor and electronic design, ECG, EEG, and eye blinking can be measured. Experiments were conducted on a high fidelity driving simulator to validate the system performance. The system was found to be able to detect the ECG/EEG signals through cloth or hair with no contact with skin. Eye blinking activities can also be detected at a distance of 10 cm. Digital signal processing algorithms were developed to decimate the signal noise and extract the physiological features. The extracted features from the vital signals were further analyzed to assess the potential criterion for alertness and drowsiness determination.

Truck driver fatigue assessment using a virtual reality system.

DOT National Transportation Integrated Search

2016-10-17

In this study, a fully immersive Virtual Reality (VR) based driving simulator was developed to serve : as a proof-of-concept that VR can be utilized to assess the level of fatigue (or drowsiness) truck : drivers typically experience during real...

The Role Of Driver Inattention In Crashes; New Statistics From The 1995 Crashworthiness Data System

DOT National Transportation Integrated Search

1996-08-08

INTELLIGENT VEHICLE INITIATIVE OR IVI : IN 1995, NHTSA BEGAN EMPLOYING THE CRASHWORTHINESS DATA SYSTEM (CDS) TO OBTAIN MORE IN-DEPTH INFORMATION ON DRIVER INATTENTION-RELATED CRASH CAUSES, INCLUDING DROWSINESS AND MANY FORMS OF DISTRACTION. CDS IS PO...

On the efficiency of driver state monitoring systems

NASA Astrophysics Data System (ADS)

Dementienko, V. V.; Dorokhov, V. B.; Gerus, S. V.; Markov, A. G.; Shakhnarovich, V. M.

2007-06-01

Statistical data on road traffic and the results of laboratory studies are used to construct a mathematical model of a driver-driver state monitor-automobile-traffic system. In terms of the model, the probability of an accident resulting from the drowsy state of the driver is determined both in the absence and presence of a monitor. The model takes into account the efficiency and safety level provided by different monitoring systems, as well as psychological factors associated with the excessive reliance of drivers upon monitoring.

Short and long sleep duration and risk of drowsy driving and the role of subjective sleep insufficiency.

PubMed

Maia, Querino; Grandner, Michael A; Findley, James; Gurubhagavatula, Indira

2013-10-01

Experimental sleep restriction increases sleepiness and impairs driving performance. However, it is unclear whether short sleep duration in the general population is associated with drowsy driving. The goal of the present study was to evaluate whether individuals in the general population who obtained sleep of 6h or less are more likely to report drowsy driving, and evaluate the role of perceived sleep sufficiency. Data exploring whether subgroups of short sleepers (those who report the most or least unmet sleep need) show different risk profiles for drowsy driving are limited. From the 2009 Behavioral Risk Factor Surveillance System (N=31,522), we obtained the following self-reported data: (1) sleep duration (≤5, 6, 7, 8, 9, or ≥10 h/night); (2) number of days/week of perceived insufficient sleep; (3) among drivers, yes/no response to: "During the past 30 days, have you ever nodded off or fallen asleep, even just for a brief moment, while driving?" (4) demographics, physical/mental health. Using 7 h/night as reference, logistic regression analyses evaluated whether self-reported sleep duration was associated with drowsy driving. Overall, 3.6% reported drowsy driving. Self-identified short-sleepers reported drowsy driving more often, and long sleepers, less often. Among those who perceived sleep as always insufficient, drowsy driving was reported more often when sleep duration was ≤5 h, 6 h, or ≥10 h. Among those who perceived sleep as always sufficient, drowsy driving was reported more often among ≤5 h and 6h sleepers. Overall, drowsy driving was common, particularly in self-identified short-sleepers as a whole, as well as subgroups based on sleep insufficiency. Copyright © 2013 Elsevier Ltd. All rights reserved.

[Objective evaluation of driving fatigue by using variability of pupil diameter under spontaneous pupillary fluctuation conditions].

PubMed

Xiong, Xingliang; Zhang, Yan; Chen, Mengmeng; Chen, Longcong

2013-04-01

Objective evaluation of driver drowsiness is necessary toward suppression of fatigued driving and prevention of traffic accident. We have developed a new method in which we utilized pupillary diameter variability (PDV) under spontaneous pupillary fluctuation conditions. The method consists of three main steps. Firstly, we use a 90s long infrared video of pupillogram infrared-sensitive CCD camera. Secondly, we employed edge detection algorithm based on curvature characteristics of pupil boundary to extract a set of points of visible pupil boundary, and then we adopted these points to fit a circle to obtain the diameter of the pupil in current frame of video. Finally, the values of PDV in 90s long video is calculated. In an experimental pilot study, the values of PDV of two groups were measured. One group rated themselves as alert (12 men), the other group as sleepy (13 men). The results showed that significant differences could be found between the two groups, and the values were 0.06 +/- 0.005 and 0.141 +/- 0.042, respectively. Taking into account of the knowledge that spontaneous pupillary fluctuation is innervated by autonomic nervous system which activity is known to change in parallel with drowsiness and cannot be influenced by subjective motive of people. From the results of the experiments, we concluded that PDV could be used to evaluate driver fatigue objectively.

Sleep-deprived motor vehicle operators are unfit to drive: a multidisciplinary expert consensus statement on drowsy driving.

PubMed

Czeisler, Charles A; Wickwire, Emerson M; Barger, Laura K; Dement, William C; Gamble, Karen; Hartenbaum, Natalie; Ohayon, Maurice M; Pelayo, Rafael; Phillips, Barbara; Strohl, Kingman; Tefft, Brian; Rajaratnam, Shantha M W; Malhotra, Raman; Whiton, Kaitlyn; Hirshkowitz, Max

2016-06-01

This article presents the consensus findings of the National Sleep Foundation Drowsy Driving Consensus Working Group, which was an expert panel assembled to establish a consensus statement regarding sleep-related driving impairment. The National Sleep Foundation assembled a expert panel comprised of experts from the sleep community and experts appointed by stakeholder organizations. A systematic literature review identified 346 studies that were abstracted and provided to the panelists for review. A modified Delphi RAND/UCLA Appropriateness Method with 2 rounds of voting was used to reach consensus. A final consensus was reached that sleep deprivation renders motorists unfit to drive a motor vehicle. After reviewing growing evidence of impairment and increased crash risk among drivers who obtained less than optimal sleep duration in the preceding 24 hours, the panelists recognized the need for public policy guidance as to when it is certainly unsafe to drive. Toward this end, the panelists agreed upon the following expert consensus statement: "Drivers who have slept for two hours or less in the preceding 24 hours are not fit to operate a motor vehicle." Panelists further agreed that most healthy drivers would likely be impaired with only 3 to 5 hours of sleep during the prior 24 hours. There is consensus among experts that healthy individuals who have slept for 2 hours or less in the preceding 24 hours are too impaired to safely operate a motor vehicle. Prevention of drowsy driving will require sustained and collaborative effort from multiple stakeholders. Implications and limitations of the consensus recommendations are discussed. Copyright © 2016. Published by Elsevier Inc.

Distraction and drowsiness in motorcoach drivers.

DOT National Transportation Integrated Search

2016-11-01

Despite the large number of motorcoaches in the United States, there has been limited research on motorcoach operations. With more than 15 billion miles traveled per year and the transport of millions of people, crashes, when they occur, can involve ...

Study of high-tension cable barriers on Michigan roadways.

DOT National Transportation Integrated Search

2014-10-01

Median-crossover crashes present the highest risk of fatality and severe injury among all collision types on : freeways. These crashes are caused by : a variety of factors, including drowsiness, driver distraction, impaired : driving, and loss of con...

Sleep-related car crashes: risk perception and decision-making processes in young drivers.

PubMed

Lucidi, Fabio; Russo, Paolo Maria; Mallia, Luca; Devoto, Alessandra; Lauriola, Marco; Violani, Cristiano

2006-03-01

The aim of the present study is to analyse factors affecting worries, coping strategies and decisions of young drivers regarding the risk of sleep-related car crashes. Furthermore, the study also analyses whether framing the same information about sleepiness in two different linguistic forms influences: (1) the evaluation of the level of risk associated to a specific level of drowsiness (Attribute Framing problem); (2) the willingness to enact strategies to "prevent" sleepiness before night-time driving (Goal Framing problem); (3) the choice between two different ways, both of equal expected efficacy, of lowering drowsiness (Risky decision-making Framing problem). Six hundred and ninety-five young drivers [(57.6% females, 42.4% males); mean age 20.85 years (S.D.=1.2)] answered questions on drive risk perception and sleepiness, on nocturnal driving experience and on the strategies to deal with driver sleepiness, responding to one of the two different versions of the framed problems. A sub-sample of 130 participants completed the framed problems in both versions. The results show that experiences of sleep attacks and nocturnal driving frequency in the past 6 months affect both risk perception and the preventive strategies adopted. Furthermore, the manipulation on two out of the three problems (attribute and risky decision-making frames) significantly affected the respondents' evaluation.

Light Vehicle-Heavy Vehicle Interaction Data Collection and Countermeasure Research Project.

DOT National Transportation Integrated Search

2016-11-01

The Light Vehicle-Heavy Vehicle Interaction (LV-HV) Data Collection and Countermeasure Research Project : leveraged data from the Drowsy Driver Warning System Field Operational Test (DDWS FOT) to investigate a : set of research issues relating to dri...

[Sleep deprivation and its effect on the ability to maintain wakefulness: implications on functioning and driving].

PubMed

Furman, Gabriela Dorfman; Cahan, Clement; Baharav, Armada

2009-05-01

During the last century, western society suffers from an increasing steep debt. A large number of accidents occur due to drowsy drivers. People are not aware of the influence of fatigue/drowsiness on their functioning and driving capacity. Our goal is to identify and characterize measurable physioLogicaL information capable of monitoring simple and reliable performance of driver vigilance. Eight healthy volunteers without sleep disorders were included in the study. They participated in two missions, on and off every two hours during 34-36 hours, in order to create an accumulative sleep debt. The tasks included the Maintenance of wakefulness test (MWT) and the driving simulator test. White tested, they remained connected to EEG, EMG, EOG, ECG and audio-video registration. These first results are related to 60 MWT tests. The first falling asleep events (FA) appeared around the early afternoon hours, in agreement to the physiological tendency to fall asleep, according to the biological clock. The night was characterized by FAs with a very short sleep Latency time at around 4 AM. On the second day of the experiment, the averaged sleep latency was larger than in the night before, despite the accumulation of sleep debt. The fluctuations of RRI increased after the first micro sleep. The autonomic nervous regulation displays an increase in the overall sympathetic activity as an indicator of increased stress. There is a correlation between parameters associated with instantaneous autonomic changes of heart rhythm (RRI) and the FA/almost-FA events observed on EEG. These attributes may provide a useful tool for monitoring drowsy drivers and preventing accidents.

Circadian timing, drowsy driving, and health risk behavior in adolescent drivers.

DOT National Transportation Integrated Search

2016-06-01

Both worldwide and in the UnitedStates, major contributors to adolescent and early adult mortality and morbidity arise from health risks characterized as behavioral misadventure. The large majority of deaths among 10-to 24-year-olds are due to risk-r...

Integration of Body Sensor Networks and Vehicular Ad-hoc Networks for Traffic Safety.

PubMed

Reyes-Muñoz, Angelica; Domingo, Mari Carmen; López-Trinidad, Marco Antonio; Delgado, José Luis

2016-01-15

The emergence of Body Sensor Networks (BSNs) constitutes a new and fast growing trend for the development of daily routine applications. However, in the case of heterogeneous BSNs integration with Vehicular ad hoc Networks (VANETs) a large number of difficulties remain, that must be solved, especially when talking about the detection of human state factors that impair the driving of motor vehicles. The main contributions of this investigation are principally three: (1) an exhaustive review of the current mechanisms to detect four basic physiological behavior states (drowsy, drunk, driving under emotional state disorders and distracted driving) that may cause traffic accidents is presented; (2) A middleware architecture is proposed. This architecture can communicate with the car dashboard, emergency services, vehicles belonging to the VANET and road or street facilities. This architecture seeks on the one hand to improve the car driving experience of the driver and on the other hand to extend security mechanisms for the surrounding individuals; and (3) as a proof of concept, an Android real-time attention low level detection application that runs in a next-generation smartphone is developed. The application features mechanisms that allow one to measure the degree of attention of a driver on the base of her/his EEG signals, establish wireless communication links via various standard wireless means, GPRS, Bluetooth and WiFi and issue alarms of critical low driver attention levels.

Integration of Body Sensor Networks and Vehicular Ad-hoc Networks for Traffic Safety

PubMed Central

Reyes-Muñoz, Angelica; Domingo, Mari Carmen; López-Trinidad, Marco Antonio; Delgado, José Luis

2016-01-01

The emergence of Body Sensor Networks (BSNs) constitutes a new and fast growing trend for the development of daily routine applications. However, in the case of heterogeneous BSNs integration with Vehicular ad hoc Networks (VANETs) a large number of difficulties remain, that must be solved, especially when talking about the detection of human state factors that impair the driving of motor vehicles. The main contributions of this investigation are principally three: (1) an exhaustive review of the current mechanisms to detect four basic physiological behavior states (drowsy, drunk, driving under emotional state disorders and distracted driving) that may cause traffic accidents is presented; (2) A middleware architecture is proposed. This architecture can communicate with the car dashboard, emergency services, vehicles belonging to the VANET and road or street facilities. This architecture seeks on the one hand to improve the car driving experience of the driver and on the other hand to extend security mechanisms for the surrounding individuals; and (3) as a proof of concept, an Android real-time attention low level detection application that runs in a next-generation smartphone is developed. The application features mechanisms that allow one to measure the degree of attention of a driver on the base of her/his EEG signals, establish wireless communication links via various standard wireless means, GPRS, Bluetooth and WiFi and issue alarms of critical low driver attention levels. PMID:26784204

Drowsiness/alertness algorithm development and validation using synchronized EEG and cognitive performance to individualize a generalized model

PubMed Central

Johnson, Robin R.; Popovic, Djordje P.; Olmstead, Richard E.; Stikic, Maja; Levendowski, Daniel J.; Berka, Chris

2011-01-01

A great deal of research over the last century has focused on drowsiness/alertness detection, as fatigue-related physical and cognitive impairments pose a serious risk to public health and safety. Available drowsiness/alertness detection solutions are unsatisfactory for a number of reasons: 1) lack of generalizability, 2) failure to address individual variability in generalized models, and/or 3) they lack a portable, un-tethered application. The current study aimed to address these issues, and determine if an individualized electroencephalography (EEG) based algorithm could be defined to track performance decrements associated with sleep loss, as this is the first step in developing a field deployable drowsiness/alertness detection system. The results indicated that an EEG-based algorithm, individualized using a series of brief "identification" tasks, was able to effectively track performance decrements associated with sleep deprivation. Future development will address the need for the algorithm to predict performance decrements due to sleep loss, and provide field applicability. PMID:21419826

Drowsiness/alertness algorithm development and validation using synchronized EEG and cognitive performance to individualize a generalized model.

PubMed

Johnson, Robin R; Popovic, Djordje P; Olmstead, Richard E; Stikic, Maja; Levendowski, Daniel J; Berka, Chris

2011-05-01

A great deal of research over the last century has focused on drowsiness/alertness detection, as fatigue-related physical and cognitive impairments pose a serious risk to public health and safety. Available drowsiness/alertness detection solutions are unsatisfactory for a number of reasons: (1) lack of generalizability, (2) failure to address individual variability in generalized models, and/or (3) lack of a portable, un-tethered application. The current study aimed to address these issues, and determine if an individualized electroencephalography (EEG) based algorithm could be defined to track performance decrements associated with sleep loss, as this is the first step in developing a field deployable drowsiness/alertness detection system. The results indicated that an EEG-based algorithm, individualized using a series of brief "identification" tasks, was able to effectively track performance decrements associated with sleep deprivation. Future development will address the need for the algorithm to predict performance decrements due to sleep loss, and provide field applicability. Copyright © 2011 Elsevier B.V. All rights reserved.

In-vehicle evaluation of milled rumble strips at pre- and post-chip sealed maintenance periods : final report.

DOT National Transportation Integrated Search

2017-01-01

Driver fatigue and drowsiness can have a profound impact on safety. Centerline and shoulder rumble strips (RS) are popular countermeasures designed to produce audible and tactile warning when vehicles deviate from the travel lane onto the RS. This re...

The influence of daily sleep patterns of commercial truck drivers on driving performance

PubMed Central

Chen, Guang Xiang; Fang, Youjia; Guo, Feng; Hanowski, Richard J.

2016-01-01

Fatigued and drowsy driving has been found to be a major cause of truck crashes. Lack of sleep is the number one cause of fatigue and drowsiness. However, there are limited data on the sleep patterns (sleep duration, sleep percentage in the duration of non-work period, and the time when sleep occurred) of truck drivers in non-work periods and the impact on driving performance. This paper examined sleep patterns of 96 commercial truck drivers during non-work periods and evaluated the influence these sleep patterns had on truck driving performance. Data were from the Naturalistic Truck Driving Study. Each driver participated in the study for approximately four weeks. A shift was defined as a non-work period followed by a work period. A total of 1397 shifts were identified. Four distinct sleep patterns were identified based on sleep duration, sleep start/end point in a non-work period, and the percentage of sleep with reference to the duration of non-work period. Driving performance was measured by safety-critical events, which included crashes, near-crashes, crash-relevant conflicts, and unintentional lane deviations. Negative binomial regression was used to evaluate the association between the sleep patterns and driving performance, adjusted for driver demographic information. The results showed that the sleep pattern with the highest safety-critical event rate was associated with shorter sleep, sleep in the early stage of a non-work period, and less sleep between 1 a.m. and 5 a.m. This study also found that male drivers, with fewer years of commercial vehicle driving experience and higher body mass index, were associated with deteriorated driving performance and increased driving risk. The results of this study could inform hours-of-service policy-making and benefit safety management in the trucking industry. PMID:26954762

Insufficient sleep rather than the apnea-hypopnea index can be associated with sleepiness-related driving problems of Japanese obstructive sleep apnea syndrome patients residing in metropolitan areas.

PubMed

Matsui, Kentaro; Sasai-Sakuma, Taeko; Ishigooka, Jun; Inoue, Yuichi

2017-05-01

Obstructive sleep apnea syndrome (OSAS) and insufficient sleep might increase the risk of drowsy driving and sleepiness-related vehicular accidents. This study retrospectively investigated the factors associated with these driving problems, particularly addressing OSAS severity and sleep amounts of affected drivers. This study examined 161 patients (146 male and 15 female) with OSAS (apnea-hypopnea index [AHI] ≥ 5) who drove on a routine basis and who completed study questionnaires. To investigate factors associated with drowsy driving during the prior year and sleepiness-related vehicular accidents or near-miss events during the prior five years, logistic regression analyses were performed with age, body mass index, monthly driving distance, habitual sleep duration on weekdays, the Japanese version of Epworth Sleepiness Scale score, AHI, and periodic limb movement index as independent variables. Of the patients, 68 (42.2%) reported drowsy driving experiences, and 86 (53.4%) reported sleepiness-related vehicular accidents or near-miss events. Analyses revealed the following: older age (46-65 years, ≥66 years) was negatively associated with drowsy driving (p <0.05, p <0.05), and habitually shorter sleep duration on weekdays (≤6 hours) was positively associated with drowsy driving (p <0.01). Habitual sleep duration of ≤6 hours (p <0.01) and Epworth Sleepiness Scale score of ≥11 (p <0.01) were positively associated with sleepiness-related vehicular accidents and near-miss events. However, AHI was not associated with these driving problems. Insufficient sleep, rather than severity of OSAS, was associated with sleepiness-related driving problems in these Japanese OSAS patients. Copyright © 2016 Elsevier B.V. All rights reserved.

High risk of near-crash driving events following night-shift work

PubMed Central

Lee, Michael L.; Howard, Mark E.; Horrey, William J.; Liang, Yulan; Anderson, Clare; Shreeve, Michael S.; O’Brien, Conor S.; Czeisler, Charles A.

2016-01-01

Night-shift workers are at high risk of drowsiness-related motor vehicle crashes as a result of circadian disruption and sleep restriction. However, the impact of actual night-shift work on measures of drowsiness and driving performance while operating a real motor vehicle remains unknown. Sixteen night-shift workers completed two 2-h daytime driving sessions on a closed driving track at the Liberty Mutual Research Institute for Safety: (i) a postsleep baseline driving session after an average of 7.6 ± 2.4 h sleep the previous night with no night-shift work, and (ii) a postnight-shift driving session following night-shift work. Physiological measures of drowsiness were collected, including infrared reflectance oculography, electroencephalography, and electrooculography. Driving performance measures included lane excursions, near-crash events, and drives terminated because of failure to maintain control of the vehicle. Eleven near-crashes occurred in 6 of 16 postnight-shift drives (37.5%), and 7 of 16 postnight-shift drives (43.8%) were terminated early for safety reasons, compared with zero near-crashes or early drive terminations during 16 postsleep drives (Fishers exact: P = 0.0088 and P = 0.0034, respectively). Participants had a significantly higher rate of lane excursions, average Johns Drowsiness Scale, blink duration, and number of slow eye movements during postnight-shift drives compared with postsleep drives (3.09/min vs. 1.49/min; 1.71 vs. 0.97; 125 ms vs. 100 ms; 35.8 vs. 19.1; respectively, P < 0.05 for all). Night-shift work increases driver drowsiness, degrading driving performance and increasing the risk of near-crash drive events. With more than 9.5 million Americans working overnight or rotating shifts and one-third of United States commutes exceeding 30 min, these results have implications for traffic and occupational safety. PMID:26699470

High risk of near-crash driving events following night-shift work.

PubMed

Lee, Michael L; Howard, Mark E; Horrey, William J; Liang, Yulan; Anderson, Clare; Shreeve, Michael S; O'Brien, Conor S; Czeisler, Charles A

2016-01-05

Night-shift workers are at high risk of drowsiness-related motor vehicle crashes as a result of circadian disruption and sleep restriction. However, the impact of actual night-shift work on measures of drowsiness and driving performance while operating a real motor vehicle remains unknown. Sixteen night-shift workers completed two 2-h daytime driving sessions on a closed driving track at the Liberty Mutual Research Institute for Safety: (i) a postsleep baseline driving session after an average of 7.6 ± 2.4 h sleep the previous night with no night-shift work, and (ii) a postnight-shift driving session following night-shift work. Physiological measures of drowsiness were collected, including infrared reflectance oculography, electroencephalography, and electrooculography. Driving performance measures included lane excursions, near-crash events, and drives terminated because of failure to maintain control of the vehicle. Eleven near-crashes occurred in 6 of 16 postnight-shift drives (37.5%), and 7 of 16 postnight-shift drives (43.8%) were terminated early for safety reasons, compared with zero near-crashes or early drive terminations during 16 postsleep drives (Fishers exact: P = 0.0088 and P = 0.0034, respectively). Participants had a significantly higher rate of lane excursions, average Johns Drowsiness Scale, blink duration, and number of slow eye movements during postnight-shift drives compared with postsleep drives (3.09/min vs. 1.49/min; 1.71 vs. 0.97; 125 ms vs. 100 ms; 35.8 vs. 19.1; respectively, P < 0.05 for all). Night-shift work increases driver drowsiness, degrading driving performance and increasing the risk of near-crash drive events. With more than 9.5 million Americans working overnight or rotating shifts and one-third of United States commutes exceeding 30 min, these results have implications for traffic and occupational safety.

The influence of daily sleep patterns of commercial truck drivers on driving performance.

PubMed

Chen, Guang Xiang; Fang, Youjia; Guo, Feng; Hanowski, Richard J

2016-06-01

Fatigued and drowsy driving has been found to be a major cause of truck crashes. Lack of sleep is the number one cause of fatigue and drowsiness. However, there are limited data on the sleep patterns (sleep duration, sleep percentage in the duration of non-work period, and the time when sleep occurred) of truck drivers in non-work periods and the impact on driving performance. This paper examined sleep patterns of 96 commercial truck drivers during non-work periods and evaluated the influence these sleep patterns had on truck driving performance. Data were from the Naturalistic Truck Driving Study. Each driver participated in the study for approximately four weeks. A shift was defined as a non-work period followed by a work period. A total of 1397 shifts were identified. Four distinct sleep patterns were identified based on sleep duration, sleep start/end point in a non-work period, and the percentage of sleep with reference to the duration of non-work period. Driving performance was measured by safety-critical events, which included crashes, near-crashes, crash-relevant conflicts, and unintentional lane deviations. Negative binomial regression was used to evaluate the association between the sleep patterns and driving performance, adjusted for driver demographic information. The results showed that the sleep pattern with the highest safety-critical event rate was associated with shorter sleep, sleep in the early stage of a non-work period, and less sleep between 1 a.m. and 5 a.m. This study also found that male drivers, with fewer years of commercial vehicle driving experience and higher body mass index, were associated with deteriorated driving performance and increased driving risk. The results of this study could inform hours-of-service policy-making and benefit safety management in the trucking industry. Published by Elsevier Ltd.

Automated Driving System Architecture to Ensure Safe Delegation of Driving Authority

NASA Astrophysics Data System (ADS)

YUN, Sunkil; NISHIMURA, Hidekazu

2016-09-01

In this paper, the architecture of an automated driving system (ADS) is proposed to ensure safe delegation of driving authority between the ADS and a driver. Limitations of the ADS functions may activate delegation of driving authority to a driver. However, it leads to severe consequences in emergency situations where a driver may be drowsy or distracted. To address these issues, first, the concept model for the ADS in the situation for delegation of driving authority is described taking the driver's behaviour and state into account. Second, the behaviour / state of a driver and functional flow / state of ADS and the interactions between them are modelled to understand the context where the ADS requests to delegate the driving authority to a driver. Finally, the proposed architecture of the ADS is verified under the simulations based on the emergency braking scenarios. In the verification process using simulation, we have derived the necessary condition for safe delegation of driving authority is that the ADS should assist s driver even after delegating driving authority to a driver who has not enough capability to regain control of the driving task.

Regulating danger on the highways: hours of service regulations.

PubMed

Mansfield, Daniel; Kryger, Meir

2015-12-01

Current hours of service regulations governing commercial truck drivers in place in the United States, Canada, Australia, and the European Union are summarized and compared to facilitate the assessment of the effectiveness of such provisions in preventing fatigue and drowsiness among truck drivers. Current hours of service provisions governing commercial truck drivers were derived from governmental sources. The commercial truck driver hours of service provisions in the United States, Canada, and the European Union permit drivers to work 14 hours and those of Australia permit drivers to work 12 hours a day on a regular basis. The regulations do not state what a driver may do with time off. They are consistent with a driver being able to drive after 24 hours without sleep. They do not take into account circadian rhythm by linking driving or rest to time of day. Current hours of service regulations governing commercial truck drivers leave gaps--permitting drivers to work long hours on a regular basis, permitting driving after no sleep for 24 hours, and failing to take into account the importance of circadian rhythm, endangering the public safety and the truck drivers themselves. Copyright © 2015 National Sleep Foundation. Published by Elsevier Inc. All rights reserved.

Development of wireless brain computer interface with embedded multitask scheduling and its application on real-time driver's drowsiness detection and warning.

PubMed

Lin, Chin-Teng; Chen, Yu-Chieh; Huang, Teng-Yi; Chiu, Tien-Ting; Ko, Li-Wei; Liang, Sheng-Fu; Hsieh, Hung-Yi; Hsu, Shang-Hwa; Duann, Jeng-Ren

2008-05-01

Biomedical signal monitoring systems have been rapidly advanced with electronic and information technologies in recent years. However, most of the existing physiological signal monitoring systems can only record the signals without the capability of automatic analysis. In this paper, we proposed a novel brain-computer interface (BCI) system that can acquire and analyze electroencephalogram (EEG) signals in real-time to monitor human physiological as well as cognitive states, and, in turn, provide warning signals to the users when needed. The BCI system consists of a four-channel biosignal acquisition/amplification module, a wireless transmission module, a dual-core signal processing unit, and a host system for display and storage. The embedded dual-core processing system with multitask scheduling capability was proposed to acquire and process the input EEG signals in real time. In addition, the wireless transmission module, which eliminates the inconvenience of wiring, can be switched between radio frequency (RF) and Bluetooth according to the transmission distance. Finally, the real-time EEG-based drowsiness monitoring and warning algorithms were implemented and integrated into the system to close the loop of the BCI system. The practical online testing demonstrates the feasibility of using the proposed system with the ability of real-time processing, automatic analysis, and online warning feedback in real-world operation and living environments.

Driver education: Enhancing knowledge of sleep, fatigue and risky behaviour to improve decision making in young drivers.

PubMed

Alvaro, Pasquale K; Burnett, Nicole M; Kennedy, Gerard A; Min, William Yu Xun; McMahon, Marcus; Barnes, Maree; Jackson, Melinda; Howard, Mark E

2018-03-01

This study assessed the impact of an education program on knowledge of sleepiness and driving behaviour in young adult drivers and their performance and behaviour during simulated night driving. Thirty-four participants (18-26 years old) were randomized to receive either a four-week education program about sleep and driving or a control condition. A series of questionnaires were administered to assess knowledge of factors affecting sleep and driving before and after the four-week education program. Participants also completed a two hour driving simulator task at 1am after 17 h of extended wakefulness to assess the impact on driving behaviour. There was an increase in circadian rhythm knowledge in the intervention group following the education program. Self-reported risky behaviour increased in the control group with no changes in other aspects of sleep knowledge. There were no significant differences in proportion of intervention and control participants who had microsleeps (p ≤ .096), stopped driving due to sleepiness (p = .107), recorded objective episodes of drowsiness (p = .455), and crashed (p = .761), although there was a trend towards more control participants having microsleeps and stopping driving. Those in the intervention group reported higher subjective sleepiness at the end of the drive [M = 6.25, SD = 3.83, t(31) = 2.15, p = .05] and were more likely to indicate that they would stop driving [M = 3.08, SD = 1.16, t(31) = 2.24, p = .04]. The education program improved some aspects of driver knowledge about sleep and safety. The results also suggested that the education program lead to an increased awareness of sleepiness. Education about sleep and driving could reduce the risk of drowsy driving and associated road trauma in young drivers, but requires evaluation in a broader sample with assessment of real world driving outcomes. Copyright © 2017 Elsevier Ltd. All rights reserved.

The influence of vibration on seated human drowsiness

PubMed Central

AZIZAN, Amzar; FARD, Mohammad; AZARI, Michael F.; BENEDIKTSDÓTTIR, Bryndís; ARNARDÓTTIR, Erna Sif; JAZAR, Reza; MAEDA, Setsuo

2016-01-01

Although much is known about human body vibration discomfort, there is little research data on the effects of vibration on vehicle occupant drowsiness. A laboratory experimental setup has been developed. Vibration was applied to the volunteers sitting on the vehicle seat mounted on the vibration platform. Seated volunteers were exposed to a Gaussian random vibration, with 1–15 Hz frequency bandwidth at 0.2 ms−2 r.m.s., for 20-minutes. Two drowsiness measurement methods were used, Psychomotor Vigilance Test (PVT) and Karolinska Sleepiness Scale (KSS). Significant changes in PVT (p<0.05) and KSS (p<0.05) were detected in all eighteen volunteers. Furthermore, a moderate correlation (r>0.4) was observed between objective measurement (PVT) and subjective measurement (KSS). The results suggest that exposure to vibration even for 20-minutes can cause significant drowsiness impairing psychomotor performance. This finding has important implications for road safety. PMID:26829971

Modeling EEG fractal dimension changes in wake and drowsy states in humans--a preliminary study.

PubMed

Bojić, Tijana; Vuckovic, Aleksandra; Kalauzi, Aleksandar

2010-01-21

Aim of this preliminary study was to examine and compare topographic distribution of Higuchi's fractal dimension (FD, measure of signal complexity) of EEG signals between states of relaxed wakefulness and drowsiness, as well as their FD differences. The experiments were performed on 10 healthy individuals using a fourteen-channel montage. An explanation is offered on the causes of the detected FD changes. FD values of 60s records belonging to wake (Hori's stage 1) and drowsy (Hori's stages 2-4) states were calculated for each channel and each subject. In 136 out of 140 epochs an increase in FD was obtained. Relationship between signal FD and its relative alpha amplitude was mathematically modeled and we quantitatively demonstrated that the increase in FD was predominantly due to a reduction in alpha activity. The model was generalized to include other EEG oscillations. By averaging FD values for each channel across 10 subjects, four clusters (O2O1; T6P4T5P3; C3F3F4C4F8F7; T4T3) for the wake and two clusters (O2O1P3T6P4T5; C3C4F4F3F8T4T3F7) for the drowsy state were statistically verified. Topographic distribution of FD values in wakefulness showed a lateral symmetry and a partial fronto-occipital gradient. In drowsiness, a reduction in the number of clusters was detected, due to regrouping of channels T3, T4, O1 and O2. Topographic distribution of absolute FD differences revealed largest values at F7, O1 and F3. Reorganization of channel clusters showed that regionalized brain activity, specific for wakefulness, became more global by entering into drowsiness. Since the global increase in FD during wake-to-drowsy transition correlated with the decrease of alpha power, we inferred that increase of EEG complexity may not necessarily be an index of brain activation.

The relative importance of real-time in-cab and external feedback in managing fatigue in real-world commercial transport operations.

PubMed

Fitzharris, Michael; Liu, Sara; Stephens, Amanda N; Lenné, Michael G

2017-05-29

Real-time driver monitoring systems represent a solution to address key behavioral risks as they occur, particularly distraction and fatigue. The efficacy of these systems in real-world settings is largely unknown. This article has three objectives: (1) to document the incidence and duration of fatigue in real-world commercial truck-driving operations, (2) to determine the reduction, if any, in the incidence of fatigue episodes associated with providing feedback, and (3) to tease apart the relative contribution of in-cab warnings from 24/7 monitoring and feedback to employers. Data collected from a commercially available in-vehicle camera-based driver monitoring system installed in a commercial truck fleet operating in Australia were analyzed. The real-time driver monitoring system makes continuous assessments of driver drowsiness based on eyelid position and other factors. Data were collected in a baseline period where no feedback was provided to drivers. Real-time feedback to drivers then occurred via in-cab auditory and haptic warnings, which were further enhanced by direct feedback by company management when fatigue events were detected by external 24/7 monitors. Fatigue incidence rates and their timing of occurrence across the three time periods were compared. Relative to no feedback being provided to drivers when fatigue events were detected, in-cab warnings resulted in a 66% reduction in fatigue events, with a 95% reduction achieved by the real-time provision of direct feedback in addition to in-cab warnings (p < 0.01). With feedback, fatigue events were shorter in duration a d occurred later in the trip, and fewer drivers had more than one verified fatigue event per trip. That the provision of feedback to the company on driver fatigue events in real time provides greater benefit than feedback to the driver alone has implications for companies seeking to mitigate risks associated with fatigue. Having fewer fatigue events is likely a reflection of the device itself and the accompanying safety culture of the company in terms of how the information is used. Data were analysed on a per-truck trip basis, and the findings are indicative of fatigue events in a large-scale commercial transport fleet. Future research ought to account for individual driver performance, which was not possible with the available data in this retrospective analysis. Evidence that real-time driver monitoring feedback is effective in reducing fatigue events is invaluable in the development of fleet safety policies, and of future national policy and vehicle safety regulations. Implications for automotive driver monitoring are discussed.

Cell phone users, reported crash risk, unsafe driving behaviors and dispositions: a survey of motorists in Maryland.

PubMed

Beck, Kenneth H; Yan, Fang; Wang, Min Qi

2007-01-01

The purpose of this investigation was to identify risky driving behaviors and dispositions that distinguish drivers who use a cell phone while operating a motor vehicle from non-cell phone using drivers. Annual telephone surveys were used to identify drivers who reported using a cell phone while driving in the last month (n=1803) and were compared to those who said they did not use cell phones while driving (n=1578). Cell phone using drivers were more likely to report driving while drowsy, going 20 mph over the speed limit, driving aggressively, running a stop sign or red light, and driving after having had several drinks. They were also more likely to have had a prior history of citation and crash involvement than non-cell phone using drivers. Cell phone using drivers also reported they were less careful and more in a hurry when they drive than non-cell phone using drivers. Cell phone using drivers report engaging in many behaviors that place them at risk for a traffic crash, independent of the specific driving impairments that cell phone usage may produce. Strategies that combine coordinated and sustained enforcement activities along with widespread public awareness campaigns hold promise as effective countermeasures for these drivers, who resemble aggressive drivers in many respects.

Mobile Healthcare for Automatic Driving Sleep-Onset Detection Using Wavelet-Based EEG and Respiration Signals

PubMed Central

Lee, Boon-Giin; Lee, Boon-Leng; Chung, Wan-Young

2014-01-01

Driving drowsiness is a major cause of traffic accidents worldwide and has drawn the attention of researchers in recent decades. This paper presents an application for in-vehicle non-intrusive mobile-device-based automatic detection of driver sleep-onset in real time. The proposed application classifies the driving mental fatigue condition by analyzing the electroencephalogram (EEG) and respiration signals of a driver in the time and frequency domains. Our concept is heavily reliant on mobile technology, particularly remote physiological monitoring using Bluetooth. Respiratory events are gathered, and eight-channel EEG readings are captured from the frontal, central, and parietal (Fpz-Cz, Pz-Oz) regions. EEGs are preprocessed with a Butterworth bandpass filter, and features are subsequently extracted from the filtered EEG signals by employing the wavelet-packet-transform (WPT) method to categorize the signals into four frequency bands: α, β, θ, and δ. A mutual information (MI) technique selects the most descriptive features for further classification. The reduction in the number of prominent features improves the sleep-onset classification speed in the support vector machine (SVM) and results in a high sleep-onset recognition rate. Test results reveal that the combined use of the EEG and respiration signals results in 98.6% recognition accuracy. Our proposed application explores the possibility of processing long-term multi-channel signals. PMID:25264954

Comparisons of Traffic Collisions between Expressways and Rural Roads in Truck Drivers.

PubMed

Lee, Sangbok; Jeong, Byung Yong

2016-03-01

Truck driving is known as one of the occupations with the highest accident rate. This study investigates the characteristics of traffic collisions according to road types (expressway and rural road). Classifying 267 accidents into expressway and rural road, we analyzed them based on driver characteristics (age, working experience, size of employment), time characteristics (day of accident, time, weather), and accident characteristics (accident causes, accident locations, accident types, driving conditions). When we compared the accidents by road conditions, no differences were found between the driver characteristics. However, from the accident characteristics, the injured person distributions were different by the road conditions. In particular, driving while drowsy is shown to be highly related with the accident characteristics. This study can be used as a guideline and a base line to develop a plan of action to prevent traffic accidents. It can also help to prepare formal regulations about a truck driver's vehicle maintenance and driving attitude for a precaution on road accidents.

Comparisons of Traffic Collisions between Expressways and Rural Roads in Truck Drivers

PubMed Central

Lee, Sangbok; Jeong, Byung Yong

2015-01-01

Background Truck driving is known as one of the occupations with the highest accident rate. This study investigates the characteristics of traffic collisions according to road types (expressway and rural road). Methods Classifying 267 accidents into expressway and rural road, we analyzed them based on driver characteristics (age, working experience, size of employment), time characteristics (day of accident, time, weather), and accident characteristics (accident causes, accident locations, accident types, driving conditions). Results When we compared the accidents by road conditions, no differences were found between the driver characteristics. However, from the accident characteristics, the injured person distributions were different by the road conditions. In particular, driving while drowsy is shown to be highly related with the accident characteristics. Conclusion This study can be used as a guideline and a base line to develop a plan of action to prevent traffic accidents. It can also help to prepare formal regulations about a truck driver's vehicle maintenance and driving attitude for a precaution on road accidents. PMID:27014489

School start times and teenage driver motor vehicle crashes.

PubMed

Foss, Robert D; Smith, Richard L; O'Brien, Natalie P

2018-04-26

Shifting school start times to 8:30 am or later has been found to improve academic performance and reduce behavior problems. Limited research suggests this may also reduce adolescent driver motor vehicle crashes. A change in the school start time from 7:30 am to 8:45 am for all public high schools in one North Carolina county presented the opportunity to address this question with greater methodologic rigor. We conducted ARIMA interrupted time-series analyses to examine motor vehicle crash rates of high school age drivers in the intervention county and 3 similar comparison counties with comparable urban-rural population distribution. To focus on crashes most likely to be affected, we limited analysis to crashes involving 16- & 17-year-old drivers occurring on days when school was in session. In the intervention county, there was a 14% downward shift in the time-series following the 75 min delay in school start times (p = .076). There was no change approaching statistical significance in any of the other three counties. Further analysis indicated marked, statistically significant shifts in hourly crash rates in the intervention county, reflecting effects of the change in school start time on young driver exposure. Crashes from 7 to 7:59 am decreased sharply (-25%, p = .008), but increased similarly from 8 to 8:59 am (21%, p = .004). Crashes from 2 to 2:59 pm declined dramatically (-48%, p = .000), then increased to a lesser degree from 3 to 3:59 pm (32%, p = .024) and non-significantly from 4 to 4:59 (19%, p = .102). There was no meaningful change in early morning or nighttime crashes, when drowsiness-induced crashes might have been expected to be most common. The small decrease in crashes among high school age drivers following the shift in school start time is consistent with the findings of other studies of teen driver crashes and school start times. All these studies, including the present one, have limitations, but the similar findings suggest that crashes and school start times are indeed related, with earlier start times equating to more crashes. Later high school start times (>8:30 am) appear to be associated with lower adolescent driver crash rates, but additional research is needed to confirm this and to identify the mechanism by which this occurs (reduced drowsiness or reduced exposure). Copyright © 2018 Elsevier Ltd. All rights reserved.

Correlation between driving errors and vigilance level: influence of the driver's age.

PubMed

Campagne, Aurelie; Pebayle, Thierry; Muzet, Alain

2004-01-01

During long and monotonous driving at night, most drivers progressively show signs of visual fatigue and loss of vigilance. Their capacity to maintain adequate driving performance usually is affected and varies with the age of the driver. The main question is to know, on one hand, if occurrence of fatigue and drowsiness is accompanied by a modification in the driving performance of the driver and, on the other hand, if this relationship partially depends on the driver's age. Forty-six male drivers, divided into three age categories: 20-30, 40-50, and 60-70 years, performed a 350-km motorway driving session at night on a driving simulator. Driving errors were measured in terms of number of running-off-the-road incidents (RORI) and large speed deviations. The evolution of physiological vigilance level was evaluated using electroencephalography (EEG) recording. In older drivers, in comparison with young and middle-aged drivers, the degradation of driving performance was correlated to the evolution of lower frequency waking EEG (i.e., theta). Contrary to young and middle-aged drivers, the deterioration of the vigilance level attested by EEG correlated with the increase in gravity of all studied driving errors in older drivers. Thus, depending on the age category considered, only part of the driving errors would constitute a relevant indication as for the occurrence of a state of low arousal.

An exploratory study of long-haul truck drivers' secondary tasks and reasons for performing them.

PubMed

Iseland, Tobias; Johansson, Emma; Skoog, Siri; Dåderman, Anna M

2018-08-01

Research on drivers has shown how certain visual-manual secondary tasks, unrelated to driving, increase the risk of being involved in crashes. The purpose of the study was to investigate (1) if long-haul truck drivers in Sweden engage in secondary tasks while driving, what tasks are performed and how frequently, (2) the drivers' self-perceived reason/s for performing them, and (3) if psychological factors might reveal reasons for their engaging in secondary tasks. The study comprised 13 long-haul truck drivers and was conducted through observations, interviews, and questionnaires. The drivers performed secondary tasks, such as work environment related "necessities" (e.g., getting food and/or beverages from the refrigerator/bag, eating, drinking, removing a jacket, face rubbing, and adjusting the seat), interacting with a mobile phone/in-truck technology, and doing administrative tasks. The long-haul truck drivers feel bored and use secondary tasks as a coping strategy to alleviate boredom/drowsiness, and for social interaction. The higher number of performed secondary tasks could be explained by lower age, shorter driver experience, less openness to experience, lower honesty-humility, lower perceived stress, lower workload, and by higher health-related quality of life. These explanatory results may serve as a starting point for further studies on large samples to develop a safer and healthier environment for long-haul truck drivers. Copyright © 2018. Published by Elsevier Ltd.

Teen Crashes Declined After Massachusetts Raised Penalties For Graduated Licensing Law Restricting Night Driving.

PubMed

Rajaratnam, Shantha M W; Landrigan, Christopher P; Wang, Wei; Kaprielian, Rachel; Moore, Richard T; Czeisler, Charles A

2015-06-01

In 2007, as part of the Massachusetts graduated driver-licensing program designed to allow junior operators (ages 16½-17 years) to gain experience before receiving full licensure, stringent penalties were introduced for violating a law prohibiting unsupervised driving at night; driver education, including drowsy driving education, became mandatory; and other new restrictions and penalties began. We evaluated the impact of these changes on police-reported vehicle crash records for one year before and five years after the law's implementation in drivers ages 16-17, inclusive, and two comparison groups. We found that crash rates for the youngest drivers fell 18.6 percent, from 16.24 to 13.22 per 100 licensed drivers. For drivers ages 18-19 the rates fell by 6.7 percent (from 9.59 to 8.95 per 100 drivers), and for those ages 20 and older, the rate remained relatively constant. The incidence rate ratio for drivers ages 16-17 relative to those ages 20 and older decreased 19.1 percent for all crashes, 39.8 percent for crashes causing a fatal or incapacitating injury, and 28.8 percent for night crashes. Other states should consider implementing strict penalties for violating graduated driver-licensing laws, including restrictions on unsupervised night driving, to reduce the risk of sleep-related crashes in young people. Project HOPE—The People-to-People Health Foundation, Inc.

Real-time monitoring of drowsiness through wireless nanosensor systems

NASA Astrophysics Data System (ADS)

Ramasamy, Mouli; Varadan, Vijay K.

2016-04-01

Detection of sleepiness and drowsiness in human beings has been a daunting task for both engineering and medical technologies. Accuracy, precision and promptness of detection have always been an issue that has to be dealt by technologists. Generally, the bio potential signals - ECG, EOG, EEG and EMG are used to classify and discriminate sleep from being awake. However, the potential drawbacks may be high false detections, low precision, obtrusiveness, aftermath analysis, etc. To overcome the disadvantages, this paper reviews the design aspects of a wireless and a real time monitoring system to track sleep and detect fatigue. This concept involves the use of EOG and EEG to measure the blink rate and asses the person's condition. In this user friendly and intuitive approach, EOG and EEG signals are obtained by the textile based nanosensors mounted on the inner side of a flexible headband. The acquired signals are then electrically transmitted to the data processing and transmission unit, which transmits the processed data to the receiver/monitoring module through ZigBee communication. This system is equipped with a software program to process, feature extract, analyze, display and store the information. Thereby, immediate detection of a person falling asleep is made feasible and, tracking the sleep cycle continuously provides an insight about the fatigue level. This approach of using a wireless, real time, dry sensor on a flexible substrate mitigates obtrusiveness that is expected from a wearable system. We have previously presented the results of the aforementioned wearable systems. This paper aims to extend our work conceptually through a review of engineering and medical techniques involved in wearable systems to detect drowsiness.

Awareness during drowsiness: dynamics and electrophysiological correlates

NASA Technical Reports Server (NTRS)

Makeig, S.; Jung, T. P.; Sejnowski, T. J.

2000-01-01

During drowsy periods, performance on tasks requiring continuous attention becomes intermittent. Previously, we have reported that during drowsy periods of intermittent performance, 7 of 10 participants performing an auditory detection task exhibited episodes of non-responding lasting about 18 s (Makeig & Jung, 1996). Further, the time patterns of these episodes were repeated precisely in subsequent sessions. The 18-s cycles were accompanied by counterbalanced power changes within two frequency bands in the vertex EEG (near 4 Hz and circa 40 Hz). In the present experiment, performance patterns and concurrent EEG spectra were examined in four participants performing a continuous visuomotor compensatory tracking task in 15-20 minute bouts during a 42-hour sleep deprivation study. During periods of good performance, participants made compensatory trackball movements about twice per second, attempting to keep a target disk near a central ring. Autocorrelations of time series representing the distance of the target disk from the ring centre showed that during periods of poor performance marked near-18-s cycles in performance again appeared. There were phases of poor or absent performance accompanied by an increase in EEG power that was largest at 3-4 Hz. These studies show that in drowsy humans, opening and closing of the gates of behavioural awareness is marked not by the appearance of (12-14 Hz) sleep spindles, but by prominent EEG amplitude changes in the low theta band. Further, both EEG and behavioural changes during drowsiness often exhibit stereotyped 18-s cycles.

Ventilation and Heart Rate Monitoring in Drivers using a Contactless Electrical Bioimpedance System

NASA Astrophysics Data System (ADS)

Macías, R.; García, M. A.; Ramos, J.; Bragós, R.; Fernández, M.

2013-04-01

Nowadays, the road safety is one of the most important priorities in the automotive industry. Many times, this safety is jeopardized because of driving under inappropriate states, e.g. drowsiness, drugs and/or alcohol. Therefore several systems for monitoring the behavior of subjects during driving are researched. In this paper, a device based on a contactless electrical bioimpedance system is shown. Using the four-wire technique, this system is capable of obtaining the heart rate and the ventilation of the driver through multiple textile electrodes. These textile electrodes are placed on the car seat and the steering wheel. Moreover, it is also reported several measurements done in a controlled environment, i.e. a test room where there are no artifacts due to the car vibrations or the road state. In the mentioned measurements, the system response can be observed depending on several parameters such as the placement of the electrodes or the number of clothing layers worn by the driver.

A Study of Deep CNN-Based Classification of Open and Closed Eyes Using a Visible Light Camera Sensor.

PubMed

Kim, Ki Wan; Hong, Hyung Gil; Nam, Gi Pyo; Park, Kang Ryoung

2017-06-30

The necessity for the classification of open and closed eyes is increasing in various fields, including analysis of eye fatigue in 3D TVs, analysis of the psychological states of test subjects, and eye status tracking-based driver drowsiness detection. Previous studies have used various methods to distinguish between open and closed eyes, such as classifiers based on the features obtained from image binarization, edge operators, or texture analysis. However, when it comes to eye images with different lighting conditions and resolutions, it can be difficult to find an optimal threshold for image binarization or optimal filters for edge and texture extraction. In order to address this issue, we propose a method to classify open and closed eye images with different conditions, acquired by a visible light camera, using a deep residual convolutional neural network. After conducting performance analysis on both self-collected and open databases, we have determined that the classification accuracy of the proposed method is superior to that of existing methods.

The relationship between nurse work schedules, sleep duration, and drowsy driving.

PubMed

Scott, Linda D; Hwang, Wei-Ting; Rogers, Ann E; Nysse, Tami; Dean, Grace E; Dinges, David F

2007-12-01

Recent studies have shown that extended shifts worked by hospital staff nurses are associated with significantly higher risk of errors, yet little information is available about the ability to remain alert during the nurses' commutes following the completion of an extended work shift. The purpose of this study is to describe the prevalence of drowsy driving episodes and the relationship between drowsy driving and nurse work hours, alertness on duty, working at night, and sleep duration. Data were collected from 2 national random samples of registered nurses (n=895). Full-time hospital staff nurses (n=895) completed logbooks on a daily basis for 4 weeks providing information concerning work hours, sleep duration, drowsy and sleep episodes at work, and drowsy driving occurrences. Almost 600 of the nurses (596/895) reported at least 1 episode of drowsy driving, and 30 nurses reported experiencing drowsy driving following every shift worked. Shorter sleep durations, working at night, and difficulties remaining awake at work significantly increased the likelihood of drowsy driving episodes. Given the large numbers of nurses who reported struggling to stay awake when driving home from work and the frequency with which nurses reported drowsy driving, greater attention should be paid to increasing nurse awareness of the risks and to implementing strategies to prevent drowsy driving episodes to ensure public safety. Without mitigation, fatigued nurses will continue to put the public and themselves at risk.

Monotony of road environment and driver fatigue: a simulator study.

PubMed

Thiffault, Pierre; Bergeron, Jacques

2003-05-01

Studies have shown that drowsiness and hypovigilance frequently occur during highway driving and that they may have serious implications in terms of accident causation. This paper focuses on the task induced factors that are involved in the development of these phenomena. A driving simulator study was conducted in order to evaluate the impact of the monotony of roadside visual stimulation using a steering wheel movement (SWM) analysis procedure. Fifty-six male subjects each drove during two different 40-min periods. In one case, roadside visual stimuli were essentially repetitive and monotonous, while in the other one, the environment contained disparate visual elements aiming to disrupt monotony without changing road geometry. Subject's driving performance was compared across these conditions in order to determine whether disruptions of monotony can have a positive effect and help alleviate driver fatigue. Results reveal an early time-on-task effect on driving performance for both driving periods and more frequent large SWM when driving in the more monotonous road environment, which implies greater fatigue and vigilance decrements. Implications in terms of environmental countermeasures for driver fatigue are discussed.

Potential distractions and unsafe driving behaviors among drivers of 1- to 12-year-old children.

PubMed

Macy, Michelle L; Carter, Patrick M; Bingham, C Raymond; Cunningham, Rebecca M; Freed, Gary L

2014-01-01

Driver distraction has been identified as a threat to individual drivers and public health. Motor vehicle collisions remain a leading cause of death for children, yet little is known about distractions among drivers of children. This study sought to characterize potential distractions among drivers of children. A 2-site, cross-sectional, computerized survey of child passenger safety practices was conducted among adult drivers of 1- to 12-year-old children who presented for emergency care between October 2011 to May 2012. Drivers indicated the frequency with which they engaged in 10 potential distractions in the past month while driving with their child. Distractions were grouped in 4 categories: (1) nondriving, (2) cellular phone, (3) child, and (4) directions. Information about other unsafe driving behaviors and sociodemographic characteristics was collected. Nearly 90% of eligible parents participated. Analysis included 570 drivers (92.2%). Non-driving-related and cellular phone-related distractions were disclosed by >75% of participants. Fewer participants disclosed child (71.2%) and directions-related distractions (51.9%). Child age was associated with each distraction category. Cellular phone-related distractions were associated with the child riding daily in the family car, non-Hispanic white, and higher education. Parents admitting to drowsy driving and being pulled over for speeding had over 2 times higher odds of disclosing distractions from each category. Distracted driving activities are common among drivers of child passengers and are associated with other unsafe driving behaviors. Child passenger safety may be improved by preventing crash events through the reduction or elimination of distractions among drivers of child passengers. Copyright © 2014 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.

Potential Distractions and Unsafe Driving Behaviors Among Drivers of 1- to 12-year-old Children

PubMed Central

Macy, Michelle L.; Carter, Patrick M.; Bingham, C. Raymond; Cunningham, Rebecca M.; Freed, Gary L.

2014-01-01

Objective Driver distraction has been identified as a threat to individual drivers and public health. Motor vehicle collisions remain a leading cause of death for children yet little is known about distractions among drivers of children. This study sought to characterize potential distractions among drivers of children. Methods A two-site, cross-sectional, computerized survey of child passenger safety practices was conducted among adult drivers of 1- to 12-year-old children who presented for emergency care between October 2011-May 2012. Drivers indicated the frequency with which they engaged in ten potential distractions in the past month while driving with their child. Distractions were grouped in four categories: 1) non-driving, 2) cellular phone, 3) child, 4) directions. Information about other unsafe driving behaviors and sociodemographic characteristics was collected. Results Nearly 90% of eligible parents participated. Analysis included 570 (92.2%) drivers. Non-driving and cellular phone-related distractions were disclosed by >75% of participants. Fewer participants disclosed child (71.2%) and directions-related distractions (51.9%). Child age was associated with each distraction category. Cellular phone-related distractions were associated with the child riding daily in the family car, non-Hispanic white and other race/ethnicity, and higher education. Parents admitting to drowsy driving and being pulled over for speeding had over two-times higher odds of disclosing distractions from each category. Conclusions Distracted driving activities are common among drivers of child passengers and associated with other unsafe driving behaviors. Child passenger safety may be improved by preventing crash events through the reduction or elimination of distractions among drivers of child passengers. PMID:24767781

Intentions and willingness to drive while drowsy among university students: An application of an extended theory of planned behavior model.

PubMed

Lee, Clark J; Geiger-Brown, Jeanne; Beck, Kenneth H

2016-08-01

A web-based questionnaire was used to assess the utility of constructs from the Theory of Planned Behavior (TPB) and the Prototype Willingness Model (PWM) to predict intentions and willingness to engage in drowsy driving in a sample of 450 university students. Those students who reported more favorable attitudes and subjective norm and greater perceived control and willingness in relation to drowsy driving behavior were more likely to report stronger intentions to engage in drowsy driving behavior. Augmenting the TPB constructs with the PWM construct of willingness significantly explained up to an additional 8 percent of the variance in drowsy driving intention. Perceived behavioral control and willingness were consistently the strongest predictors of drowsy driving intention in the augmented model, which together with the control (personal) variables explained up to 70 percent of the variance in intention. Thus, the Theory of Planned Behavior and the Prototype Willingness Model may be useful for understanding motivational influences on drowsy driving behavior in young people and present promising theoretical frameworks for designing more effective interventions against drowsy driving in this population. Copyright © 2016 Elsevier Ltd. All rights reserved.

Prevalence of teen driver errors leading to serious motor vehicle crashes.

PubMed

Curry, Allison E; Hafetz, Jessica; Kallan, Michael J; Winston, Flaura K; Durbin, Dennis R

2011-07-01

Motor vehicle crashes are the leading cause of adolescent deaths. Programs and policies should target the most common and modifiable reasons for crashes. We estimated the frequency of critical reasons for crashes involving teen drivers, and examined in more depth specific teen driver errors. The National Highway Traffic Safety Administration's (NHTSA) National Motor Vehicle Crash Causation Survey collected data at the scene of a nationally representative sample of 5470 serious crashes between 7/05 and 12/07. NHTSA researchers assigned a single driver, vehicle, or environmental factor as the critical reason for the event immediately leading to each crash. We analyzed crashes involving 15-18 year old drivers. 822 teen drivers were involved in 795 serious crashes, representing 335,667 teens in 325,291 crashes. Driver error was by far the most common reason for crashes (95.6%), as opposed to vehicle or environmental factors. Among crashes with a driver error, a teen made the error 79.3% of the time (75.8% of all teen-involved crashes). Recognition errors (e.g., inadequate surveillance, distraction) accounted for 46.3% of all teen errors, followed by decision errors (e.g., following too closely, too fast for conditions) (40.1%) and performance errors (e.g., loss of control) (8.0%). Inadequate surveillance, driving too fast for conditions, and distracted driving together accounted for almost half of all crashes. Aggressive driving behavior, drowsy driving, and physical impairments were less commonly cited as critical reasons. Males and females had similar proportions of broadly classified errors, although females were specifically more likely to make inadequate surveillance errors. Our findings support prioritization of interventions targeting driver distraction and surveillance and hazard awareness training. Copyright © 2010 Elsevier Ltd. All rights reserved.

A Study of Deep CNN-Based Classification of Open and Closed Eyes Using a Visible Light Camera Sensor

PubMed Central

Kim, Ki Wan; Hong, Hyung Gil; Nam, Gi Pyo; Park, Kang Ryoung

2017-01-01

The necessity for the classification of open and closed eyes is increasing in various fields, including analysis of eye fatigue in 3D TVs, analysis of the psychological states of test subjects, and eye status tracking-based driver drowsiness detection. Previous studies have used various methods to distinguish between open and closed eyes, such as classifiers based on the features obtained from image binarization, edge operators, or texture analysis. However, when it comes to eye images with different lighting conditions and resolutions, it can be difficult to find an optimal threshold for image binarization or optimal filters for edge and texture extraction. In order to address this issue, we propose a method to classify open and closed eye images with different conditions, acquired by a visible light camera, using a deep residual convolutional neural network. After conducting performance analysis on both self-collected and open databases, we have determined that the classification accuracy of the proposed method is superior to that of existing methods. PMID:28665361

Truckers drive their own assessment for obstructive sleep apnea: a collaborative approach to online self-assessment for obstructive sleep apnea.

PubMed

Smith, Ben; Phillips, Barbara A

2011-06-15

Commercial motor vehicle drivers are at an increased risk for obstructive sleep apnea (OSA). The Federal Motor Carrier Safety Administration (FMCSA) Medical Review Board has recommended that commercial motor vehicle drivers undergo testing for OSA if they have a positive Berlin Questionnaire or a BMI ≥ 30 kg/m(2). We developed an online screening tool based on the Berlin Questionnaire for anonymous use by commercial drivers to assess their risk of OSA prior to their required FMCSA physicals. We based the survey on the Berlin Sleep Questionnaire. The survey was hosted on the Truckers for a Cause Chapter of Alert Well and Keeping Energetic of the American Sleep Apnea Association (TFAC-AWAKE) organization website, and was promoted through the TFAC's XM radio, word of mouth, and trucking industry press contacts. A total of 595 individuals completed the survey. Of these, 55.9% were positive on the Berlin, 78.3% had either hypertension or obesity, 69.6% were obese, 47.6% had a BMI > 33 kg/m(2), and 20.5% reported falling asleep at stoplights. Some commercial drivers willingly assess their OSA risk anonymously online, and a majority of those who do so are obese, have positive Berlin screening questionnaires, and would be required to undergo polysomnography if recommendations made to the FMCSA became regulation. In contrast to reported behavior during actual Commercial Driver Medical Examinations physicals, some commercial drivers will report OSA symptoms if it is "safe" to do so. Sleep health professionals need expedient, non-punitive methods to keep commercial motor vehicle drivers healthy and driving and to raise drivers' awareness of the dangers of drowsy driving and unhealthy lifestyles.

Brain Dynamics in Predicting Driving Fatigue Using a Recurrent Self-Evolving Fuzzy Neural Network.

PubMed

Liu, Yu-Ting; Lin, Yang-Yin; Wu, Shang-Lin; Chuang, Chun-Hsiang; Lin, Chin-Teng

2016-02-01

This paper proposes a generalized prediction system called a recurrent self-evolving fuzzy neural network (RSEFNN) that employs an on-line gradient descent learning rule to address the electroencephalography (EEG) regression problem in brain dynamics for driving fatigue. The cognitive states of drivers significantly affect driving safety; in particular, fatigue driving, or drowsy driving, endangers both the individual and the public. For this reason, the development of brain-computer interfaces (BCIs) that can identify drowsy driving states is a crucial and urgent topic of study. Many EEG-based BCIs have been developed as artificial auxiliary systems for use in various practical applications because of the benefits of measuring EEG signals. In the literature, the efficacy of EEG-based BCIs in recognition tasks has been limited by low resolutions. The system proposed in this paper represents the first attempt to use the recurrent fuzzy neural network (RFNN) architecture to increase adaptability in realistic EEG applications to overcome this bottleneck. This paper further analyzes brain dynamics in a simulated car driving task in a virtual-reality environment. The proposed RSEFNN model is evaluated using the generalized cross-subject approach, and the results indicate that the RSEFNN is superior to competing models regardless of the use of recurrent or nonrecurrent structures.

Stationary gaze entropy predicts lane departure events in sleep-deprived drivers.

PubMed

Shiferaw, Brook A; Downey, Luke A; Westlake, Justine; Stevens, Bronwyn; Rajaratnam, Shantha M W; Berlowitz, David J; Swann, Phillip; Howard, Mark E

2018-02-02

Performance decrement associated with sleep deprivation is a leading contributor to traffic accidents and fatalities. While current research has focused on eye blink parameters as physiological indicators of driver drowsiness, little is understood of how gaze behaviour alters as a result of sleep deprivation. In particular, the effect of sleep deprivation on gaze entropy has not been previously examined. In this randomised, repeated measures study, 9 (4 male, 5 female) healthy participants completed two driving sessions in a fully instrumented vehicle (1 after a night of sleep deprivation and 1 after normal sleep) on a closed track, during which eye movement activity and lane departure events were recorded. Following sleep deprivation, the rate of fixations reduced while blink rate and duration as well as saccade amplitude increased. In addition, stationary and transition entropy of gaze also increased following sleep deprivation as well as with amount of time driven. An increase in stationary gaze entropy in particular was associated with higher odds of a lane departure event occurrence. These results highlight how fatigue induced by sleep deprivation and time-on-task effects can impair drivers' visual awareness through disruption of gaze distribution and scanning patterns.

Highway driving safety the day after using sleep medication: the direction of lapses and excursions out-of-lane in drowsy drivers.

PubMed

Verster, Joris C; Mooren, Loes; Bervoets, Adriana C; Roth, Thomas

2017-10-24

The primary outcome measure of the on-road driving test is the Standard Deviation of Lateral Position. However, other outcome measures, such as lapses and excursions out-of-lane, also need to be considered as they may be related to crash risk. The aim of this study was to determine the direction of lapses and excursions out-of-lane (i.e. towards/into the adjacent traffic lane or towards/into the road shoulder). In total, data from 240 driving tests were re-analysed, and 628 lapses and 401 excursions out-of-lane were identified. The analyses revealed that lapses were made equally frequently over left (49.4%) and over right (43.3%). In contrast, excursions out-of-lane were almost exclusively directed over right into the (safer) road shoulder (97.3%). These findings suggest that drivers are unaware of having lapses, whereas excursions out-of-lane are events where the driver is aware of loss of vehicle control. © 2017 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.

Impact of Modafinil Add-on with Atypical Anti-psychotics on Excessive Daytime Drowsiness

PubMed Central

Prasuna, P Lakshmi; Sudhakar, TP

2015-01-01

Background: Atypical antipsychotic drugs are known to cause many side effects which include daytime drowsiness. So many add on drugs are tried to reduce the same. Materials and Methods: 72 patients who were on atypical antipsychotic drugs were randomly assigned to either Modafinil or placebo and were followed for a period of 12 weeks. Daytime drowsiness, was taken at baseline, week 3, and at week 12 by using VAS, EDD scales. Results: The results were analyzed and showed that the Modafinil add on therapy significantly reduced the daytime Drowsiness. Conclusions: Modafinil could be a potential candidate in selected group of patients to decrease some of the unwanted adverse events like daytime drowsiness produced by atypical antipsychotics. PMID:26702168

Road accidents caused by drivers falling asleep.

PubMed

Sagberg, F

1999-11-01

About 29600 Norwegian accident-involved drivers received a questionnaire about the last accident reported to their insurance company. About 9200 drivers (31%) returned the questionnaire. The questionnaire contained questions about sleep or fatigue as contributing factors to the accident. In addition, the drivers reported whether or not they had fallen asleep some time whilst driving. and what the consequences had been. Sleep or drowsiness was a contributing factor in 3.9% of all accidents, as reported by drivers who were at fault for the accident. This factor was strongly over-represented in night-time accidents (18.6%), in running-off-the-road accidents (8.3%), accidents after driving more than 150 km on one trip (8.1%), and personal injury accidents (7.3%). A logistic regression analysis showed that the following additional factors made significant and independent contributions to increasing the odds of sleep involvement in an accident: dry road, high speed limit, driving one's own car, not driving the car daily, high education, and few years of driving experience. More male than female drivers were involved in sleep-related accidents, but this seems largely to be explained by males driving relatively more than females on roads with high speed limits. A total of 10% of male drivers and 4% of females reported to have fallen asleep while driving during the last 12 months. A total of 4% of these events resulted in an accident. The most frequent consequence of falling asleep--amounting to more than 40% of the reported incidents--was crossing of the right edge-line before awaking, whereas crossing of the centreline was reported by 16%. Drivers' lack of awareness of important precursors of falling asleep--like highway hypnosis, driving without awareness, and similar phenomena--as well as a reluctance to discontinue driving despite feeling tired are pointed out as likely contributors to sleep-related accidents. More knowledge about the drivers' experiences immediately preceding such accidents may give a better background for implementing effective driver warning systems and other countermeasures.

Evaluation of reaction time performance and subjective drowsiness during whole-body vibration exposure

NASA Astrophysics Data System (ADS)

Azizan, A.; Zali, Z.; Padil, H.

2018-05-01

Despite the automotive industry’s interest in how vibration affects the level of human comfort, there is little focus on the effect of vibration on drowsiness level. Thus, this study involves eighteen healthy male participants to study the effect of exposure to vibration on the drowsiness level. Prior to the experiment, the total transmitted vibration measured at interfaces between the seat pan and seat back to the human body for each participant was modified to become 0.2 ms-2 r.m.s and 0.4 ms-2 r.m.s. During the experiment, the participants were seated and exposed to 20-minutes of Gaussian random vibration with frequency band 1-15 Hz at two level of amplitude (low vibration amplitude and medium vibration amplitude) on separate days. The level of drowsiness was measured using a PVT test prior and after exposure to the vibration while participants rated their subjective drowsiness by using the Karolinska Sleepiness Scale (KSS). The significant increase in the number of lapse and reaction time because of the exposure to vibration in both conditions provide strong evidence of drowsiness. In this regard, the medium vibration amplitude shows a more prominent effect. All participants have shown a steady increase of drowsiness level in KSS. Meanwhile, there are no significant differences found between low vibration amplitude and medium vibration amplitude in the KSS. These findings suggest that human alertness level is greatly affected by the exposure to vibration and these effects are more pronounced at higher vibration amplitude. Both findings indicate that the presence of vibration promotes drowsiness, especially at higher vibration amplitude.

Risk factors for automobile accidents caused by falling asleep while driving in obstructive sleep apnea syndrome.

PubMed

Arita, Aki; Sasanabe, Ryujiro; Hasegawa, Rika; Nomura, Atsuhiko; Hori, Reiko; Mano, Mamiko; Konishi, Noriyuki; Shiomi, Toshiaki

2015-12-01

We examined the risk factors for automobile accidents caused by falling asleep while driving in subjects with obstructive sleep apnea syndrome (OSAS). We asked licensed drivers with history of snoring and excessive daytime sleepiness who had undergone polysomnography (PSG) at the Department of Sleep Medicine/Sleep Disorders Center at Aichi Medical University Hospital to complete the questionnaires on accidents caused by falling asleep while driving. As a subjective measure of sleepiness, we used the Epworth sleepiness scale (ESS). Based on PSG results, 2387 subjects diagnosed with OSAS were divided into three groups according to apnea-hypopnea index (AHI): mild-to-moderate (5 ≤ AHI < 30), severe (30 ≤ AHI < 60), and very severe (AHI ≥ 60). We performed univariate and multivariate logistic regression on variables that might explain falling asleep at the wheel. We compared results between each group and simple snorers (394 subjects with AHI < 5) and found the group with very severe OSAS reported significantly higher rates of driving when drowsy and having accidents in the past 5 years due to falling asleep. Our multivariate analysis suggests that scores on the ESS and patient-reported frequency of feeling drowsy while regular driving and working are related to automobile accidents caused by falling asleep while driving.

Can arousing feedback rectify lapses in driving? Prediction from EEG power spectra.

PubMed

Lin, Chin-Teng; Huang, Kuan-Chih; Chuang, Chun-Hsiang; Ko, Li-Wei; Jung, Tzyy-Ping

2013-10-01

This study explores the neurophysiological changes, measured using an electroencephalogram (EEG), in response to an arousing warning signal delivered to drowsy drivers, and predicts the efficacy of the feedback based on changes in the EEG. Eleven healthy subjects participated in sustained-attention driving experiments. The driving task required participants to maintain their cruising position and compensate for randomly induced lane deviations using the steering wheel, while their EEG and driving performance were continuously monitored. The arousing warning signal was delivered to participants who experienced momentary behavioral lapses, failing to respond rapidly to lane-departure events (specifically the reaction time exceeded three times the alert reaction time). The results of our previous studies revealed that arousing feedback immediately reversed deteriorating driving performance, which was accompanied by concurrent EEG theta- and alpha-power suppression in the bilateral occipital areas. This study further proposes a feedback efficacy assessment system to accurately estimate the efficacy of arousing warning signals delivered to drowsy participants by monitoring the changes in their EEG power spectra immediately thereafter. The classification accuracy was up 77.8% for determining the need for triggering additional warning signals. The findings of this study, in conjunction with previous studies on EEG correlates of behavioral lapses, might lead to a practical closed-loop system to predict, monitor and rectify behavioral lapses of human operators in attention-critical settings.

Fusing Multiple Sensor Modalities for Complex Physiological State Monitoring

DTIC Science & Technology

2012-12-01

sleep-alpha variants (drowsiness alpha activity and REM -alpha bursts) over frontal, central, parietal and occipital regions. Note the higher spectral...contribution of the slowest components (7.8–8.6 Hz) during REM alpha bursts as compared with drowsiness-alpha activity (13...occipital regions of the brain during the drowsiness state as compared to REM sleep and other states, as seen in figure 1 (13). Furthermore, using EEG

Associating crash avoidance maneuvers with driver attributes and accident characteristics: a mixed logit model approach.

PubMed

Kaplan, Sigal; Prato, Carlo Giacomo

2012-01-01

The current study focuses on the propensity of drivers to engage in crash avoidance maneuvers in relation to driver attributes, critical events, crash characteristics, vehicles involved, road characteristics, and environmental conditions. The importance of avoidance maneuvers derives from the key role of proactive and state-aware road users within the concept of sustainable safety systems, as well as from the key role of effective corrective maneuvers in the success of automated in-vehicle warning and driver assistance systems. The analysis is conducted by means of a mixed logit model that represents the selection among 5 emergency lateral and speed control maneuvers (i.e., "no avoidance maneuvers," "braking," "steering," "braking and steering," and "other maneuvers) while accommodating correlations across maneuvers and heteroscedasticity. Data for the analysis were retrieved from the General Estimates System (GES) crash database for the year 2009 by considering drivers for which crash avoidance maneuvers are known. The results show that (1) the nature of the critical event that made the crash imminent greatly influences the choice of crash avoidance maneuvers, (2) women and elderly have a relatively lower propensity to conduct crash avoidance maneuvers, (3) drowsiness and fatigue have a greater negative marginal effect on the tendency to engage in crash avoidance maneuvers than alcohol and drug consumption, (4) difficult road conditions increase the propensity to perform crash avoidance maneuvers, and (5) visual obstruction and artificial illumination decrease the probability to carry out crash avoidance maneuvers. The results emphasize the need for public awareness campaigns to promote safe driving style for senior drivers and warning about the risks of driving under fatigue and distraction being comparable to the risks of driving under the influence of alcohol and drugs. Moreover, the results suggest the need to educate drivers about hazard perception, designing a forgiving infrastructure within a sustainable safety systems, and rethinking in-vehicle collision warning systems. Future research should address the effectiveness of crash avoidance maneuvers and joint modeling of maneuver selection and crash severity.

Drowsiness

MedlinePlus

... of your drowsiness. Alternative Names Sleepiness - during the day; Hypersomnia; Somnolence References Chokroverty S, Avidan AY. Sleep and its disorders. In: Daroff RB, Jankovic J, Mazziotta JC, Pomeroy SL, eds. Bradley's Neurology in ...

Sopite syndrome - A sometimes sole manifestation of motion sickness. [drowsiness in rotating environment

NASA Technical Reports Server (NTRS)

Graybiel, A.; Knepton, J.

1976-01-01

Sopite syndrome is understood to mean a symptom complex centering around 'drowsiness' produced by motion sickness. The typical symptoms of the syndrome are: yawning; drowsiness; disinclination to work either physically or mentally; and lack of participation in group activities. The present study is based on data obtained in rotating rooms, at sea, in the air, and in orbital flight. When the sopite syndrom occurs either before other typical symptoms of motion sickness appear or after their disappearance, they are distinguished, respectively, by the terms 'early sopite syndrome' and 'late sopite syndrome'. Further distinction is made between brief and prolonged exposures. Evidence is presented indicating that drowsiness and mental depression caused by prolonged motion sickness are only part of the symptom complex that is termed sopite syndrome.

Helmet-based physiological signal monitoring system.

PubMed

Kim, Youn Sung; Baek, Hyun Jae; Kim, Jung Soo; Lee, Haet Bit; Choi, Jong Min; Park, Kwang Suk

2009-02-01

A helmet-based system that was able to monitor the drowsiness of a soldier was developed. The helmet system monitored the electrocardiogram, electrooculogram and electroencephalogram (alpha waves) without constraints. Six dry electrodes were mounted at five locations on the helmet: both temporal sides, forehead region and upper and lower jaw strips. The electrodes were connected to an amplifier that transferred signals to a laptop computer via Bluetooth wireless communication. The system was validated by comparing the signal quality with conventional recording methods. Data were acquired from three healthy male volunteers for 12 min twice a day whilst they were sitting in a chair wearing the sensor-installed helmet. Experimental results showed that physiological signals for the helmet user were measured with acceptable quality without any intrusions on physical activities. The helmet system discriminated between the alert and drowsiness states by detecting blinking and heart rate variability (HRV) parameters extracted from ECG. Blinking duration and eye reopening time were increased during the sleepiness state compared to the alert state. Also, positive peak values of the sleepiness state were much higher, and the negative peaks were much lower than that of the alert state. The LF/HF ratio also decreased during drowsiness. This study shows the feasibility for using this helmet system: the subjects' health status and mental states could be monitored without constraints whilst they were working.

Effects of vibration on occupant driving performance under simulated driving conditions.

PubMed

Azizan, Amzar; Fard, M; Azari, Michael F; Jazar, Reza

2017-04-01

Although much research has been devoted to the characterization of the effects of whole-body vibration on seated occupants' comfort, drowsiness induced by vibration has received less attention to date. There are also little validated measurement methods available to quantify whole body vibration-induced drowsiness. Here, the effects of vibration on drowsiness were investigated. Twenty male volunteers were recruited for this experiment. Drowsiness was measured in a driving simulator, before and after 30-min exposure to vibration. Gaussian random vibration, with 1-15 Hz frequency bandwidth was used for excitation. During the driving session, volunteers were required to obey the speed limit of 100 kph and maintain a steady position on the left-hand lane. A deviation in lane position, steering angle variability, and speed deviation were recorded and analysed. Alternatively, volunteers rated their subjective drowsiness by Karolinska Sleepiness Scale (KSS) scores every 5-min. Following 30-min of exposure to vibration, a significant increase of lane deviation, steering angle variability, and KSS scores were observed in all volunteers suggesting the adverse effects of vibration on human alertness level. Copyright © 2016 Elsevier Ltd. All rights reserved.

Drowsy driving and automobile crashes

DOT National Transportation Integrated Search

1998-04-01

Drowsy driving is a serious problem that leads to : thousands of automobile crashes each year. This : report, sponsored by the National Center on : Sleep Disorders Research (NCSDR) of the National : Heart, Lung, and Blood Institute of the : National ...

Drowsy driving and automobile crashes : report and recommendations.

DOT National Transportation Integrated Search

2013-08-01

Drowsy driving is a serious problem that leads to thousands of automobile crashes each year. This report, sponsored by the National Center on Sleep Disorders Research (NCSDR) of the National Heart, Lung, and Blood Institute of the National Institutes...

Drowsy Driving

MedlinePlus

... Ford ES, Croft JB. Drowsy driving and risk behaviors—10 states and Puerto Rico, 2011-2012. MMWR Morb Mortal Wkly Rep . 2014; 63:557-562. Available at http://www.cdc.gov/mmwr/pdf/wk/mm6326.pdf . Jackson ML, Croft RJ, Kennedy GA, Owens K, Howard ME. Cognitive components of simulated ...

Evaluation of blue light exposure to beta brainwaves on simulated night driving

NASA Astrophysics Data System (ADS)

Purawijaya, Dandri Aly; Fitri, Lulu Lusianti; Suprijanto

2015-09-01

Numbers of night driving accident in Indonesia since 2010 are exponentially rising each year with total of loss more than 50 billion rupiah. One of the causes that contribute to night driving accident is drowsiness. Drowsiness is affected by circadian rhythm resulted from the difference of blue light quality and quantity between night and day. Blue light may effect on human physiology through non-visual pathway by suppressing melatonin hormone suppression that influence drowsiness. Meanwhile, the production of hormones and other activities in brain generate bioelectrical activity such as brainwaves and can be recorded using Electroencephalograph (EEG). Therefore, this research objective is to evaluate the effect of blue light exposure to beta brainwave emergence during night driving simulation to a driver. This research was conducted to 4 male subjects who are able to drive and have a legitimate car driving license. The driving simulator was done using SCANIA Truck Driving Simulator on freeform driving mode in dark environment. Subjects drove for total 32 minutes. The data collections were taken in 2 days with 16 minutes for each day. The 16 minutes were divided again into 8 minutes adaptation in dark and 8 minutes for driving either in blue light exposure or in total darkness. While driving the simulation, subjects' brainwaves were recorded using EEG EMOTIV 14 Channels, exposed by LED monochromatic blue light with 160 Lux from source and angle 45o and sat 1 m in front of the screen. Channels used on this research were for visual (O1; O2), cognition (F3; F4; P7; P8), and motor (FC5; FC6). EEG brainwave result was filtered with EEGLab to obtain beta waves at 13 - 30 Hz frequencies. Results showed that beta waves response to blue light varied for each subject. Blue light exposure either increased or decreased beta waves in 2 minutes pattern and maintaining beta waves on cognition and motor area in 3 out of 4 subjects. Meanwhile, blue light exposure did not maintain and induce beta waves fluctuation on visual area of another 2 subjects. The conclusion of this research is that blue light exposure affected the pattern of beta waves on frontal, parietal, premotor cortex and visual lobes.

78 FR 17123 - Amitraz; Pesticide Tolerances

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-20

... inhalation routes of exposure. Further, it is not a skin or eye irritant, nor is it a skin sensitizer..., neurotoxic effects such as dry mouth, drowsiness, decreased temperature, and bradycardia were seen within 90... mg/ subjects. LOAEL = 0.25 mg/kg/day FQPA SF = UFDB = 10x kg/day. based on dry mouth, drowsiness...

Objective assessment of drowsiness and reaction time during intermittent Ramadan fasting in young men: a case-crossover study

PubMed Central

2013-01-01

Background Ramadan fasting and its attendant lifestyle changes induce changes in the circadian rhythm and in associated physiological and metabolic functions. Previous studies that have assessed psychomotor performance during Ramadan fasting have reported conflicting results. Therefore, we designed this study to objectively assess the effects of intermittent fasting during and outside Ramadan (to control for lifestyle changes) on drowsiness, blink total duration and mean reaction time (MRT) test while controlling for potential confounders. Methods Eight healthy volunteers with a mean age of 25.3 ± 2.9 years and a mean body mass index (BMI) of 23.4 ± 3.2 kg/m2 reported to the sleep laboratory on four occasions for polysomnography (PSG) and drowsiness and psychomotor assessments as follows: 1) adaptation; 2) 4 weeks before Ramadan while performing the Islamic fasting for 1 week (baseline fasting) (BLF); 3) 1 week before Ramadan (non-fasting baseline) (BL); and 4) during the second week of Ramadan while fasting (Ramadan). OPTALERT™ was used to objectively assess daytime drowsiness using the Johns Drowsiness Scale (JDS), and blink total duration and a visual reaction time test were used to assess MRT. Results Rapid eye movement (REM) sleep percentage was significantly lower at BLF (17.7 ± 8.1%) and at Ramadan (18.6 ± 10.7%) compared with BL (25.6 ± 4.8%) (p < 0.05). There were no significant differences between JDS scores and blink total duration during the two test periods in BL, BLF and Ramadan. There were no significant changes in MRT during BL, BLF and Ramadan. Conclusions Under controlled conditions of fixed light/dark exposure, caloric intake, sleep/wake schedule and sleep quality, the Islamic intermittent fasting has no impact on drowsiness and vigilance as measured by the JDS, total blink duration and MRT. PMID:23937904

Objective assessment of drowsiness and reaction time during intermittent Ramadan fasting in young men: a case-crossover study.

PubMed

Bahammam, Ahmed S; Nashwan, Samar; Hammad, Omeima; Sharif, Munir M; Pandi-Perumal, Seithikurippu R

2013-08-12

Ramadan fasting and its attendant lifestyle changes induce changes in the circadian rhythm and in associated physiological and metabolic functions. Previous studies that have assessed psychomotor performance during Ramadan fasting have reported conflicting results. Therefore, we designed this study to objectively assess the effects of intermittent fasting during and outside Ramadan (to control for lifestyle changes) on drowsiness, blink total duration and mean reaction time (MRT) test while controlling for potential confounders. Eight healthy volunteers with a mean age of 25.3 ± 2.9 years and a mean body mass index (BMI) of 23.4 ± 3.2 kg/m2 reported to the sleep laboratory on four occasions for polysomnography (PSG) and drowsiness and psychomotor assessments as follows: 1) adaptation; 2) 4 weeks before Ramadan while performing the Islamic fasting for 1 week (baseline fasting) (BLF); 3) 1 week before Ramadan (non-fasting baseline) (BL); and 4) during the second week of Ramadan while fasting (Ramadan). OPTALERT™ was used to objectively assess daytime drowsiness using the Johns Drowsiness Scale (JDS), and blink total duration and a visual reaction time test were used to assess MRT. Rapid eye movement (REM) sleep percentage was significantly lower at BLF (17.7 ± 8.1%) and at Ramadan (18.6 ± 10.7%) compared with BL (25.6 ± 4.8%) (p < 0.05). There were no significant differences between JDS scores and blink total duration during the two test periods in BL, BLF and Ramadan. There were no significant changes in MRT during BL, BLF and Ramadan. Under controlled conditions of fixed light/dark exposure, caloric intake, sleep/wake schedule and sleep quality, the Islamic intermittent fasting has no impact on drowsiness and vigilance as measured by the JDS, total blink duration and MRT.

Low-cost EEG-based sleep detection.

PubMed

Van Hal, Bryan; Rhodes, Samhita; Dunne, Bruce; Bossemeyer, Robert

2014-01-01

A real-time stage 1 sleep detection system using a low-cost single dry-sensor EEG headset is described. This device issues an auditory warning at the onset of stage 1 sleep using the "NeuroSky Mindset," an inexpensive commercial entertainment-based headset. The EEG signal is filtered into low/high alpha and low/high beta frequency bands which are analyzed to indicate the onset of sleep. Preliminary results indicate an 81% effective rate of detecting sleep with all failures being false positives of sleep onset. This device was able to predict and respond to the onset of drowsiness preceding stage 1 sleep allowing for earlier warnings with the result of fewer sleep-related accidents.

Sleepiness at the wheel across Europe: a survey of 19 countries.

PubMed

Gonçalves, Marta; Amici, Roberto; Lucas, Raquel; Åkerstedt, Torbjörn; Cirignotta, Fabio; Horne, Jim; Léger, Damien; McNicholas, Walter T; Partinen, Markku; Téran-Santos, Joaquín; Peigneux, Philippe; Grote, Ludger

2015-06-01

The European Sleep Research Society aimed to estimate the prevalence, determinants and consequences of falling asleep at the wheel. In total, 12 434 questionnaires were obtained from 19 countries using an anonymous online questionnaire that collected demographic and sleep-related data, driving behaviour, history of drowsy driving and accidents. Associations were quantified using multivariate logistic regression. The average prevalence of falling asleep at the wheel in the previous 2 years was 17%. Among respondents who fell asleep, the median prevalence of sleep-related accidents was 7.0% (13.2% involved hospital care and 3.6% caused fatalities). The most frequently perceived reasons for falling asleep at the wheel were poor sleep in the previous night (42.5%) and poor sleeping habits in general (34.1%). Falling asleep was more frequent in the Netherlands [odds ratio = 3.55 (95% confidence interval: 1.97; 6.39)] and Austria [2.34 (1.75; 3.13)], followed by Belgium [1.52 (1.28; 1.81)], Portugal [1.34 (1.13, 1.58)], Poland [1.22 (1.06; 1.40)] and France [1.20 (1.05; 1.38)]. Lower odds were found in Croatia [0.36 (0.21; 0.61)], Slovenia [0.62 (0.43; 0.89)] and Italy [0.65 (0.53; 0.79)]. Individual determinants of falling asleep were younger age; male gender [1.79 (1.61; 2.00)]; driving ≥20 000 km year [2.02 (1.74; 2.35)]; higher daytime sleepiness [7.49 (6.26; 8.95)] and high risk of obstructive sleep apnea syndrome [3.48 (2.78; 4.36) in men]. This Pan European survey demonstrates that drowsy driving is a major safety hazard throughout Europe. It emphasizes the importance of joint research and policy efforts to reduce the burden of sleepiness at the wheel for European drivers.

Intrusions of a drowsy mind: neural markers of phenomenological unpredictability.

PubMed

Noreika, Valdas; Canales-Johnson, Andrés; Koh, Justin; Taylor, Mae; Massey, Irving; Bekinschtein, Tristan A

2015-01-01

The transition from a relaxed to a drowsy state of mind is often accompanied by hypnagogic experiences: most commonly, perceptual imagery, but also linguistic intrusions, i.e., the sudden emergence of unpredictable anomalies in the stream of inner speech. This study has sought to describe the contents of such intrusions, to verify their association with the progression of sleep onset, and to investigate the electroencephalographic processes associated with linguistic intrusions as opposed to more common hypnagogic perceptual imagery. A single participant attended 10 experimental sessions in the EEG laboratory, where he was allowed to drift into a drowsy state of mind, while maintaining metacognition of his own experiences. Once a linguistic intrusion or a noticeable perceptual image occurred, the participant pressed a button and reported it verbally. An increase in the EEG-defined depth of drowsiness as assessed by the Hori system of sleep onset was observed in the last 20 s before a button press. Likewise, EEG Dimension of Activation values decreased before the button press, indicating that the occurrence of cognitively incongruous experiences coincides with the rapid change of EEG predictability patterns. EEG hemispheric asymmetry analysis showed that linguistic intrusions had a higher alpha and gamma power in the left hemisphere electrodes, whereas perceptual imagery reports were associated with a higher beta power over the right hemisphere. These findings indicate that the modality as well as the incongruence of drowsiness-related hypnagogic experiences is strongly associated with distinct EEG signatures in this participant. Sleep onset may provide a unique possibility to study the neural mechanisms accompanying the fragmentation of the stream of consciousness in healthy individuals.

Intrusions of a drowsy mind: neural markers of phenomenological unpredictability

PubMed Central

Noreika, Valdas; Canales-Johnson, Andrés; Koh, Justin; Taylor, Mae; Massey, Irving; Bekinschtein, Tristan A.

2015-01-01

The transition from a relaxed to a drowsy state of mind is often accompanied by hypnagogic experiences: most commonly, perceptual imagery, but also linguistic intrusions, i.e., the sudden emergence of unpredictable anomalies in the stream of inner speech. This study has sought to describe the contents of such intrusions, to verify their association with the progression of sleep onset, and to investigate the electroencephalographic processes associated with linguistic intrusions as opposed to more common hypnagogic perceptual imagery. A single participant attended 10 experimental sessions in the EEG laboratory, where he was allowed to drift into a drowsy state of mind, while maintaining metacognition of his own experiences. Once a linguistic intrusion or a noticeable perceptual image occurred, the participant pressed a button and reported it verbally. An increase in the EEG-defined depth of drowsiness as assessed by the Hori system of sleep onset was observed in the last 20 s before a button press. Likewise, EEG Dimension of Activation values decreased before the button press, indicating that the occurrence of cognitively incongruous experiences coincides with the rapid change of EEG predictability patterns. EEG hemispheric asymmetry analysis showed that linguistic intrusions had a higher alpha and gamma power in the left hemisphere electrodes, whereas perceptual imagery reports were associated with a higher beta power over the right hemisphere. These findings indicate that the modality as well as the incongruence of drowsiness-related hypnagogic experiences is strongly associated with distinct EEG signatures in this participant. Sleep onset may provide a unique possibility to study the neural mechanisms accompanying the fragmentation of the stream of consciousness in healthy individuals. PMID:25814962

Not in My Navy. A Legal Guide to Drug Abuse.

DTIC Science & Technology

1984-06-01

opiates produces drowsiness, sleep, and a reduction in physical activity. Side effects can include nausea and vomiting, constipation, itching, flushing...diarrhea, pallor, and dilation of the pupils. Such effects are generally seen only with high doses or as occasional side effects with therapeutic doses...that will produce low-level side effects . or, a person might be drowsy from ingesting a nonprescription product - such as an antihistamine. A clue to

iLid: Low-power Sensing of Fatigue and Drowsiness Measures on a Computational Eyeglass

PubMed Central

ROSTAMINIA, SOHA; MAYBERRY, ADDISON; GANESAN, DEEPAK; MARLIN, BENJAMIN; GUMMESON, JEREMY

2018-01-01

The ability to monitor eye closures and blink patterns has long been known to enable accurate assessment of fatigue and drowsiness in individuals. Many measures of the eye are known to be correlated with fatigue including coarse-grained measures like the rate of blinks as well as fine-grained measures like the duration of blinks and the extent of eye closures. Despite a plethora of research validating these measures, we lack wearable devices that can continually and reliably monitor them in the natural environment. In this work, we present a low-power system, iLid, that can continually sense fine-grained measures such as blink duration and Percentage of Eye Closures (PERCLOS) at high frame rates of 100fps. We present a complete solution including design of the sensing, signal processing, and machine learning pipeline; implementation on a prototype computational eyeglass platform; and extensive evaluation under many conditions including illumination changes, eyeglass shifts, and mobility. Our results are very encouraging, showing that we can detect blinks, blink duration, eyelid location, and fatigue-related metrics such as PERCLOS with less than a few percent error. PMID:29417956

Driver fatigue detection based on eye state.

PubMed

Lin, Lizong; Huang, Chao; Ni, Xiaopeng; Wang, Jiawen; Zhang, Hao; Li, Xiao; Qian, Zhiqin

2015-01-01

Nowadays, more and more traffic accidents occur because of driver fatigue. In order to reduce and prevent it, in this study, a calculation method using PERCLOS (percentage of eye closure time) parameter characteristics based on machine vision was developed. It determined whether a driver's eyes were in a fatigue state according to the PERCLOS value. The overall workflow solutions included face detection and tracking, detection and location of the human eye, human eye tracking, eye state recognition, and driver fatigue testing. The key aspects of the detection system incorporated the detection and location of human eyes and driver fatigue testing. The simplified method of measuring the PERCLOS value of the driver was to calculate the ratio of the eyes being open and closed with the total number of frames for a given period. If the eyes were closed more than the set threshold in the total number of frames, the system would alert the driver. Through many experiments, it was shown that besides the simple detection algorithm, the rapid computing speed, and the high detection and recognition accuracies of the system, the system was demonstrated to be in accord with the real-time requirements of a driver fatigue detection system.

Developing and evaluating a mobile driver fatigue detection network based on electroencephalograph signals

PubMed Central

Yin, Jinghai; Mu, Zhendong

2016-01-01

The rapid development of driver fatigue detection technology indicates important significance of traffic safety. The authors’ main goals of this Letter are principally three: (i) A middleware architecture, defined as process unit (PU), which can communicate with personal electroencephalography (EEG) node (PEN) and cloud server (CS). The PU receives EEG signals from PEN, recognises the fatigue state of the driver, and transfer this information to CS. The CS sends notification messages to the surrounding vehicles. (ii) An android application for fatigue detection is built. The application can be used for the driver to detect the state of his/her fatigue based on EEG signals, and warn neighbourhood vehicles. (iii) The detection algorithm for driver fatigue is applied based on fuzzy entropy. The idea of 10-fold cross-validation and support vector machine are used for classified calculation. Experimental results show that the average accurate rate of detecting driver fatigue is about 95%, which implying that the algorithm is validity in detecting state of driver fatigue. PMID:28529761

Developing and evaluating a mobile driver fatigue detection network based on electroencephalograph signals.

PubMed

Yin, Jinghai; Hu, Jianfeng; Mu, Zhendong

2017-02-01

The rapid development of driver fatigue detection technology indicates important significance of traffic safety. The authors' main goals of this Letter are principally three: (i) A middleware architecture, defined as process unit (PU), which can communicate with personal electroencephalography (EEG) node (PEN) and cloud server (CS). The PU receives EEG signals from PEN, recognises the fatigue state of the driver, and transfer this information to CS. The CS sends notification messages to the surrounding vehicles. (ii) An android application for fatigue detection is built. The application can be used for the driver to detect the state of his/her fatigue based on EEG signals, and warn neighbourhood vehicles. (iii) The detection algorithm for driver fatigue is applied based on fuzzy entropy. The idea of 10-fold cross-validation and support vector machine are used for classified calculation. Experimental results show that the average accurate rate of detecting driver fatigue is about 95%, which implying that the algorithm is validity in detecting state of driver fatigue.

The Case for Addressing Operator Fatigue

PubMed Central

Duffy, Jeanne F.; Zitting, Kirsi-Marja; Czeisler, Charles A.

2015-01-01

Sleep deficiency, which can be caused by acute sleep deprivation, chronic insufficient sleep, untreated sleep disorders, disruption of circadian timing, and other factors, is endemic in the U.S., including among professional and non-professional drivers and operators. Vigilance and attention are critical for safe transportation operations, but fatigue and sleepiness compromise vigilance and attention by slowing reaction times and impairing judgment and decision-making abilities. Research studies, polls, and accident investigations indicate that many Americans drive a motor vehicle or operate an aircraft, train or marine vessel while drowsy, putting themselves and others at risk for error and accident. In this chapter, we will outline some of the factors that contribute to sleepiness, present evidence from laboratory and field studies demonstrating how sleepiness impacts transportation safety, review how sleepiness is measured in laboratory and field settings, describe what is known about interventions for sleepiness in transportation settings, and summarize what we believe are important gaps in our knowledge of sleepiness and transportation safety. PMID:26056516

Antihistamines in drivers, aircrew and occupations of risk.

PubMed

Jáuregui, I; Ferrer, M; Montoro, J; Dávila, I; Bartra, J; del Cuvillo, A; Mullol, J; Sastre, J; Valero, A

2013-01-01

The most commonly occurring allergic diseases can involve a daytime drowsiness associated with the condition itself. The antihistamines used in their treatment can also have central effects and affect certain occupations concerned with risk, road safety and maritime and air navigation. Cognitive tests, experimental studies and epidemiological data recommend avoiding 1st generation antihistamines for people who must drive regularly and/or professions concerned with safety. Although there are no comparative studies on real driving between 1st and 2nd generation antihistamines, in this type of patients there should be a preference for prescribing those with least possible central effect, especially those which are a good substrate for transmembrane transporter pumps such as P-glycoprotein and therefore have a low capacity for crossing the hematoencephalic barrier, thus allowing a broader window for therapy. In this sense, bilastine is a good P-glycoprotein substrate and shows good tolerance at CNS level, in both psychometric trials and real driving test protocols, even at double the dose recommended in the technical file.

Drivers' and non-drivers' performance in a change detection task with static driving scenes: is there a benefit of experience?

PubMed

Zhao, Nan; Chen, Wenfeng; Xuan, Yuming; Mehler, Bruce; Reimer, Bryan; Fu, Xiaolan

2014-01-01

The 'looked-but-failed-to-see' phenomenon is crucial to driving safety. Previous research utilising change detection tasks related to driving has reported inconsistent effects of driver experience on the ability to detect changes in static driving scenes. Reviewing these conflicting results, we suggest that drivers' increased ability to detect changes will only appear when the task requires a pattern of visual attention distribution typical of actual driving. By adding a distant fixation point on the road image, we developed a modified change blindness paradigm and measured detection performance of drivers and non-drivers. Drivers performed better than non-drivers only in scenes with a fixation point. Furthermore, experience effect interacted with the location of the change and the relevance of the change to driving. These results suggest that learning associated with driving experience reflects increased skill in the efficient distribution of visual attention across both the central focus area and peripheral objects. This article provides an explanation for the previously conflicting reports of driving experience effects in change detection tasks. We observed a measurable benefit of experience in static driving scenes, using a modified change blindness paradigm. These results have translational opportunities for picture-based training and testing tools to improve driver skill.

Monitoring alert and drowsy states by modeling EEG source nonstationarity

NASA Astrophysics Data System (ADS)

Hsu, Sheng-Hsiou; Jung, Tzyy-Ping

2017-10-01

Objective. As a human brain performs various cognitive functions within ever-changing environments, states of the brain characterized by recorded brain activities such as electroencephalogram (EEG) are inevitably nonstationary. The challenges of analyzing the nonstationary EEG signals include finding neurocognitive sources that underlie different brain states and using EEG data to quantitatively assess the state changes. Approach. This study hypothesizes that brain activities under different states, e.g. levels of alertness, can be modeled as distinct compositions of statistically independent sources using independent component analysis (ICA). This study presents a framework to quantitatively assess the EEG source nonstationarity and estimate levels of alertness. The framework was tested against EEG data collected from 10 subjects performing a sustained-attention task in a driving simulator. Main results. Empirical results illustrate that EEG signals under alert versus drowsy states, indexed by reaction speeds to driving challenges, can be characterized by distinct ICA models. By quantifying the goodness-of-fit of each ICA model to the EEG data using the model deviation index (MDI), we found that MDIs were significantly correlated with the reaction speeds (r  =  -0.390 with alertness models and r  =  0.449 with drowsiness models) and the opposite correlations indicated that the two models accounted for sources in the alert and drowsy states, respectively. Based on the observed source nonstationarity, this study also proposes an online framework using a subject-specific ICA model trained with an initial (alert) state to track the level of alertness. For classification of alert against drowsy states, the proposed online framework achieved an averaged area-under-curve of 0.745 and compared favorably with a classic power-based approach. Significance. This ICA-based framework provides a new way to study changes of brain states and can be applied to monitoring cognitive or mental states of human operators in attention-critical settings or in passive brain-computer interfaces.

Screening for delirium with the Intensive Care Delirium Screening Checklist (ICDSC): Symptom profile and utility of individual items in the identification of delirium dependent on the level of sedation.

PubMed

Boettger, Soenke; Meyer, Rafael; Richter, André; Fernandez, Susana Franco; Rudiger, Alain; Schubert, Maria; Jenewein, Josef; Nuñez, David Garcia

2018-05-24

The importance of the proper identification of delirium, with its high incidence and adversities in the intensive care setting, has been widely recognized. One common screening instrument is the Intensive Care Delirium Screening Checklist (ICDSC); however, the symptom profile and key features of delirium dependent on the level of sedation have not yet been evaluated. In this prospective cohort study, the ICDSC was evaluated versus the Diagnostic and Statistical Manual, 4th edition, text revision, diagnosis of delirium set as standard with respect to the symptom profile, and correct identification of delirium. The aim of this study was to identify key features of delirium in the intensive care setting dependent on the Richmond Agitation and Sedation Scale levels of sedation: drowsiness versus alert and calmness.ResultThe 88 delirious patients of 225 were older, had more severe disease, and prolonged hospitalization. Irrespective of the level of sedation, delirium was correctly classified by items related to inattention, disorientation, psychomotor alterations, inappropriate speech or mood, and symptom fluctuation. In the drowsy patients, inattention reached substantial sensitivity and specificity, whereas psychomotor alterations and sleep-wake cycle disturbances were sensitive lacked specificity. The positive prediction was substantial across items, whereas the negative prediction was only moderate. In the alert and calm patient, the sensitivities were substantial for psychomotor alterations, sleep-wake cycle disturbances, and symptom fluctuations; however, these fluctuations were not specific. The positive prediction was moderate and the negative prediction substantial. Between the nondelirious drowsy and alert, the symptom profile was similar; however, drowsiness was associated with alterations in consciousness.Significance of resultsIn the clinical routine, irrespective of the level of sedation, delirium was characterized by the ICDSC items for inattention, disorientation, psychomotor alterations, inappropriate speech or mood and symptom fluctuation. Further, drowsiness caused altered levels of consciousness.

Long-term retention of a divided attention psycho-motor test combining choice reaction test and postural balance test: A preliminary study.

PubMed

Rossi, R; Pascolo, P B

2015-09-01

Driving in degraded psychophysical conditions, such as under the influence of alcohol or drugs but also in a state of fatigue or drowsiness, is a growing problem. The current roadside tests used for detecting drugs from drivers suffer various limitations, while impairment is subjective and does not necessarily correlate with drug metabolite concentration found in body fluids. This work is a validation step towards the study of feasibility of a novel test conceived to assess psychophysical conditions of individuals performing at-risk activities. Motor gestures, long-term retention and learning phase related to the protocol are analysed in unimpaired subjects. The protocol is a divided attention test, which combines a critical tracking test achieved with postural movements and a visual choice reaction test. Ten healthy subjects participated in a first set of trials and in a second set after about six months. Each session required the carrying out of the test for ten times in order to investigate learning effect and performance over repetitions. In the first set the subjects showed a learning trend up to the third trial, whilst in the second set of trials they showed motor retention. Nevertheless, the overall performance did not significantly improve. Gestures are probably retained due to the type of tasks and the way in which the instructions are conveyed to the subjects. Moreover, motor retention after a short training suggests that the protocol is easy to learn and understand. Implications for roadside test usage and comparison with current tests are also discussed. Copyright © 2015 Elsevier Ltd. All rights reserved.

32 CFR 634.36 - Detection, apprehension, and testing of intoxicated drivers.

Code of Federal Regulations, 2011 CFR

2011-07-01

... THE ARMY (CONTINUED) LAW ENFORCEMENT AND CRIMINAL INVESTIGATIONS MOTOR VEHICLE TRAFFIC SUPERVISION Traffic Supervision § 634.36 Detection, apprehension, and testing of intoxicated drivers. (a) Law enforcement personnel usually detect drivers under the influence of alcohol or other drugs by observing...

32 CFR 634.36 - Detection, apprehension, and testing of intoxicated drivers.

Code of Federal Regulations, 2010 CFR

2010-07-01

... THE ARMY (CONTINUED) LAW ENFORCEMENT AND CRIMINAL INVESTIGATIONS MOTOR VEHICLE TRAFFIC SUPERVISION Traffic Supervision § 634.36 Detection, apprehension, and testing of intoxicated drivers. (a) Law enforcement personnel usually detect drivers under the influence of alcohol or other drugs by observing...

Early driver fatigue detection from electroencephalography signals using artificial neural networks.

PubMed

King, L M; Nguyen, H T; Lal, S K L

2006-01-01

This paper describes a driver fatigue detection system using an artificial neural network (ANN). Using electroencephalogram (EEG) data sampled from 20 professional truck drivers and 35 non professional drivers, the time domain data are processed into alpha, beta, delta and theta bands and then presented to the neural network to detect the onset of driver fatigue. The neural network uses a training optimization technique called the magnified gradient function (MGF). This technique reduces the time required for training by modifying the standard back propagation (SBP) algorithm. The MGF is shown to classify professional driver fatigue with 81.49% accuracy (80.53% sensitivity, 82.44% specificity) and non-professional driver fatigue with 83.06% accuracy (84.04% sensitivity and 82.08% specificity).

Adaptive Response Criteria in Road Hazard Detection Among Older Drivers

PubMed Central

Feng, Jing; Choi, HeeSun; Craik, Fergus I. M.; Levine, Brian; Moreno, Sylvain; Naglie, Gary; Zhu, Motao

2018-01-01

OBJECTIVES The majority of existing investigations on attention, aging, and driving have focused on the negative impacts of age-related declines in attention on hazard detection and driver performance. However, driving skills and behavioral compensation may accommodate the negative effects that age-related attentional decline places on driving performance. In this study, we examined an important question that had been largely neglected in the literature linking attention, aging, and driving: can top-down factors such as behavioral compensation, specifically adaptive response criteria, accommodate the negative impacts from age-related attention declines on hazard detection during driving? METHODS In the experiment, we used the Drive Aware Task, a task combining the driving context with well-controlled laboratory procedures measuring attention. We compared younger (n = 16, age 21 – 30) and older drivers (n = 21, age 65 – 79) on their attentional processing of hazards in driving scenes, indexed by percentage of correct and reaction time of hazard detection, as well as sensitivity and response criterion using the signal detection analysis. RESULTS Older drivers, in general, were less accurate and slower on the task than younger drivers. However, results from this experiment also revealed that older, but not younger, drivers adapted their response criteria when the traffic condition changed in the driving scenes. When there was more traffic in the driving scene, older drivers became more liberal in their responses, meaning that they were more likely to report that a driving hazard was detected. CONCLUSIONS Older drivers adopt compensatory strategies on hazard detection during driving . Our findings showed that, in the driving context, even at an old age our attentional functions are still adaptive according to environmental conditions. This leads to considerations on potential training methods to promote adaptive strategies which may help older drivers maintaining performance in road hazard detection. PMID:28898116

Convolutional Neural Network-Based Classification of Driver's Emotion during Aggressive and Smooth Driving Using Multi-Modal Camera Sensors.

PubMed

Lee, Kwan Woo; Yoon, Hyo Sik; Song, Jong Min; Park, Kang Ryoung

2018-03-23

Because aggressive driving often causes large-scale loss of life and property, techniques for advance detection of adverse driver emotional states have become important for the prevention of aggressive driving behaviors. Previous studies have primarily focused on systems for detecting aggressive driver emotion via smart-phone accelerometers and gyro-sensors, or they focused on methods of detecting physiological signals using electroencephalography (EEG) or electrocardiogram (ECG) sensors. Because EEG and ECG sensors cause discomfort to drivers and can be detached from the driver's body, it becomes difficult to focus on bio-signals to determine their emotional state. Gyro-sensors and accelerometers depend on the performance of GPS receivers and cannot be used in areas where GPS signals are blocked. Moreover, if driving on a mountain road with many quick turns, a driver's emotional state can easily be misrecognized as that of an aggressive driver. To resolve these problems, we propose a convolutional neural network (CNN)-based method of detecting emotion to identify aggressive driving using input images of the driver's face, obtained using near-infrared (NIR) light and thermal camera sensors. In this research, we conducted an experiment using our own database, which provides a high classification accuracy for detecting driver emotion leading to either aggressive or smooth (i.e., relaxed) driving. Our proposed method demonstrates better performance than existing methods.

Research on driver fatigue detection

NASA Astrophysics Data System (ADS)

Zhang, Ting; Chen, Zhong; Ouyang, Chao

2018-03-01

Driver fatigue is one of the main causes of frequent traffic accidents. In this case, driver fatigue detection system has very important significance in avoiding traffic accidents. This paper presents a real-time method based on fusion of multiple facial features, including eye closure, yawn and head movement. The eye state is classified as being open or closed by a linear SVM classifier trained using HOG features of the detected eye. The mouth state is determined according to the width-height ratio of the mouth. The head movement is detected by head pitch angle calculated by facial landmark. The driver's fatigue state can be reasoned by the model trained by above features. According to experimental results, drive fatigue detection obtains an excellent performance. It indicates that the developed method is valuable for the application of avoiding traffic accidents caused by driver's fatigue.

Analysis of Braking Behavior of Train Drivers to Detect Unusual Driving

NASA Astrophysics Data System (ADS)

Marumo, Yoshitaka; Tsunashima, Hitoshi; Kojima, Takashi; Hasegawa, Yasushi

The safety devices for train systems are activated in emergency situations when a risk becomes obvious, and the emergency brake is applied. If such systems are faulty, the drivers' operating errors may cause immediate accidents. So it is necessary to evaluate potential risks by detecting improper driving behavior before overt risks appear. This study analyzes the driving behavior of train drivers using a train-driving simulator. We focus on braking behavior when approaching a station. Two methods for detecting unusual braking operation are examined by giving drivers mental calculation problems as a mental workload. The first is a method monitoring the driver's brake handle operation, and the second is a method measuring vehicle deceleration. These methods make it possible to detect unusual driving.

Automatic Fatigue Detection of Drivers through Yawning Analysis

NASA Astrophysics Data System (ADS)

Azim, Tayyaba; Jaffar, M. Arfan; Ramzan, M.; Mirza, Anwar M.

This paper presents a non-intrusive fatigue detection system based on the video analysis of drivers. The focus of the paper is on how to detect yawning which is an important cue for determining driver's fatigue. Initially, the face is located through Viola-Jones face detection method in a video frame. Then, a mouth window is extracted from the face region, in which lips are searched through spatial fuzzy c-means (s-FCM) clustering. The degree of mouth openness is extracted on the basis of mouth features, to determine driver's yawning state. If the yawning state of the driver persists for several consecutive frames, the system concludes that the driver is non-vigilant due to fatigue and is thus warned through an alarm. The system reinitializes when occlusion or misdetection occurs. Experiments were carried out using real data, recorded in day and night lighting conditions, and with users belonging to different race and gender.

Drivers of Emerging Infectious Disease Events as a Framework for Digital Detection.

PubMed

Olson, Sarah H; Benedum, Corey M; Mekaru, Sumiko R; Preston, Nicholas D; Mazet, Jonna A K; Joly, Damien O; Brownstein, John S

2015-08-01

The growing field of digital disease detection, or epidemic intelligence, attempts to improve timely detection and awareness of infectious disease (ID) events. Early detection remains an important priority; thus, the next frontier for ID surveillance is to improve the recognition and monitoring of drivers (antecedent conditions) of ID emergence for signals that precede disease events. These data could help alert public health officials to indicators of elevated ID risk, thereby triggering targeted active surveillance and interventions. We believe that ID emergence risks can be anticipated through surveillance of their drivers, just as successful warning systems of climate-based, meteorologically sensitive diseases are supported by improved temperature and precipitation data. We present approaches to driver surveillance, gaps in the current literature, and a scientific framework for the creation of a digital warning system. Fulfilling the promise of driver surveillance will require concerted action to expand the collection of appropriate digital driver data.

Association of sleep habits with accidents and near misses in United States transportation operators.

PubMed

Johnson, Kevin D; Patel, Sanjay R; Baur, Dorothee M; Edens, Edward; Sherry, Patrick; Malhotra, Atul; Kales, Stefanos N

2014-05-01

To explore sleep risk factors and their association with adverse events in transportation operators. Self-reported sleep-related behaviors were analyzed in transportation operators (drivers, pilots, and rail operators) aged 26 to 78 years who completed the National Sleep Foundation's 2012 "Planes, Trains, Automobiles, and Sleep" survey. Regression analyses were used to assess the associations of various sleep-related variables with the combined outcome of self-reported accidents and near misses. Age- and body mass-adjusted predictors of accidents/near misses included an accident while commuting (odds ratio [OR] = 4.6; confidence interval [CI], 2.1 to 9.8), driving drowsy (OR = 4.1; CI, 2.5 to 6.7), and Sheehan Disability Scale score greater than 15 (OR = 3.5; CI, 2.2 to 5.5). Sleeping more than 7 hours nightly was protective for accident/near misses (OR = 0.6; CI, 0.4 to 0.9). Recognized risk factors for poor sleep or excessive daytime sleepiness were significantly associated with self-reported near misses and/or accidents in transportation operators.

Association of Sleep Habits With Accidents and Near Misses in United States Transportation Operators

PubMed Central

Johnson, Kevin D.; Patel, Sanjay R.; Baur, Dorothee M.; Edens, Edward; Sherry, Patrick; Malhotra, Atul; Kales, Stefanos N.

2015-01-01

Objective To explore sleep risk factors and their association with adverse events in transportation operators. Methods Self-reported sleep-related behaviors were analyzed in transportation operators (drivers, pilots, and rail operators) aged 26 to 78 years who completed the National Sleep Foundation’s 2012 “Planes, Trains, Automobiles, and Sleep” survey. Regression analyses were used to assess the associations of various sleep-related variables with the combined outcome of self-reported accidents and near misses. Results Age- and body mass–adjusted predictors of accidents/near misses included an accident while commuting (odds ratio [OR] = 4.6; confidence interval [CI], 2.1 to 9.8), driving drowsy (OR = 4.1; CI, 2.5 to 6.7), and Sheehan Disability Scale score greater than 15 (OR = 3.5; CI, 2.2 to 5.5). Sleeping more than 7 hours nightly was protective for accident/near misses (OR = 0.6; CI, 0.4 to 0.9). Conclusion Recognized risk factors for poor sleep or excessive daytime sleepiness were significantly associated with self-reported near misses and/or accidents in transportation operators. PMID:24806564

Automatic Recognition of Road Signs

NASA Astrophysics Data System (ADS)

Inoue, Yasuo; Kohashi, Yuuichirou; Ishikawa, Naoto; Nakajima, Masato

2002-11-01

The increase in traffic accidents is becoming a serious social problem with the recent rapid traffic increase. In many cases, the driver"s carelessness is the primary factor of traffic accidents, and the driver assistance system is demanded for supporting driver"s safety. In this research, we propose the new method of automatic detection and recognition of road signs by image processing. The purpose of this research is to prevent accidents caused by driver"s carelessness, and call attention to a driver when the driver violates traffic a regulation. In this research, high accuracy and the efficient sign detecting method are realized by removing unnecessary information except for a road sign from an image, and detect a road sign using shape features. At first, the color information that is not used in road signs is removed from an image. Next, edges except for circular and triangle ones are removed to choose sign shape. In the recognition process, normalized cross correlation operation is carried out to the two-dimensional differentiation pattern of a sign, and the accurate and efficient method for detecting the road sign is realized. Moreover, the real-time operation in a software base was realized by holding down calculation cost, maintaining highly precise sign detection and recognition. Specifically, it becomes specifically possible to process by 0.1 sec(s)/frame using a general-purpose PC (CPU: Pentium4 1.7GHz). As a result of in-vehicle experimentation, our system could process on real time and has confirmed that detection and recognition of a sign could be performed correctly.

EEG quantification of alertness: methods for early identification of individuals most susceptible to sleep deprivation

NASA Astrophysics Data System (ADS)

Berka, Chris; Levendowski, Daniel J.; Westbrook, Philip; Davis, Gene; Lumicao, Michelle N.; Olmstead, Richard E.; Popovic, Miodrag; Zivkovic, Vladimir T.; Ramsey, Caitlin K.

2005-05-01

Electroencephalographic (EEG) and neurocognitive measures were simultaneously acquired to quantify alertness from 24 participants during 44-hours of sleep deprivation. Performance on a three-choice vigilance task (3C-VT), paired-associate learning/memory task (PAL) and modified Maintenance of Wakefulness Test (MWT), and sleep technician-observed drowsiness (eye-closures, head-nods, EEG slowing) were quantified. The B-Alert system automatically classifies each second of EEG on an alertness/drowsiness continuum. B-Alert classifications were significantly correlated with technician-observations, visually scored EEG and performance measures. B-Alert classifications during 3C-VT, and technician observations and performance during the 3C-VT and PAL evidenced progressively increasing drowsiness as a result of sleep deprivation with a stabilizing effect observed at the batteries occurring between 0600 and 1100 suggesting a possible circadian effect similar to those reported in previous sleep deprivation studies. Participants were given an opportunity to take a 40-minute nap approximately 24-hours into the sleep deprivation portion of the study (i.e., 7 PM on Saturday). The nap was followed by a transient period of increased alertness. Approximately 8 hours after the nap, behavioral and physiological measures of drowsiness returned to levels prior to the nap. Cluster analysis was used to stratify individuals into three groups based on their level of impairment as a result of sleep deprivation. The combination of B-Alert and neuro-behavioral measures may identify individuals whose performance is most susceptible to sleep deprivation. These objective measures could be applied in an operational setting to provide a "biobehavioral assay" to determine vulnerability to sleep deprivation.

Topographic distribution of EEG alpha attractor correlation dimension values in wake and drowsy states in humans.

PubMed

Kalauzi, Aleksandar; Vuckovic, Aleksandra; Bojić, Tijana

2015-03-01

Organization of resting state cortical networks is of fundamental importance for the phenomenon of awareness, which is altered in the first part of hypnagogic period (Hori stages 1-4). Our aim was to investigate the change in brain topography pattern of EEG alpha attractor correlation dimension (CD) in the period of transition from Hori stage 1 to 4. EEG of ten healthy adult individuals was recorded in the wake and drowsy states, using a 14 channel average reference montage, from which 91 bipolar channels were derived and filtered in the wider alpha (6-14 Hz) range. Sixty 1s long epochs of each state and individual were subjected to CD calculation according to the Grassberger-Procaccia method. For such a collection of signals, two embedding dimensions, d={5, 10}, and 22 time delays τ=2-23 samples were explored. Optimal values were d=10 and τ=18, where both saturation and second zero crossing of the autocorrelation function occurred. Bipolar channel CD underwent a significant decrease during the transition and showed a positive linear correlation with electrode distance, stronger in the wake individuals. Topographic distribution of bipolar channels with above median CD changed from longitudinal anterior-posterior pattern (awake) to a more diagonal pattern, with localization in posterior regions (drowsiness). Our data are in line with the literature reporting functional segregation of neuronal assemblies in anterior and posterior regions during this transition. Our results should contribute to understanding of complex reorganization of the cortical part of alpha generators during the wake/drowsy transition. Copyright © 2014 Elsevier B.V. All rights reserved.

Single-channel EEG-based mental fatigue detection based on deep belief network.

PubMed

Pinyi Li; Wenhui Jiang; Fei Su

2016-08-01

Mental fatigue has a pernicious influence on road and work place safety as well as a negative symptom of many acute and chronic illnesses, since the ability of concentrating, responding and judging quickly decreases during the fatigue or drowsiness stage. Electroencephalography (EEG) has been proven to be a robust physiological indicator of human cognitive state over the last few decades. But most existing EEG-based fatigue detection methods have poor performance in accuracy. This paper proposed a single-channel EEG-based mental fatigue detection method based on Deep Belief Network (DBN). The fused nonliear features from specified sub-bands and dynamic analysis, a total of 21 features are extracted as the input of the DBN to discriminate three classes of mental state including alert, slight fatigue and severe fatigue. Experimental results show the good performance of the proposed model comparing with those state-of-art methods.

Psychophysiological effects of self-regulation method: EEG frequency analysis and contingent negative variations.

PubMed

Ikemi, A

1988-01-01

Experiments were conducted to investigate the psychophysiological effects of self-regulation method (SRM), a newly developed method of self-control, using EEG frequency analysis and contingent negative variations (CNV). The results of the EEG frequency analysis showed that there is a significant increase in the percentage (power) of the theta-band and a significant decrease in the percentage (power) of the beta-band during SRM. Moreover, the results of an identical experiment conducted on subjects in a drowsy state showed that the changes in EEG frequencies during SRM can be differentiated from those of a drowsy state. Furthermore, experiments using CNV showed that there is a significant reduction of CNV amplitude during SRM. Despite the reduced amplitude during SRM, the number of errors in a task to evoke the CNV was reduced significantly without significant delay of reaction time. When an identical experiment was conducted in a drowsy state, CNV amplitude was reduced significantly, but reaction time and errors increased. From these experiments, the state of vigilance during SRM was discussed as a state of 'relaxed alertness'.

Wearable sensor glove based on conducting fabric using electrodermal activity and pulse-wave sensors for e-health application.

PubMed

Lee, Youngbum; Lee, Byungwoo; Lee, Myoungho

2010-03-01

Improvement of the quality and efficiency of health in medicine, both at home and the hospital, calls for improved sensors that might be included in a common carrier such as a wearable sensor device to measure various biosignals and provide healthcare services that use e-health technology. Designed to be user-friendly, smart clothes and gloves respond well to the end users for health monitoring. This study describes a wearable sensor glove that is equipped with an electrodermal activity (EDA) sensor, pulse-wave sensor, conducting fabric, and an embedded system. The EDA sensor utilizes the relationship between drowsiness and the EDA signal. The EDA sensors were made using a conducting fabric instead of silver chloride electrodes, as a more practical and practically wearable device. The pulse-wave sensor measurement system, which is widely applied in oriental medicinal practices, is also a strong element in e-health monitoring systems. The EDA and pulse-wave signal acquisition module was constructed by connecting the sensor to the glove via a conductive fabric. The signal acquisition module is then connected to a personal computer that displays the results of the EDA and pulse-wave signal processing analysis and gives accurate feedback to the user. This system is designed for a number of applications for the e-health services, including drowsiness detection and oriental medicine.

Segmentation method of eye region based on fuzzy logic system for classifying open and closed eyes

NASA Astrophysics Data System (ADS)

Kim, Ki Wan; Lee, Won Oh; Kim, Yeong Gon; Hong, Hyung Gil; Lee, Eui Chul; Park, Kang Ryoung

2015-03-01

The classification of eye openness and closure has been researched in various fields, e.g., driver drowsiness detection, physiological status analysis, and eye fatigue measurement. For a classification with high accuracy, accurate segmentation of the eye region is required. Most previous research used the segmentation method by image binarization on the basis that the eyeball is darker than skin, but the performance of this approach is frequently affected by thick eyelashes or shadows around the eye. Thus, we propose a fuzzy-based method for classifying eye openness and closure. First, the proposed method uses I and K color information from the HSI and CMYK color spaces, respectively, for eye segmentation. Second, the eye region is binarized using the fuzzy logic system based on I and K inputs, which is less affected by eyelashes and shadows around the eye. The combined image of I and K pixels is obtained through the fuzzy logic system. Third, in order to reflect the effect by all the inference values on calculating the output score of the fuzzy system, we use the revised weighted average method, where all the rectangular regions by all the inference values are considered for calculating the output score. Fourth, the classification of eye openness or closure is successfully made by the proposed fuzzy-based method with eye images of low resolution which are captured in the environment of people watching TV at a distance. By using the fuzzy logic system, our method does not require the additional procedure of training irrespective of the chosen database. Experimental results with two databases of eye images show that our method is superior to previous approaches.

An application of signal detection theory for understanding driver behavior at highway-rail grade crossings

DOT National Transportation Integrated Search

2009-10-19

We used signal detection theory to examine if grade crossing warning devices were effective because they increased drivers' sensitivity to a train's approach or because they encouraged drivers to stop. We estimated d' and a for eight warning devices ...

Passive in-vehicle driver breath alcohol detection using advanced sensor signal acquisition and fusion.

PubMed

Ljungblad, Jonas; Hök, Bertil; Allalou, Amin; Pettersson, Håkan

2017-05-29

The research objective of the present investigation is to demonstrate the present status of passive in-vehicle driver breath alcohol detection and highlight the necessary conditions for large-scale implementation of such a system. Completely passive detection has remained a challenge mainly because of the requirements on signal resolution combined with the constraints of vehicle integration. The work is part of the Driver Alcohol Detection System for Safety (DADSS) program aiming at massive deployment of alcohol sensing systems that could potentially save thousands of American lives annually. The work reported here builds on earlier investigations, in which it has been shown that detection of alcohol vapor in the proximity of a human subject may be traced to that subject by means of simultaneous recording of carbon dioxide (CO 2 ) at the same location. Sensors based on infrared spectroscopy were developed to detect and quantify low concentrations of alcohol and CO 2 . In the present investigation, alcohol and CO 2 were recorded at various locations in a vehicle cabin while human subjects were performing normal in-step procedures and driving preparations. A video camera directed to the driver position was recording images of the driver's upper body parts, including the face, and the images were analyzed with respect to features of significance to the breathing behavior and breath detection, such as mouth opening and head direction. Improvement of the sensor system with respect to signal resolution including algorithm and software development, and fusion of the sensor and camera signals was successfully implemented and tested before starting the human study. In addition, experimental tests and simulations were performed with the purpose of connecting human subject data with repeatable experimental conditions. The results include occurrence statistics of detected breaths by signal peaks of CO 2 and alcohol. From the statistical data, the accuracy of breath alcohol estimation and timing related to initial driver routines (door opening, taking a seat, door closure, buckling up, etc.) can be estimated. The investigation confirmed the feasibility of passive driver breath alcohol detection using our present system. Trade-offs between timing and sensor signal resolution requirements will become critical. Further improvement of sensor resolution and system ruggedness is required before the results can be industrialized. It is concluded that a further important step toward completely passive detection of driver breath alcohol has been taken. If required, the sniffer function with alcohol detection capability can be combined with a subsequent highly accurate breath test to confirm the driver's legal status using the same sensor device. The study is relevant to crash avoidance, in particular driver monitoring systems and driver-vehicle interface design.

Sleep Disorders Associated With Mild Traumatic Brain Injury Using Sport Concussion Assessment Tool 3.

PubMed

Tkachenko, Nataliya; Singh, Kanwaljit; Hasanaj, Lisena; Serrano, Liliana; Kothare, Sanjeev V

2016-04-01

Sleep problems affect 30% to 80% of patients with mild traumatic brain injury. We assessed the prevalence of sleep disorders after mild traumatic brain injury and its correlation with other symptoms. Individuals with mild traumatic brain injury were assessed at the New York University Concussion Center during 2013-2014 with the Sports Concussion Assessment Tool, third edition, data following mild traumatic brain injury. The relationship between sleep problems (drowsiness, difficulty falling asleep, fatigue or low energy), psychiatric symptoms (sadness, nervousness or anxiousness), headache, and dizziness were analyzed by Spearman correlation and logistic regression using moderate to severe versus none to mild categorization. Ninety-three patients were retrospectively considered. The most common injury causes were falls (34.4%) and motor vehicle accidents (21.5%). There was a positive correlation between dizziness, headache, psychiatric problems (sadness, anxiety, irritability), and sleep problems (fatigue, drowsiness, and difficulty falling asleep) (P < 0.001). Logistic regression showed a significant association between moderate to severe psychiatric symptoms and moderate to severe sleep symptoms (P < 0.05). Sleep symptoms became more severe with increased time interval from mild traumatic brain injury to Sport Concussion Assessment Tool 3 administration (odds ratio = 1.005, 1.006, and 1.008, P < 0.05). There was significant correlation between motor vehicle accident and drowsiness and difficulty falling asleep (P < 0.05). Medications given in the emergency department had a positive correlation with drowsiness (P < 0.05). Individuals who report moderate to severe headache, dizziness, and psychiatric symptoms have a higher likelihood of reporting moderate to severe sleep disorders following mild traumatic brain injury and should be counseled and initiated with early interventions. Copyright © 2016 Elsevier Inc. All rights reserved.

Driver gene classification reveals a substantial overrepresentation of tumor suppressors among very large chromatin-regulating proteins.

PubMed

Waks, Zeev; Weissbrod, Omer; Carmeli, Boaz; Norel, Raquel; Utro, Filippo; Goldschmidt, Yaara

2016-12-23

Compiling a comprehensive list of cancer driver genes is imperative for oncology diagnostics and drug development. While driver genes are typically discovered by analysis of tumor genomes, infrequently mutated driver genes often evade detection due to limited sample sizes. Here, we address sample size limitations by integrating tumor genomics data with a wide spectrum of gene-specific properties to search for rare drivers, functionally classify them, and detect features characteristic of driver genes. We show that our approach, CAnceR geNe similarity-based Annotator and Finder (CARNAF), enables detection of potentially novel drivers that eluded over a dozen pan-cancer/multi-tumor type studies. In particular, feature analysis reveals a highly concentrated pool of known and putative tumor suppressors among the <1% of genes that encode very large, chromatin-regulating proteins. Thus, our study highlights the need for deeper characterization of very large, epigenetic regulators in the context of cancer causality.

Driving with hemianopia: IV. Head scanning and detection at intersections in a simulator.

PubMed

Bowers, Alex R; Ananyev, Egor; Mandel, Aaron J; Goldstein, Robert B; Peli, Eli

2014-03-13

Using a driving simulator, we examined the effects of homonymous hemianopia (HH) on head scanning behaviors at intersections and evaluated the role of inadequate head scanning in detection failures. Fourteen people with complete HH and without cognitive decline or visual neglect and 12 normally sighted (NV) current drivers participated. They drove in an urban environment following predetermined routes, which included multiple intersections. Head scanning behaviors were quantified at T-intersections (n = 32) with a stop or yield sign. Participants also performed a pedestrian detection task. The relationship between head scanning and detection was examined at 10 intersections. For HH drivers, the first scan was more likely to be toward the blind than the seeing hemifield. They also made a greater proportion of head scans overall to the blind side than did the NV drivers to the corresponding side (P = 0.003). However, head scan magnitudes of HH drivers were smaller than those of the NV group (P < 0.001). Drivers with HH had impaired detection of blind-side pedestrians due either to not scanning in the direction of the pedestrian or to an insufficient scan magnitude (left HH detected only 46% and right HH 8% at the extreme left and right of the intersection, respectively). Drivers with HH demonstrated compensatory head scan patterns, but not scan magnitudes. Inadequate scanning resulted in blind-side detection failures, which might place HH drivers at increased risk for collisions at intersections. Scanning training tailored to specific problem areas identified in this study might be beneficial.

Reducing impaired-driving recidivism using advanced vehicle-based alcohol detection systems : a report to Congress

DOT National Transportation Integrated Search

2007-12-01

Vehicle-based alcohol detection systems use technologies designed to detect the presence of alcohol in a driver. Technology suitable for use in all vehicles that will detect an impaired driver faces many challenges including public acceptability, pas...

Detecting the high risk driver : the development of a risk questionnaire

DOT National Transportation Integrated Search

1974-01-01

This report describes the development of a driver risk questionnaire that is intended to be used for the identification of accident-prone drivers from problem drivers in general and from alcoholic drivers in particular. A self-administered questionna...

The Effect of reduced transmittance window tinting on drivers' ability to detect targets in their rear-view mirrors : final report.

DOT National Transportation Integrated Search

1996-01-01

This study addressed the degree to which motor vehicle window tint films impede drivers' ability to detect targets in their vehicle's rear-view mirrors. Twenty-four subjects participated. Each sat in the driver's seat of one of four experimental vehi...

Evaluation of sleep profile in schizophrenia patients treated with extended-release paliperidone: an open-label prospective study in Southeast Asia.

PubMed

Kongsakon, Ronnachai; Thavichachart, Nuntika; Chung, Ka Fai; Lim, Leslie; Azucena, Beverly; Rondain, Elizabeth; Go, Benson; Costales, Fe; Nerapusee, Osot

2017-01-01

To evaluate the effect of 6 months of treatment with paliperidone extended-release (ER) tablets on the sleep profile of patients with schizophrenia. A total of 984 patients meeting the The Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria for schizophrenia who switched their antipsychotic to paliperidone ER were recruited from 61 sites in five countries in Southeast Asia. We recorded patient demographics and assessed sleep quality and daytime drowsiness using visual analog scales. Approximately 70% of patients completed the 6-month study. After the use of paliperidone ER, patients reported significantly better sleep quality (76.44 vs 65.48; p <0.001) and less daytime drowsiness compared with their baseline value (23.18 vs 34.22; p <0.001). Factors predicting sleep profile improvement were completion of the study and higher baseline Positive and Negative Syndrome Scale scores. Paliperidone ER can help schizophrenia patients to improve sleep quality and reduce daytime drowsiness; this was seen especially in the patients who completed the 6-month treatment period and had higher baseline Positive and Negative Syndrome Scale scores.

Evaluation of sleep profile in schizophrenia patients treated with extended-release paliperidone: an open-label prospective study in Southeast Asia

PubMed Central

Kongsakon, Ronnachai; Thavichachart, Nuntika; Chung, Ka Fai; Lim, Leslie; Azucena, Beverly; Rondain, Elizabeth; Go, Benson; Costales, Fe; Nerapusee, Osot

2017-01-01

Objective To evaluate the effect of 6 months of treatment with paliperidone extended-release (ER) tablets on the sleep profile of patients with schizophrenia. Methods A total of 984 patients meeting the The Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria for schizophrenia who switched their antipsychotic to paliperidone ER were recruited from 61 sites in five countries in Southeast Asia. We recorded patient demographics and assessed sleep quality and daytime drowsiness using visual analog scales. Results Approximately 70% of patients completed the 6-month study. After the use of paliperidone ER, patients reported significantly better sleep quality (76.44 vs 65.48; p<0.001) and less daytime drowsiness compared with their baseline value (23.18 vs 34.22; p<0.001). Factors predicting sleep profile improvement were completion of the study and higher baseline Positive and Negative Syndrome Scale scores. Conclusion Paliperidone ER can help schizophrenia patients to improve sleep quality and reduce daytime drowsiness; this was seen especially in the patients who completed the 6-month treatment period and had higher baseline Positive and Negative Syndrome Scale scores. PMID:29138607

Discovering potential driver genes through an integrated model of somatic mutation profiles and gene functional information.

PubMed

Xi, Jianing; Wang, Minghui; Li, Ao

2017-09-26

The accumulating availability of next-generation sequencing data offers an opportunity to pinpoint driver genes that are causally implicated in oncogenesis through computational models. Despite previous efforts made regarding this challenging problem, there is still room for improvement in the driver gene identification accuracy. In this paper, we propose a novel integrated approach called IntDriver for prioritizing driver genes. Based on a matrix factorization framework, IntDriver can effectively incorporate functional information from both the interaction network and Gene Ontology similarity, and detect driver genes mutated in different sets of patients at the same time. When evaluated through known benchmarking driver genes, the top ranked genes of our result show highly significant enrichment for the known genes. Meanwhile, IntDriver also detects some known driver genes that are not found by the other competing approaches. When measured by precision, recall and F1 score, the performances of our approach are comparable or increased in comparison to the competing approaches.

Driver fatigue alarm based on eye detection and gaze estimation

NASA Astrophysics Data System (ADS)

Sun, Xinghua; Xu, Lu; Yang, Jingyu

2007-11-01

The driver assistant system has attracted much attention as an essential component of intelligent transportation systems. One task of driver assistant system is to prevent the drivers from fatigue. For the fatigue detection it is natural that the information about eyes should be utilized. The driver fatigue can be divided into two types, one is the sleep with eyes close and another is the sleep with eyes open. Considering that the fatigue detection is related with the prior knowledge and probabilistic statistics, the dynamic Bayesian network is used as the analysis tool to perform the reasoning of fatigue. Two kinds of experiments are performed to verify the system effectiveness, one is based on the video got from the laboratory and another is based on the video got from the real driving situation. Ten persons participate in the test and the experimental result is that, in the laboratory all the fatigue events can be detected, and in the practical vehicle the detection ratio is about 85%. Experiments show that in most of situations the proposed system works and the corresponding performance is satisfying.

The problem of suspended and revoked drivers who avoid detection at checkpoints.

PubMed

Parrish, Kelly E; Masten, Scott V

2015-01-01

Although driver license suspension and revocation have been shown to improve traffic safety, suspended or revoked (SR) drivers who continue to drive-which appears to be the majority-are about 3 times more likely to be involved in crashes and to cause a fatal crash. In California and many other U.S. states, drivers are typically mailed notices requesting that they surrender their licenses when they are SR for reasons other than driving under the influence of alcohol or drugs (DUI), yet they frequently do not comply. Typical procedures at DUI checkpoints in California and other U.S. states include inspecting driver licenses and checking for signs of intoxication during brief contacts with law enforcement officers. Hence, these checkpoints are in fact DUI/license checkpoints in California and many other states. The purpose of this study was to estimate the extent to which SR drivers avoid being detected at DUI/license checkpoints for SR driving, because they illegally retained possession of their license cards. Law enforcement officers used electronic license card readers at DUI/license checkpoints in Sacramento, California, to record data for 13,705 drivers. The SR status of all contacted drivers was determined after the checkpoints and compared to law enforcement citation records from the checkpoints. Although only 3% of the drivers contacted at the checkpoints were SR, about 41% of SR drivers were able to pass through undetected because they presented license cards that they illegally retained. Drivers SR for DUI-related reasons were more likely to be detected, whereas those SR for failure to provide proof of financial responsibility (insurance) were less likely to be detected. The fact that many SR drivers are able to pass through DUI/license checkpoints undetected weakens both the specific and general impacts of checkpoints for deterring SR driving and may diminish the effectiveness of suspension and revocation actions for reducing the crash risk posed by problem drivers. Using license card readers that can quickly identify SR drivers in real time during routine traffic stops and at DUI/license checkpoints warrants further consideration.

Augmented Reality Cues and Elderly Driver Hazard Perception

PubMed Central

Schall, Mark C.; Rusch, Michelle L.; Lee, John D.; Dawson, Jeffrey D.; Thomas, Geb; Aksan, Nazan; Rizzo, Matthew

2013-01-01

Objective Evaluate the effectiveness of augmented reality (AR) cues in improving driving safety in elderly drivers who are at increased crash risk due to cognitive impairments. Background Cognitively challenging driving environments pose a particular crash risk for elderly drivers. AR cueing is a promising technology to mitigate risk by directing driver attention to roadway hazards. This study investigates whether AR cues improve or interfere with hazard perception in elderly drivers with age-related cognitive decline. Methods Twenty elderly (Mean= 73 years, SD= 5 years), licensed drivers with a range of cognitive abilities measured by a speed of processing (SOP) composite participated in a one-hour drive in an interactive, fixed-base driving simulator. Each participant drove through six, straight, six-mile-long rural roadway scenarios following a lead vehicle. AR cues directed attention to potential roadside hazards in three of the scenarios, and the other three were uncued (baseline) drives. Effects of AR cueing were evaluated with respect to: 1) detection of hazardous target objects, 2) interference with detecting nonhazardous secondary objects, and 3) impairment in maintaining safe distance behind a lead vehicle. Results AR cueing improved the detection of hazardous target objects of low visibility. AR cues did not interfere with detection of nonhazardous secondary objects and did not impair ability to maintain safe distance behind a lead vehicle. SOP capacity did not moderate those effects. Conclusion AR cues show promise for improving elderly driver safety by increasing hazard detection likelihood without interfering with other driving tasks such as maintaining safe headway. PMID:23829037

Model driver screening and evaluation program. Volume 2, Maryland pilot older driver study

DOT National Transportation Integrated Search

2003-05-01

This research project studied the feasibility as well as the scientific validity and utility of performing functional capacity screening with older drivers. A Model Program was described encompassing procedures to detect functionally impaired drivers...

Directing driver attention with augmented reality cues

PubMed Central

Rusch, Michelle L.; Schall, Mark C.; Gavin, Patrick; Lee, John D.; Dawson, Jeffrey D.; Vecera, Shaun; Rizzo, Matthew

2013-01-01

This simulator study evaluated the effects of augmented reality (AR) cues designed to direct the attention of experienced drivers to roadside hazards. Twenty-seven healthy middle-aged licensed drivers with a range of attention capacity participated in a 54 mile (1.5 hour) drive in an interactive fixed-base driving simulator. Each participant received AR cues to potential roadside hazards in six simulated straight (9 mile long) rural roadway segments. Drivers were evaluated on response time for detecting a potentially hazardous event, detection accuracy for target (hazard) and non-target objects, and headway with respect to the hazards. Results showed no negative outcomes associated with interference. AR cues did not impair perception of non-target objects, including for drivers with lower attentional capacity. Results showed near significant response time benefits for AR cued hazards. AR cueing increased response rate for detecting pedestrians and warning signs but not vehicles. AR system false alarms and misses did not impair driver responses to potential hazards. PMID:24436635

A Vehicle Active Safety Model: Vehicle Speed Control Based on Driver Vigilance Detection Using Wearable EEG and Sparse Representation.

PubMed

Zhang, Zutao; Luo, Dianyuan; Rasim, Yagubov; Li, Yanjun; Meng, Guanjun; Xu, Jian; Wang, Chunbai

2016-02-19

In this paper, we present a vehicle active safety model for vehicle speed control based on driver vigilance detection using low-cost, comfortable, wearable electroencephalographic (EEG) sensors and sparse representation. The proposed system consists of three main steps, namely wireless wearable EEG collection, driver vigilance detection, and vehicle speed control strategy. First of all, a homemade low-cost comfortable wearable brain-computer interface (BCI) system with eight channels is designed for collecting the driver's EEG signal. Second, wavelet de-noising and down-sample algorithms are utilized to enhance the quality of EEG data, and Fast Fourier Transformation (FFT) is adopted to extract the EEG power spectrum density (PSD). In this step, sparse representation classification combined with k-singular value decomposition (KSVD) is firstly introduced in PSD to estimate the driver's vigilance level. Finally, a novel safety strategy of vehicle speed control, which controls the electronic throttle opening and automatic braking after driver fatigue detection using the above method, is presented to avoid serious collisions and traffic accidents. The simulation and practical testing results demonstrate the feasibility of the vehicle active safety model.

Missing RRI interpolation for HRV analysis using locally-weighted partial least squares regression.

PubMed

Kamata, Keisuke; Fujiwara, Koichi; Yamakawa, Toshiki; Kano, Manabu

2016-08-01

The R-R interval (RRI) fluctuation in electrocardiogram (ECG) is called heart rate variability (HRV). Since HRV reflects autonomic nervous function, HRV-based health monitoring services, such as stress estimation, drowsy driving detection, and epileptic seizure prediction, have been proposed. In these HRV-based health monitoring services, precise R wave detection from ECG is required; however, R waves cannot always be detected due to ECG artifacts. Missing RRI data should be interpolated appropriately for HRV analysis. The present work proposes a missing RRI interpolation method by utilizing using just-in-time (JIT) modeling. The proposed method adopts locally weighted partial least squares (LW-PLS) for RRI interpolation, which is a well-known JIT modeling method used in the filed of process control. The usefulness of the proposed method was demonstrated through a case study of real RRI data collected from healthy persons. The proposed JIT-based interpolation method could improve the interpolation accuracy in comparison with a static interpolation method.

Safety of veralipride for the treatment of vasomotor symptoms of menopause.

PubMed

Valencia, Marcelino Hernández; Arias, María de Jesús Vega; González, Cuauhtémoc Celis; Marín, Imelda Hernández; González, Juan Humberto Martín; Campos, Enrique Rafael Morcate; Rodríguez, María Antonia Basavilvazo; Álvarez, Ignacio Morales; Vargas, María Antonia Valdés; Flores, José Braulio Everardo Otero; Haro, Samuel Santoyo; Bonilla, Manuel Cortes; Escudero, Roberto Bernardo; Campero, Rosalba Alonso

2014-05-01

Veralipride is a nonhormonal option for the treatment of vasomotor symptoms of menopause. Incidence of adverse events in a Mexican population and drug compliance according to correct use were evaluated. We carried out a longitudinal, prospective, and analytical study in Mexican women who received veralipride to treat symptoms of menopause from 2011 to 2012. There were 386 treatment cycles; 272 were assigned to dosing schedule 1, which included 20 days of treatment with 10 days of suspension, and 114 were assigned to dosing schedule 2, which included 5 days of treatment and 2 days of suspension. A total of 57 adverse events were registered during the 386-month treatment. For the 20 × 10 dosing schedule, the highest incidence was observed for anxiety (2.2%), drowsiness, and weakness (1.5%); for the 5 × 2 dosing schedule, the highest incidence was observed for drowsiness (5.3%) and headache (2.6%). The Hamilton Depression Rating Scale was used to assess the presence and severity of depression; improvement was noted. The Unified Parkinson's Disease Rating Scale was used to assess neurological movement disorders; no adverse neurological events were detected. Based on the assessments of both women and physicians, the highest frequency was observed for "very satisfied" (45.5% and 52.3%, respectively), followed by "satisfied" (23.9% and 27.3%, respectively). Both dosing schedules show acceptable safety profiles for up to 6 months of use when used according to the contraindications in the current prescribing information for standard use (2012) and recent medical literature.

Predicting crash-relevant violations at stop sign-controlled intersections for the development of an intersection driver assistance system.

PubMed

Scanlon, John M; Sherony, Rini; Gabler, Hampton C

2016-09-01

Intersection crashes resulted in over 5,000 fatalities in the United States in 2014. Intersection Advanced Driver Assistance Systems (I-ADAS) are active safety systems that seek to help drivers safely traverse intersections. I-ADAS uses onboard sensors to detect oncoming vehicles and, in the event of an imminent crash, can either alert the driver or take autonomous evasive action. The objective of this study was to develop and evaluate a predictive model for detecting whether a stop sign violation was imminent. Passenger vehicle intersection approaches were extracted from a data set of typical driver behavior (100-Car Naturalistic Driving Study) and violations (event data recorders downloaded from real-world crashes) and were assigned weighting factors based on real-world frequency. A k-fold cross-validation procedure was then used to develop and evaluate 3 hypothetical stop sign warning algorithms (i.e., early, intermediate, and delayed) for detecting an impending violation during the intersection approach. Violation detection models were developed using logistic regression models that evaluate likelihood of a violation at various locations along the intersection approach. Two potential indicators of driver intent to stop-that is, required deceleration parameter (RDP) and brake application-were used to develop the predictive models. The earliest violation detection opportunity was then evaluated for each detection algorithm in order to (1) evaluate the violation detection accuracy and (2) compare braking demand versus maximum braking capabilities. A total of 38 violating and 658 nonviolating approaches were used in the analysis. All 3 algorithms were able to detect a violation at some point during the intersection approach. The early detection algorithm, as designed, was able to detect violations earlier than all other algorithms during the intersection approach but gave false alarms for 22.3% of approaches. In contrast, the delayed detection algorithm sacrificed some time for detecting violations but was able to substantially reduce false alarms to only 3.3% of all nonviolating approaches. Given good surface conditions (maximum braking capabilities = 0.8 g) and maximum effort, most drivers (55.3-71.1%) would be able to stop the vehicle regardless of the detection algorithm. However, given poor surface conditions (maximum braking capabilities = 0.4 g), few drivers (10.5-26.3%) would be able to stop the vehicle. Automatic emergency braking (AEB) would allow for early braking prior to driver reaction. If equipped with an AEB system, the results suggest that, even for the poor surface conditions scenario, over one half (55.3-65.8%) of the vehicles could have been stopped. This study demonstrates the potential of I-ADAS to incorporate a stop sign violation detection algorithm. Repeating the analysis on a larger, more extensive data set will allow for the development of a more comprehensive algorithm to further validate the findings.

77 FR 24247 - Privacy Act of 1974; System of Records Notice

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-23

... competence and performance in evaluating the CMV driver health and fitness and to detect irregularities in... CMV driver health and fitness and to detect irregularities in examination procedures. Certified...

[Detection of zopiclone in many drivers--a sign of misuse or abuse].

PubMed

Bramness, J G; Skurtveit, S; Mørland, J

1999-08-20

In 1998 zopiclone had a 42% share of the prescribed hypnotic drug market in Norway. The National Institute of Forensic Toxicology analyses all blood samples from suspected drugged drivers. The rise in zopiclone prescription was partly reflected in an increase in the number of drivers with zopiclone detected in the blood. We looked closer at the test results from 101 drivers with zopiclone detected in their blood in the January 1994 to April 1999 period. 60% had blood concentrations of zopiclone above the concentration observed after intake of therapeutic doses; 80% had higher blood concentrations than those expected 8 hours after intake of therapeutic doses. The majority of the drivers also tested positive for illegal drugs, prescription drugs with abuse potential, or alcohol. This indicates that zopiclone is misused or abused. Therefore the same caution should be applied when prescribing zopiclone as is applied when prescribing e.g. benzodiazepines.

Prevalence of alcohol and drugs among car and van drivers killed in road accidents in Norway: an overview from 2001 to 2010.

PubMed

Christophersen, Asbjørg S; Gjerde, Hallvard

2014-01-01

To examine the prevalence of alcohol and drugs in blood samples collected from car and van drivers killed in traffic accidents in Norway during the time period from 2001 to 2010. Blood samples (n = 676, 63% of all killed drivers) were analyzed for alcohol, psychoactive medications, and illicit drugs. The cutoff limits for positive results were set according to the new legislative limits under the Norwegian Road Traffic Act. The results were assessed in relation to sex and age, time of day and day of week, and single- versus multiple-vehicle and all investigated vehicle accidents. Alcohol or one or more drugs was detected in samples from 40.2 percent of all investigated drivers, with 28.7 percent showing blood concentrations of at least 5 times the legislative limits. For the investigated female drivers, the total prevalence was 24.0 percent. Among the single-vehicle accidents, alcohol or drugs was found in 63.8 percent of the cases, with 49.1 percent showing blood concentrations of at least 5 times the legislative limits. Alcohol was detected in 25.3 and 49.1 percent of samples from all investigated drivers and among drivers killed in single-vehicle accidents, respectively. Psychoactive medications were found in 14.4 and 17.7 percent and illicit drugs in 14.1 and 19.2 percent, respectively. The most commonly detected group of medications was benzodiazepines, and amphetamines and tetrahydrocannabinol were the most commonly detected illicit drugs. The prevalence of alcohol alone was highest among drivers under the age of 25, and the combination of alcohol with other drugs was highest among drivers under the age of 35. Drivers between the ages of 25 and 54 showed the highest prevalence of medications and/or illicit drugs without the presence of alcohol. The highest prevalence of alcohol or drugs was found among drivers killed in single-vehicle accidents on weeknights (83.8%) and on weekend nights (89.3%). The findings confirm that a large number of fatally injured drivers, in particular among drivers involved in single-vehicle accidents, had concentrations of alcohol or drugs above the new legislative limits introduced in 2012. In many cases, concentrations of at least 5 times the limits were found. The proportion of drivers killed who tested positive for alcohol or other drugs did not change during the study period; however, the total number of drivers killed per year decreased by about 20 percent. Some changes were also observed with regard to the types of benzodiazepines and amphetamines detected during the 10-year period.

Survey and comparison of sleep quality among fixed and changing shift staff in a steel factory in Tehran, Iran.

PubMed

Mohammadian, Farugh; Abbasinia, Marzieh; Rahmani, Abdolrasoul; Monazzam, Mohammad Reza; Asghari, Mehdi; Ahmadnezhad, Iman; Asadi, Ali

2013-01-01

Given the hazardous nature of the work in steel factories and that the staff has to deal with hazardous equipment and machines, improper sleep quality and drowsiness among the works tackles performance and boosts rate of job accidents. This study is aimed to survey the quality of sleep and sleepiness status and the pertinent factors among the workers in a rolling mill and a steel production company in Tehran, Iran. In a Cross-Sectional study 2011, 180 workers were selected randomly from a rolling mill and a steel production company in Tehran. A questionnaire was designed to collect demographic data and variables of work condition. Pitersborg's sleep quality questionnaire was used to survey quality and problems of Participants' sleep. Epworth Sleepiness questionnaire was used to deals with sleepiness during work, studying, watching TV, or during time spent in public. Average score of sleep quality for the fixed shift staff and changing shift staff were 7.5±2.82 and 8.49±2.95 respectively. Surveys of sleep quality for the two groups of the participants based on T-test showed a significant difference between the two groups so that the changing shift staff group suffered poorer sleep quality (p=0.03). Comparison of average drowsiness scores between the two groups of participants based on Mann-Whitney test showed no significant difference (p>0.005). Chi square test showed a significant difference between severity of drowsiness and type of working shift (p =0.028 and 0.009). Staff in revolving shifts suffers poor sleep quality comparing with staff with fixed working shift. Moreover, type of working shift greatly affects severity of drowsiness as staff at different work shift experienced different level of sleepiness. It is essential to survey sleep disorder of the staff in the industry and pay more emphasis on sleep disorder epidemic in other fields of industry.

Driver fatigue detection through multiple entropy fusion analysis in an EEG-based system.

PubMed

Min, Jianliang; Wang, Ping; Hu, Jianfeng

2017-01-01

Driver fatigue is an important contributor to road accidents, and fatigue detection has major implications for transportation safety. The aim of this research is to analyze the multiple entropy fusion method and evaluate several channel regions to effectively detect a driver's fatigue state based on electroencephalogram (EEG) records. First, we fused multiple entropies, i.e., spectral entropy, approximate entropy, sample entropy and fuzzy entropy, as features compared with autoregressive (AR) modeling by four classifiers. Second, we captured four significant channel regions according to weight-based electrodes via a simplified channel selection method. Finally, the evaluation model for detecting driver fatigue was established with four classifiers based on the EEG data from four channel regions. Twelve healthy subjects performed continuous simulated driving for 1-2 hours with EEG monitoring on a static simulator. The leave-one-out cross-validation approach obtained an accuracy of 98.3%, a sensitivity of 98.3% and a specificity of 98.2%. The experimental results verified the effectiveness of the proposed method, indicating that the multiple entropy fusion features are significant factors for inferring the fatigue state of a driver.

Detection of new in-path targets by drivers using Stop & Go Adaptive Cruise Control.

PubMed

Stanton, Neville A; Dunoyer, Alain; Leatherland, Adam

2011-05-01

This paper reports on the design and evaluation of in-car displays used to support Stop & Go Adaptive Cruise Control. Stop & Go Adaptive Cruise Control is an extension of Adaptive Cruise Control, as it is able to bring the vehicle to a complete stop. Previous versions of Adaptive Cruise Control have only operated above 26 kph. The greatest concern for these technologies is the appropriateness of the driver's response in any given scenario. Three different driver interfaces were proposed to support the detection of modal, spatial and temporal changes of the system: an iconic display, a flashing iconic display, and a representation of the radar. The results show that drivers correctly identified more changes detected by the system with the radar display than with the other displays, but higher levels of workload accompanied this increased detection. Copyright © 2010 Elsevier Ltd and The Ergonomics Society. All rights reserved.

The sopite syndrome revisited: Drowsiness and mood changes during real or apparent motion

NASA Astrophysics Data System (ADS)

Lawson, B. D.; Mead, A. M.

The sopite syndrome is a poorly understood response to motion. Drowsiness and mood changes are the primary characteristics of the syndrome. The sopite syndrome can exist in isolation from more apparent symptoms such as nausea, can last long; after nausea has subsided, and can debilitate some individuals. It is most likely a distinct syndrome from "regular" motion sickness or common fatigue, and is of potential concern in a variety of situations. The syndrome may be particularly hazardous in transportation settings where other performance challenges (e.g., sleep deprivation) are already present. It is also a potential concern in cases where illnesses such as sleep disorders or depression may interact with the syndrome and confuse diagnosis.

Low conspicuity of motorcycles for car drivers: dominant role of bottom-up control of visual attention or deficit of top-down control?

PubMed

Rogé, Joceline; Douissembekov, Evgueni; Vienne, Fabrice

2012-02-01

The aim of this study was to evaluate whether the low visibility of motorcycles is the result of their low cognitive conspicuity and/or their low sensory conspicuity for car drivers. In several cases of collision between a car and a motorcycle, the car driver failed to detect the motorcyclist in time to avoid the collision. To test the low cognitive conspicuity hypothesis, 42 car drivers (32.02 years old) including 21 motorcyclist motorists and 21 non-motorcyclist motorists carried out a motorcycle detection task in a car-driving simulator.To test the low sensory conspicuity hypothesis, the authors studied the effect of the color contrast between motorcycles and the road surface on the ability of car drivers to detect motorcycles when they appear from different parts of the road. A high level of color contrast enhanced the visibility of motorcycles when they appeared in front of the participants. Moreover, when motorcyclists appeared from behind the participants,the motorcyclist motorists detected oncoming motorcycles at a greater distance than did the non-motorcyclist motorists. Motorcyclist motorists carry out more saccades and rapidly capture information (on their rearview mirrors and on the road in front of them). The results related to the sensory conspicuity and cognitive conspicuity of motorcycles for car drivers are discussed from the viewpoint of visual attention theories. The practical implications of these results and future lines of research related to training methods for car drivers are considered.

What can the drivers' own description from combined sources provide in an analysis of driver distraction and low vigilance in accident situations?

PubMed

Tivesten, Emma; Wiberg, Henrik

2013-03-01

Accident data play an important role in vehicle safety development. Accident data sources are generally limited in terms of how much information is provided on driver states and behaviour prior to an accident. However, the precise limitations vary between databases, due to differences in analysis focus and data collection procedures between organisations. If information about a specific accident can be retrieved from more than one data source it should be possible to combine the available information sets to facilitate data from one source to compensate for limitations in the other(s). To investigate the viability of such compensation, this study identified a set of accidents recorded in two different data sources. The first data source investigated was an accident mail survey and the second data source insurance claims documents consisting predominantly of insurance claims completed by the involved road users. An analysis of survey variables was compared to a case analysis including word data derived from the same survey and filed insurance claims documents. For each accident, the added value of having access to more than one source of information was assessed. To limit the scope of this study, three particular topics were investigated: available information on low vigilance (e.g., being drowsy, ill); secondary task distraction (e.g., talking with passengers, mobile phone use); and distraction related to the driving task (e.g., looking for approaching vehicles). Results suggest that for low vigilance and secondary task distraction, a combination of the mail survey and insurance claims documents provide more reliable and detailed pre-crash information than survey variables alone. However, driving related distraction appears to be more difficult to capture. In order to gain a better understanding of the above issues and how frequently they occur in accidents, the data sources and analysis methods suggested here may be combined with other investigation methods such as in-depth accident investigations and pre-crash data recordings. Copyright © 2012 Elsevier Ltd. All rights reserved.

Drowsy Driving: Asleep at the Wheel

MedlinePlus

... Emergency Preparedness & Response Environmental Health Healthy Living Injury, Violence & Safety Life Stages & Populations Travelers’ Health Workplace Safety & Health Features Media Sign up for Features Get Email Updates To ...

Using speeding detections and numbers of fatalities to estimate relative risk of a fatality for motorcyclists and car drivers.

PubMed

Huggins, Richard

2013-10-01

Precise estimation of the relative risk of motorcyclists being involved in a fatal accident compared to car drivers is difficult. Simple estimates based on the proportions of licenced drivers or riders that are killed in a fatal accident are biased as they do not take into account the exposure to risk. However, exposure is difficult to quantify. Here we adapt the ideas behind the well known induced exposure methods and use available summary data on speeding detections and fatalities for motorcycle riders and car drivers to estimate the relative risk of a fatality for motorcyclists compared to car drivers under mild assumptions. The method is applied to data on motorcycle riders and car drivers in Victoria, Australia in 2010 and a small simulation study is conducted. Copyright © 2013 Elsevier Ltd. All rights reserved.

Non-coding cancer driver candidates identified with a sample- and position-specific model of the somatic mutation rate

PubMed Central

Juul, Malene; Bertl, Johanna; Guo, Qianyun; Nielsen, Morten Muhlig; Świtnicki, Michał; Hornshøj, Henrik; Madsen, Tobias; Hobolth, Asger; Pedersen, Jakob Skou

2017-01-01

Non-coding mutations may drive cancer development. Statistical detection of non-coding driver regions is challenged by a varying mutation rate and uncertainty of functional impact. Here, we develop a statistically founded non-coding driver-detection method, ncdDetect, which includes sample-specific mutational signatures, long-range mutation rate variation, and position-specific impact measures. Using ncdDetect, we screened non-coding regulatory regions of protein-coding genes across a pan-cancer set of whole-genomes (n = 505), which top-ranked known drivers and identified new candidates. For individual candidates, presence of non-coding mutations associates with altered expression or decreased patient survival across an independent pan-cancer sample set (n = 5454). This includes an antigen-presenting gene (CD1A), where 5’UTR mutations correlate significantly with decreased survival in melanoma. Additionally, mutations in a base-excision-repair gene (SMUG1) correlate with a C-to-T mutational-signature. Overall, we find that a rich model of mutational heterogeneity facilitates non-coding driver identification and integrative analysis points to candidates of potential clinical relevance. DOI: http://dx.doi.org/10.7554/eLife.21778.001 PMID:28362259

Driver fatigue detection through multiple entropy fusion analysis in an EEG-based system

PubMed Central

Min, Jianliang; Wang, Ping

2017-01-01

Driver fatigue is an important contributor to road accidents, and fatigue detection has major implications for transportation safety. The aim of this research is to analyze the multiple entropy fusion method and evaluate several channel regions to effectively detect a driver's fatigue state based on electroencephalogram (EEG) records. First, we fused multiple entropies, i.e., spectral entropy, approximate entropy, sample entropy and fuzzy entropy, as features compared with autoregressive (AR) modeling by four classifiers. Second, we captured four significant channel regions according to weight-based electrodes via a simplified channel selection method. Finally, the evaluation model for detecting driver fatigue was established with four classifiers based on the EEG data from four channel regions. Twelve healthy subjects performed continuous simulated driving for 1–2 hours with EEG monitoring on a static simulator. The leave-one-out cross-validation approach obtained an accuracy of 98.3%, a sensitivity of 98.3% and a specificity of 98.2%. The experimental results verified the effectiveness of the proposed method, indicating that the multiple entropy fusion features are significant factors for inferring the fatigue state of a driver. PMID:29220351

Construction and validation of the EEG analogues of the Karolinska sleepiness scale based on the Karolinska drowsiness test.

PubMed

Putilov, Arcady A; Donskaya, Olga G

2013-07-01

Simple methods of sleepiness assessment are greatly needed for both fundamental research and practical applications. The Karolinska drowsiness test (KDT) was applied to construct physiological alertness scales and to validate them against such well-known instrument of subjective sleepiness assessment as the Karolinska sleepiness scale (KSS). Seven-min EEG recordings were obtained with 2-h interval from frontal and occipital derivations during the last 32-50 h of 44-61-h wakefulness of 15 healthy study participants. Occipital alpha-theta power difference and frontal and occipital scores on the 2nd principal component of the EEG spectrum were calculated for each one-min interval of 5-min eyes closed section of the record. To obtain scores (from 0 to 5) on alertness scales for each of these EEG indexes, all positive one-min values of the index were assigned to 1, and all remaining (negative) values were assigned to 0. Scores on any of the physiological alertness scales were found to be strongly associated with KSS scores. Physiological analogues of KSS were offered by utilising the EEG recordings on eyes closed interval of KDT. The constructed physiological scales can help in improving validity and user-friendliness of the field and laboratory methods of quantification of drowsy state. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Characteristics of social drinkers with and without a hangover after heavy alcohol consumption.

PubMed

Hogewoning, A; Van de Loo, Ajae; Mackus, M; Raasveld, S J; De Zeeuw, R; Bosma, E R; Bouwmeester, N H; Brookhuis, K A; Garssen, J; Verster, J C

2016-01-01

A number of social drinkers claim that they do not experience next-day hangovers despite consuming large quantities of alcohol. The aim of this study was to investigate the characteristics of drinkers who claim to be hangover immune and compare them with drinkers who do report having hangovers. A total of 36 social drinkers participated in a naturalistic study consisting of a hangover day (alcohol consumed) and a control day (no alcohol consumed). Data were collected on alcohol consumption, demographics, sleep, next-day adverse effects, and mood. Data from drinkers with a hangover (N=18) were compared with data from drinkers who claim to be hangover immune (N=18). Drinkers with a hangover reported drowsiness-related symptoms, symptoms related to reduced cognitive functioning, and classic hangover symptoms such as headache, nausea, dizziness, weakness, and stomach pain. Corresponding mood changes comprised increased feelings of depression, anger-hostility, fatigue, and reduced vigor-activity. In contrast, hangover-immune drinkers reported relatively few hangover symptoms, with only mild corresponding severity scores. The reported symptoms were limited to drowsiness-related symptoms such as sleepiness and being tired. The classic hangover symptoms were usually not reported by these drinkers. In contrast to drinkers with a hangover, for those who claim to be hangover immune, next-day adverse effects of alcohol consumption are limited to a mild increase in drowsiness-related symptoms.

Alcohol hangover symptoms and their contribution to the overall hangover severity.

PubMed

Penning, Renske; McKinney, Adele; Verster, Joris C

2012-01-01

Scientific literature suggests a large number of symptoms that may be present the day after excessive alcohol consumption. The purpose of this study was to explore the presence and severity of hangover symptoms, and determine their interrelationship. A survey was conducted among n = 1410 Dutch students examining their drinking behavior and latest alcohol hangover. The severity of 47 presumed hangover symptoms were scored on a 10-point scale ranging from 0 (absent) to 10 (maximal). Factor analysis was conducted to summarize the data into groups of associated symptoms that contribute significantly to the alcohol hangover and symptoms that do not. About half of the participants (56.1%, n = 791) reported having had a hangover during the past month. Most commonly reported and most severe hangover symptoms were fatigue (95.5%) and thirst (89.1%). Factor analysis revealed 11 factors that together account for 62% of variance. The most prominent factor 'drowsiness' (explained variance 28.8%) included symptoms such as drowsiness, fatigue, sleepiness and weakness. The second factor 'cognitive problems' (explained variance 5.9%) included symptoms such as reduced alertness, memory and concentration problems. Other factors, including the factor 'disturbed water balance' comprising frequently reported symptoms such as 'dry mouth' and 'thirst', contributed much less to the overall hangover (explained variance <5%). Drowsiness and impaired cognitive functioning are the two dominant features of alcohol hangover.

Pattern of eyelid motion predictive of decision errors during drowsiness: oculomotor indices of altered states.

PubMed

Lobb, M L; Stern, J A

1986-08-01

Sequential patterns of eye and eyelid motion were identified in seven subjects performing a modified serial probe recognition task under drowsy conditions. Using simultaneous EOG and video recordings, eyelid motion was divided into components above, within, and below the pupil and the durations in sequence were recorded. A serial probe recognition task was modified to allow for distinguishing decision errors from attention errors. Decision errors were found to be more frequent following a downward shift in the gaze angle which the eyelid closing sequence was reduced from a five element to a three element sequence. The velocity of the eyelid moving over the pupil during decision errors was slow in the closing and fast in the reopening phase, while on decision correct trials it was fast in closing and slower in reopening. Due to the high variability of eyelid motion under drowsy conditions these findings were only marginally significant. When a five element blink occurred, the velocity of the lid over pupil motion component of these endogenous eye blinks was significantly faster on decision correct than on decision error trials. Furthermore, the highly variable, long duration closings associated with the decision response produced slow eye movements in the horizontal plane (SEM) which were more frequent and significantly longer in duration on decision error versus decision correct responses.

Modafinil

MedlinePlus

... It works by changing the amounts of certain natural substances in the area of the brain that ... asleep or staying asleep drowsiness nausea diarrhea constipation gas heartburn loss of appetite unusual tastes dry mouth ...

Citalopram

MedlinePlus

... mood changes, irritability, agitation, dizziness, numbness, tingling or electric shock-like sensations in the hands or feet, ... may make you drowsy. Do not drive a car or operate machinery until you know how this ...

Midazolam

MedlinePlus

... to cause drowsiness, relieve anxiety, and prevent any memory of the event. Midazolam is in a class ... if your child is taking certain medications for human immunodeficiency virus (HIV) including amprenavir (Agenerase), atazanavir (Reyataz), ...

A machine learning approach for detecting cell phone usage

NASA Astrophysics Data System (ADS)

Xu, Beilei; Loce, Robert P.

2015-03-01

Cell phone usage while driving is common, but widely considered dangerous due to distraction to the driver. Because of the high number of accidents related to cell phone usage while driving, several states have enacted regulations that prohibit driver cell phone usage while driving. However, to enforce the regulation, current practice requires dispatching law enforcement officers at road side to visually examine incoming cars or having human operators manually examine image/video records to identify violators. Both of these practices are expensive, difficult, and ultimately ineffective. Therefore, there is a need for a semi-automatic or automatic solution to detect driver cell phone usage. In this paper, we propose a machine-learning-based method for detecting driver cell phone usage using a camera system directed at the vehicle's front windshield. The developed method consists of two stages: first, the frontal windshield region localization using the deformable part model (DPM), next, we utilize Fisher vectors (FV) representation to classify the driver's side of the windshield into cell phone usage violation and non-violation classes. The proposed method achieved about 95% accuracy with a data set of more than 100 images with drivers in a variety of challenging poses with or without cell phones.

Pixel color feature enhancement for road signs detection

NASA Astrophysics Data System (ADS)

Zhang, Qieshi; Kamata, Sei-ichiro

2010-02-01

Road signs play an important role in our daily life which used to guide drivers to notice variety of road conditions and cautions. They provide important visual information that can help drivers operating their vehicles in a manner for enhancing traffic safety. The occurrence of some accidents can be reduced by using automatic road signs recognition system which can alert the drivers. This research attempts to develop a warning system to alert the drivers to notice the important road signs early enough to refrain road accidents from happening. For solving this, a non-linear weighted color enhancement method by pixels is presented. Due to the advantage of proposed method, different road signs can be detected from videos effectively. With suitably coefficients and operations, the experimental results have proved that the proposed method is robust, accurate and powerful in road signs detection.

Detecting driver fatigue through the use of advanced face monitoring techniques

DOT National Transportation Integrated Search

2001-09-01

Driver fatigue is an important factor in many vehicular accidents.Reducing the number of fatigue-related accidents would save : society a significant amount financially,in addition to reducing personal suffering.The researchers developed a driver fat...

The role of looming and attention capture in drivers' braking responses.

PubMed

Terry, Hugh R; Charlton, Samuel G; Perrone, John A

2008-07-01

This study assessed the ability of drivers to detect the deceleration of a preceding vehicle in a simulated vehicle-following task. The size of the preceding vehicles (car, van, or truck) and following speeds (50, 70, or 100 km/h) were systematically varied. Participants selected a preferred following distance by engaging their vehicle's cruise control and when the preceding vehicle began decelerating (no brake lights were illuminated), the participant's braking latency and distances to the lead vehicle were recorded. The experiment also employed a secondary task condition to examine how the attention-capturing properties of a looming vehicle were affected by driver distraction. The results indicated that a looming stimulus is capable of redirecting a driver's attention in a vehicle following task and, as with detection of brake lights, a driver's detection of a looming vehicle is compromised in the presence of a distracting task. Interestingly, increases in vehicle size had the effect of decreasing drivers' braking latencies and drivers engaged in the secondary task were significantly closer to the lead vehicle when they began braking, regardless of the size of the leading vehicle. Performance decrements resulting from the secondary task were reflected in a time-to-collision measure but not in optic expansion rate, lending support to earlier arguments that time-to-collision estimates require explicit cognitive judgements while perception of optic expansion may function in a more automatic fashion to redirect a driver's attention when cognitive resources are low or collision is imminent.

Role of sensory and cognitive conspicuity in the prevention of collisions between motorcycles and trucks at T-intersections.

PubMed

Law, Teik Hua; Ghanbari, Mahshid; Hamid, Hussain; Abdul-Halin, Alfian; Ng, Choy Peng

2016-11-01

Motorcyclists are particularly vulnerable to injury in crashes with heavy vehicles due to substantial differences in vehicle mass, the degree of protection and speed. There is a considerable difference in height between motorcycles and trucks; motorcycles are viewed by truck drivers from downward angles, and shorter distances between them mean steeper downward angles. Hence, we anticipated that the effects of motorcycle conspicuity treatments would be different for truck drivers. Therefore, this study aims to evaluate the effects of motorcycle conspicuity treatments on the identification and detection of motorcycles by truck drivers. Two complementary experiments were performed; the first experiment assessed the impact of motorcycle sensory conspicuity on the ability of un-alerted truck drivers to detect motorcycles, and the second experiment assessed the motorcycle cognitive conspicuity to alerted truck drivers. The sensory conspicuity was measured in terms of motorcycle detection rates by un-alerted truck drivers when they were not anticipating a motorcycle within a realistic driving scene, while the cognitive conspicuity was determined by the time taken by alerted truck drivers to actively search for a motorcycle. In the first experiment, the participants were presented with 10 pictures and were instructed to report the kinds of vehicles that were presented in the pictures. Each picture was shown to the participants for 600ms. In the second experiment, the participants were presented with the same set of pictures and were instructed to respond by clicking the right button on a mouse as soon as they detected a motorcycle in the picture. The results indicate that the motorcycle detection rate increases, and the response time to search for a motorcycle decreases, as the distance between the targeted motorcycle and the viewer decreases. This is true regardless of the type of conspicuity treatment used. The use of daytime running headlights (DRH) was found to increase the detection rate and the identification of a motorcycle by a truck driver at a farther distance, but effect deteriorates as the distance decreases. The results show that the detection rate and the identification of a motorcyclist wearing a black helmet with a reflective sticker increases as the distance between the motorcycle and the truck decreases. We also found that a motorcyclist wearing a white helmet and a white outfit is more identifiable and detectable at both shorter and longer distances. In conclusion, although this study provides evidence that the use of appropriate conspicuity treatments enhances motorcycle conspicuity to truck drivers, we suggest that more attention should be paid to the effect of background environment on motorcycle conspicuity. Copyright © 2016. Published by Elsevier Ltd.

Medicines for back pain

MedlinePlus

... direct care, they can be effective in reducing pain. Examples of narcotics include: Codeine Fentanyl -- available as a patch Hydrocodone Hydromorphone Morphine Oxycodone Tramadol Possible side effects of these drugs include: Drowsiness ...

Anxiety Disorders

MedlinePlus

... side effects, including drowsiness, and can be habit forming at higher doses. People taking these medications should ... their pursuit of life goals, prevents them from forming relationships, pursuing career or school, being assertive, or ...

49 CFR 228.411 - Training.

Code of Federal Regulations, 2013 CFR

2013-10-01

... fatigue, including sleep disorders; (3) Alertness strategies, such as policies on napping, to address acute drowsiness and fatigue while an employee is on duty; (4) Opportunities to obtain restful sleep at...

49 CFR 228.411 - Training.

Code of Federal Regulations, 2012 CFR

2012-10-01

... fatigue, including sleep disorders; (3) Alertness strategies, such as policies on napping, to address acute drowsiness and fatigue while an employee is on duty; (4) Opportunities to obtain restful sleep at...

49 CFR 228.411 - Training.

Code of Federal Regulations, 2014 CFR

2014-10-01

... fatigue, including sleep disorders; (3) Alertness strategies, such as policies on napping, to address acute drowsiness and fatigue while an employee is on duty; (4) Opportunities to obtain restful sleep at...

Model driver screening and evaluation program. Volume 1, Project summary and model program recommendations

DOT National Transportation Integrated Search

2003-05-01

This research project studied the feasibility as well as the scientific validity and utility of performing functional capacity screening with older drivers. A Model Program was described encompassing procedures to detect functionally impaired drivers...

Desipramine

MedlinePlus

... www.fda.gov/Drugs/DrugSafety/ucm085729.htm.No matter your age, before you take an antidepressant, you, ... seeing things that do not exist) widened pupils (dark circles in the middle of the eyes) drowsiness ...

Buprenorphine Transdermal Patch

MedlinePlus

... it to direct heat such as heating pads, electric blankets, heat lamps, saunas, hot tubs, and heated ... may make you drowsy. Do not drive a car, operate machinery, or do other possibly dangerous activities ...

Selegiline Transdermal Patch

MedlinePlus

... patch from direct heat such as heating pads, electric blankets, heat lamps, saunas, hot tubs, and heated ... may make you drowsy. Do not drive a car or operate machinery until you know how this ...

Early detection of ventricular tachycardia with sending messages to cell phone

NASA Astrophysics Data System (ADS)

Ramirez, L. J.; Lozano, F. A.; Rondon, C. R.

2011-09-01

Sustained ventricular tachycardia (VTs) can be asymptomatic for some people, but for other is deadly because it is a major cause of sudden cardiac death [1]. Some patients may present this arrhythmia, and even so, they decide to drive car increasing the likelihood of VTs, putting at risk not only his life but that of the other drivers. We developed a system for early detection of VTs, consisting of EKG sensors, a card of processing and a cell phone, which detects this arrhythmia, gives an alarm signal to the driver, and it simultaneously sending to text messages a specialist doctor and a relative or friend, all in real time. This design was conditioned to the car, is light and comfortable, that allowed that work of car's driver without discomfort. This system will save lives, since in case of emergency sends a help message, no matter where you are in the driver.

Thermally Activated Driver

NASA Technical Reports Server (NTRS)

Kinard, William H.; Murray, Robert C.; Walsh, Robert F.

1987-01-01

Space-qualified, precise, large-force, thermally activated driver (TAD) developed for use in space on astro-physics experiment to measure abundance of rare actinide-group elements in cosmic rays. Actinide cosmic rays detected using thermally activated driver as heart of event-thermometer (ET) system. Thermal expansion and contraction of silicone oil activates driver. Potential applications in fluid-control systems where precise valve controls are needed.

EEG-based driver fatigue detection using hybrid deep generic model.

PubMed

Phyo Phyo San; Sai Ho Ling; Rifai Chai; Tran, Yvonne; Craig, Ashley; Hung Nguyen

2016-08-01

Classification of electroencephalography (EEG)-based application is one of the important process for biomedical engineering. Driver fatigue is a major case of traffic accidents worldwide and considered as a significant problem in recent decades. In this paper, a hybrid deep generic model (DGM)-based support vector machine is proposed for accurate detection of driver fatigue. Traditionally, a probabilistic DGM with deep architecture is quite good at learning invariant features, but it is not always optimal for classification due to its trainable parameters are in the middle layer. Alternatively, Support Vector Machine (SVM) itself is unable to learn complicated invariance, but produces good decision surface when applied to well-behaved features. Consolidating unsupervised high-level feature extraction techniques, DGM and SVM classification makes the integrated framework stronger and enhance mutually in feature extraction and classification. The experimental results showed that the proposed DBN-based driver fatigue monitoring system achieves better testing accuracy of 73.29 % with 91.10 % sensitivity and 55.48 % specificity. In short, the proposed hybrid DGM-based SVM is an effective method for the detection of driver fatigue in EEG.

Shock

MedlinePlus

... Restlessness, anxiety or agitation Drowsiness or fatigue Dizziness, light-headedness or faintness Profuse sweating, moist skin Irritability Thirst Rapid pulse Rapid, weak breathing Enlarged pupils Nausea or vomiting Blue tinge to lips or fingernails (or gray in ...

Delirium

MedlinePlus

... may be slow moving or hyperactive) Changes in sleep patterns, drowsiness Confusion (disorientation) about time or place Decrease in short-term memory and recall Disorganized thinking, such as talking in a way that doesn't make sense ...

An examination of the impact of five grade crossing safety factors on driver decision making

DOT National Transportation Integrated Search

2014-04-01

The authors applied signal detection theory to model the impact : of five grade-crossing safety factors to understand their impact : on driver decision making. The safety factors were improving : commercial motor vehicle (CMV) driver safety through f...

Nortriptyline

MedlinePlus

... www.fda.gov/Drugs/DrugSafety/InformationbyDrugClass/UCM096273.No matter what your age, before you take an antidepressant, ... seeing things that do not exist) widened pupils (dark circles in the middle of the eyes) drowsiness ...

Central Sleep Apnea - Mayo Clinic

MedlinePlus

... up Difficulty staying asleep (insomnia) Excessive daytime sleepiness (hypersomnia) Chest pain at night Difficulty concentrating Mood changes ... chronically fatigued, sleepy and irritable. Excessive daytime drowsiness (hypersomnia) may be due to other disorders, such as ...

[Professional drivers and psychoactive substances consumption: results from medical surveillance at the workplace in Piedmont region].

PubMed

Rosso, G L; Feola, M; Rubinetto, Maria Paola; Petti, N; Rubinetto, L

2011-01-01

The use of psychoactive substances has been shown to be a risk factor for accidents in professional drivers. According to an approved Italian law, in order to detect dependency at the workplace the occupational health physician is called to assess the use of illicit drugs among professional drivers. The main purpose of this study was to investigate the use of psychoactive substances among professional drivers. From July to December 2008, rapid urine screening test was carried out on 198 professional drivers. All positive results from the screening stage were verified by specialized laboratories. We found 4 workers with a positive rapid urine screening test (7.1%), one of which was positive only for benzodiazepines and another positive test was not confirmed by specialized laboratory. By only considering illegal substances detected, 6.1% of the drivers tested positive. In this study, the high number of consumers among professional drivers ranged from 31 to 35 years old. Cannabis (THC) was the most frequently detected substance (seen in 10 over 12 cases,), after that was methadone (2/12 cases) and cocaine (1/12 case). We only had one case where more than one substance was found in the same subject (THC and cocaine). Five (41.7%) were former drug-addicts and public Pathological Addiction Services (Ser.T.) had previously followed them. Our results highlight the problem of drug consumption among professional drivers in Piedmont region. Health education and medical surveillance in workplace drug-testing may improve worker and third parties safety.

Roadside opioid testing of drivers using oral fluid: the case of a country with a zero tolerance law, Spain.

PubMed

Fierro, Inmaculada; Colás, Mónica; González-Luque, Juan Carlos; Álvarez, F Javier

2017-05-10

Opioids can impair psychomotor performance, and driving under the influence of opioids is associated with an increased risk of accidents. The goals of this study were i) to determine the prevalence of opioids (heroin, morphine, codeine, methadone and tramadol) in Spanish drivers and ii) to explore the presence of opioids, more specifically whether they are used alone or in combination with other drugs. The 2008/9 DRUID database regarding Spain was used, which provided information on 3302 drivers. All drivers included in the study provided a saliva sample and mass-chromatographic analyses were carried out in all cases. To determine the prevalence, the sample was weighted according to traffic intensity. In the case of opioid use combinations, the sample was not weighted. The detection limit for each substance was considered a positive result. The prevalence of opioids in Spanish drivers was 1.8% (95% CI, 1.4-2.3). Polydrug detection was common (56.2%): of these, in two out of three cases, two opioids were detected and cocaine was also detected in 86% of the cases. The concentration (median [Q1-Q3] ng/ml) of the substances was low: methadone 1.71 [0.10-15.30], codeine 40.55 [2.10-120.77], 6-acetylmorphine 5.71 [1.53-84.05], and morphine 37.40 [2.84-200.00]. Morphine was always detected with 6-acetylmorphine (heroin use). Driving under the influence of opioids is relatively infrequent, but polydrug use is common. Our study shows that 6 out of 10 drivers with methadone in their OF (likely in methadone maintenance programs) are using other substances. This should be taken into account by health professionals in order to properly inform patients about the added risks of mixing substances when driving.

Drivers' detection of roadside targets when driving vehicles with three headlight systems during high beam activation.

PubMed

Reagan, Ian J; Brumbelow, Matthew L

2017-02-01

A previous open-road experiment indicated that curve-adaptive HID headlights driven with low beams improved drivers' detection of low conspicuity targets compared with fixed halogen and fixed HID low beam systems. The current study used the same test environment and targets to assess whether drivers' detection of targets was affected by the same three headlight systems when using high beams. Twenty drivers search and responded for 60 8×12inch targets of high or low reflectance that were distributed evenly across straight and curved road sections as they drove at 30 mph on an unlit two-lane rural road. The results indicate that target detection performance was generally similar across the three systems. However, one interaction indicated that drivers saw low reflectance targets on straight road sections from further away when driving with the fixed halogen high beam condition compared with curve-adaptive HID high beam headlights and also indicated a possible benefit for the curve-adaptive HID high beams for high reflectance targets placed on the inside of curves. The results of this study conflict with the previous study of low beams, which showed a consistent benefit for the curve-adaptive HID low beams for targets placed on curves compared with fixed HID and fixed halogen low beam conditions. However, a comparison of mean detection distances from the two studies indicated uniformly longer mean target detection distances for participants driving with high beams and implicates the potential visibility benefits for systems that optimize proper high beam use. Copyright © 2016 Elsevier Ltd. All rights reserved.

Prevalence of alcohol and drug use in injured British Columbia drivers

PubMed Central

Brubacher, Jeffrey R; Chan, Herbert; Martz, Walter; Schreiber, William; Asbridge, Mark; Eppler, Jeffrey; Lund, Adam; Macdonald, Scott; Drummer, Olaf; Purssell, Roy; Andolfatto, Gary; Mann, Robert; Brant, Rollin

2016-01-01

Objectives Determine the prevalence of drug use in injured drivers and identify associated demographic factors and crash characteristics. Design Prospective cross-sectional study. Setting Seven trauma centres in British Columbia, Canada (2010–2012). Participants Automobile drivers who had blood obtained within 6 h of a crash. Main outcome measures We analysed blood for cannabis, alcohol and other impairing drugs using liquid chromatography/mass spectrometry (LCMS). Results 1097 drivers met inclusion criteria. 60% were aged 20–50 years, 63.2% were male and 29.0% were admitted to hospital. We found alcohol in 17.8% (15.6% to 20.1%) of drivers. Cannabis was the second most common recreational drug: cannabis metabolites were present in 12.6% (10.7% to 14.7%) of drivers and we detected Δ-9-tetrahydrocannabinol (Δ-9-THC) in 7.3% (5.9% to 9.0%), indicating recent use. Males and drivers aged under 30 years were most likely to use cannabis. We detected cocaine in 2.8% (2.0% to 4.0%) of drivers and amphetamines in 1.2% (0.7% to 2.0%). We also found medications including benzodiazepines (4.0% (2.9% to 5.3%)), antidepressants (6.5% (5.2% to 8.1%)) and diphenhydramine (4.7% (3.5% to 6.2%)). Drivers aged over 50 years and those requiring hospital admission were most likely to have used medications. Overall, 40.1% (37.2% to 43.0%) of drivers tested positive for alcohol or at least one impairing drug and 12.7% (10.7% to 14.7%) tested positive for more than one substance. Conclusions Alcohol, cannabis and a broad range of other impairing drugs are commonly detected in injured drivers. Alcohol is well known to cause crashes, but further research is needed to determine the impact of other drug use, including drug–alcohol and drug–drug combinations, on crash risk. In particular, more work is needed to understand the role of medications in causing crashes to guide driver education programmes and improve public safety. PMID:26966054

Deep Learning-Based Gaze Detection System for Automobile Drivers Using a NIR Camera Sensor.

PubMed

Naqvi, Rizwan Ali; Arsalan, Muhammad; Batchuluun, Ganbayar; Yoon, Hyo Sik; Park, Kang Ryoung

2018-02-03

A paradigm shift is required to prevent the increasing automobile accident deaths that are mostly due to the inattentive behavior of drivers. Knowledge of gaze region can provide valuable information regarding a driver's point of attention. Accurate and inexpensive gaze classification systems in cars can improve safe driving. However, monitoring real-time driving behaviors and conditions presents some challenges: dizziness due to long drives, extreme lighting variations, glasses reflections, and occlusions. Past studies on gaze detection in cars have been chiefly based on head movements. The margin of error in gaze detection increases when drivers gaze at objects by moving their eyes without moving their heads. To solve this problem, a pupil center corneal reflection (PCCR)-based method has been considered. However, the error of accurately detecting the pupil center and corneal reflection center is increased in a car environment due to various environment light changes, reflections on glasses surface, and motion and optical blurring of captured eye image. In addition, existing PCCR-based methods require initial user calibration, which is difficult to perform in a car environment. To address this issue, we propose a deep learning-based gaze detection method using a near-infrared (NIR) camera sensor considering driver head and eye movement that does not require any initial user calibration. The proposed system is evaluated on our self-constructed database as well as on open Columbia gaze dataset (CAVE-DB). The proposed method demonstrated greater accuracy than the previous gaze classification methods.

Disopyramide

MedlinePlus

... operate machinery until you know how this medication affects you.remember that alcohol can add to the drowsiness caused by this medication.talk to your doctor about the use of cigarettes and caffeine-containing beverages. These products may increase the irritability ...

Mumps

MedlinePlus

... you or your child has mumps along with: Red eyes Constant drowsiness Constant vomiting or abdominal pain Severe headache Pain or a lump in testicle Call the local emergency number (such as 911) or visit the emergency room if convulsions occur.

Mirtazapine

MedlinePlus

... the orally disintegrating tablets contain aspartame that forms phenylalanine.you should know that mirtazapine may cause angle- ... Mirtazapine may cause side effects. Tell your doctor if any of these symptoms are severe or do not go away: drowsiness dizziness anxiousness confusion ...

Videosensor for the Detection of Unsafe Driving Behavior in the Proximity of Black Spots

PubMed Central

Fuentes, Andres; Fuentes, Ricardo; Cabello, Enrique; Conde, Cristina; Martin, Isaac

2014-01-01

This paper discusses the overall design and implementation of a video sensor for the detection of risky behaviors of car drivers near previously identified and georeferenced black spots. The main goal is to provide the driver with a visual audio alert that informs of the proximity of an area of high incidence of highway accidents only if their driving behavior could result in a risky situation. It proposes a video sensor for detecting and supervising driver behavior, its main objective being manual distractions, so hand driver supervision is performed. A GPS signal is also considered, the GPS information is compared with a database of global positioning Black Spots to determine the relative proximity of a risky area. The outputs of the video sensor and GPS sensor are combined to evaluate a possible risky behavior. The results are promising in terms of risk analysis in order to be validated for use in the context of the automotive industry as future work. PMID:25347580

Videosensor for the detection of unsafe driving behavior in the proximity of black spots.

PubMed

Fuentes, Andres; Fuentes, Ricardo; Cabello, Enrique; Conde, Cristina; Martin, Isaac

2014-10-24

This paper discusses the overall design and implementation of a video sensor for the detection of risky behaviors of car drivers near previously identified and georeferenced black spots. The main goal is to provide the driver with a visual audio alert that informs of the proximity of an area of high incidence of highway accidents only if their driving behavior could result in a risky situation. It proposes a video sensor for detecting and supervising driver behavior, its main objective being manual distractions, so hand driver supervision is performed. A GPS signal is also considered, the GPS information is compared with a database of global positioning Black Spots to determine the relative proximity of a risky area. The outputs of the video sensor and GPS sensor are combined to evaluate a possible risky behavior. The results are promising in terms of risk analysis in order to be validated for use in the context of the automotive industry as future work.

The roles of garment design and scene complexity in the daytime conspicuity of high-visibility safety apparel.

PubMed

Sayer, James R; Buonarosa, Mary Lynn

2008-01-01

This study examines the effects of high-visibility garment design on daytime pedestrian conspicuity in work zones. Factors assessed were garment color, amount of background material, pedestrian arm motion, scene complexity, and driver age. The study was conducted in naturalistic conditions on public roads in real traffic. Drivers drove two passes on a 31-km route and indicated when they detected pedestrians outfitted in the fluorescent garments. The locations of the vehicle and the pedestrian were recorded. Detection distances between fluorescent yellow-green and fluorescent red-orange garments were not significantly different, nor were there any significant two-way interactions involving garment color. Pedestrians were detected at longer distances in lower complexity scenes. Arm motion significantly increased detection distances for pedestrians wearing a Class 2 vest, but had little added benefit on detection distances for pedestrians wearing a Class 2 jacket. Daytime detection distances for pedestrians wearing Class 2 or Class 3 garments are longest when the complexity of the surround is low. The more background information a driver has to search through, the longer it is likely to take the driver to locate a pedestrian--even when wearing a high-visibility garment. These findings will provide information to safety garment manufacturers about characteristics of high-visibility safety garments which make them effective for daytime use.

Determinants and Drivers of Infectious Disease Threat Events in Europe.

PubMed

Semenza, Jan C; Lindgren, Elisabet; Balkanyi, Laszlo; Espinosa, Laura; Almqvist, My S; Penttinen, Pasi; Rocklöv, Joacim

2016-04-01

Infectious disease threat events (IDTEs) are increasing in frequency worldwide. We analyzed underlying drivers of 116 IDTEs detected in Europe during 2008-2013 by epidemic intelligence at the European Centre of Disease Prevention and Control. Seventeen drivers were identified and categorized into 3 groups: globalization and environment, sociodemographic, and public health systems. A combination of >2 drivers was responsible for most IDTEs. The driver category globalization and environment contributed to 61% of individual IDTEs, and the top 5 individual drivers of all IDTEs were travel and tourism, food and water quality, natural environment, global trade, and climate. Hierarchical cluster analysis of all drivers identified travel and tourism as a distinctly separate driver. Monitoring and modeling such disease drivers can help anticipate future IDTEs and strengthen control measures. More important, intervening directly on these underlying drivers can diminish the likelihood of the occurrence of an IDTE and reduce the associated human and economic costs.

Determinants and Drivers of Infectious Disease Threat Events in Europe

PubMed Central

Lindgren, Elisabet; Balkanyi, Laszlo; Espinosa, Laura; Almqvist, My S.; Penttinen, Pasi; Rocklöv, Joacim

2016-01-01

Infectious disease threat events (IDTEs) are increasing in frequency worldwide. We analyzed underlying drivers of 116 IDTEs detected in Europe during 2008–2013 by epidemic intelligence at the European Centre of Disease Prevention and Control. Seventeen drivers were identified and categorized into 3 groups: globalization and environment, sociodemographic, and public health systems. A combination of >2 drivers was responsible for most IDTEs. The driver category globalization and environment contributed to 61% of individual IDTEs, and the top 5 individual drivers of all IDTEs were travel and tourism, food and water quality, natural environment, global trade, and climate. Hierarchical cluster analysis of all drivers identified travel and tourism as a distinctly separate driver. Monitoring and modeling such disease drivers can help anticipate future IDTEs and strengthen control measures. More important, intervening directly on these underlying drivers can diminish the likelihood of the occurrence of an IDTE and reduce the associated human and economic costs. PMID:26982104

Driver genes in non-small cell lung cancer: Characteristics, detection methods, and targeted therapies

PubMed Central

He, Bing; Zhang, Hu-Qin

2017-01-01

Lung cancer is one of the most common causes of cancer-related death in the world. The large number of lung cancer cases is non-small cell lung cancer (NSCLC), which approximately accounting for 75% of lung cancer. Over the past years, our comprehensive knowledge about the molecular biology of NSCLC has been rapidly enriching, which has promoted the discovery of driver genes in NSCLC and directed FDA-approved targeted therapies. Of course, the targeted therapies based on driver genes provide a more exact option for advanced non-small cell lung cancer, improving the survival rate of patients. Now, we will review the landscape of driver genes in NSCLC including the characteristics, detection methods, the application of target therapy and challenges. PMID:28915704

Periodic Limb Movement Disorder (PLMD) and Restless Legs Syndrome (RLS)

MedlinePlus

... Professional Version Sleep Disorders Overview of Sleep Snoring Insomnia and Excessive Daytime Sleepiness (EDS) Circadian Rhythm Sleep ... pressure when a person stands (orthostatic hypotension), and insomnia. Benzodiazepines: These drugs (such as clonazepam ) cause drowsiness, ...

The Impact of Delirium | NIH MedlinePlus the Magazine

MedlinePlus

... delusions Variable levels of consciousness or awareness Disrupted sleep patterns, drowsiness Confusion (disorientation) about time or place Declines in short-term memory and recall Disorganized thinking, talking in a way that doesn't make sense ...

Drowsiness and uncommon fever in a child after cannabis ingestion.

PubMed

Feliu, Catherine; Cazaubon, Yoann; Fouley, Aurélie; Guillemin, Hélène; Millart, Hervé; Gozalo, Claire; Djerada, Zoubir

2017-08-01

Trivialization of cannabis consumption goes hand in hand with a growing exposure of children and the number of cannabis poisoning cases is steadily increasing. As clinical presentation can be different from what is currently seen in adults, added to the fact that it is not always suspected, diagnosis of cannabis intoxication in children is often delayed or missed. A 16-month-old girl was admitted to the pediatric emergency unit for an important drowsiness combined to moderate fever. After elimination of infectious causes, a toxic origin was considered and biological analyses led to the diagnosis of involuntary acute cannabis intoxication. In conclusion, cannabis intoxication in child has uncommon presentations compared to that seen in adults. In this context, biological analyses have a great importance for a rapid diagnosis and also for the understanding intoxication circumstance. This is of paramount importance because it may lead to consider child protection measures.

A Vehicle Active Safety Model: Vehicle Speed Control Based on Driver Vigilance Detection Using Wearable EEG and Sparse Representation

PubMed Central

Zhang, Zutao; Luo, Dianyuan; Rasim, Yagubov; Li, Yanjun; Meng, Guanjun; Xu, Jian; Wang, Chunbai

2016-01-01

In this paper, we present a vehicle active safety model for vehicle speed control based on driver vigilance detection using low-cost, comfortable, wearable electroencephalographic (EEG) sensors and sparse representation. The proposed system consists of three main steps, namely wireless wearable EEG collection, driver vigilance detection, and vehicle speed control strategy. First of all, a homemade low-cost comfortable wearable brain-computer interface (BCI) system with eight channels is designed for collecting the driver’s EEG signal. Second, wavelet de-noising and down-sample algorithms are utilized to enhance the quality of EEG data, and Fast Fourier Transformation (FFT) is adopted to extract the EEG power spectrum density (PSD). In this step, sparse representation classification combined with k-singular value decomposition (KSVD) is firstly introduced in PSD to estimate the driver’s vigilance level . Finally, a novel safety strategy of vehicle speed control, which controls the electronic throttle opening and automatic braking after driver fatigue detection using the above method, is presented to avoid serious collisions and traffic accidents. The simulation and practical testing results demonstrate the feasibility of the vehicle active safety model. PMID:26907278

Psychoactive substances in seriously injured drivers in Denmark.

PubMed

Wiese Simonsen, K; Steentoft, A; Bernhoft, I M; Hels, T; Rasmussen, B S; Linnet, K

2013-01-10

This study assesses the presence of a number of psychoactive substances, including alcohol, based on blood samples from 840 seriously injured drivers admitted to five selected hospitals located in five different regions of Denmark. The study was a part of the EU 6th framework program DRUID (Driving Under the Influence of Drugs, Alcohol and Medicines). Blood samples were screened for 30 illegal and legal psychoactive substances and metabolites as well as ethanol. Danish legal limits were used to evaluate the frequency of drivers violating the Danish legislation while limit of quantification (LOQ) was used for monitoring positive drivers. Tramadol is not included in the Danish legislation therefore the general cut off, as decided in the DRUID project was used. Overall, ethanol (18%) was the most frequently identified compound (alone or in combination with other drugs) exceeding the legal limit, which is 0.53g/l in Denmark. The percentage of seriously injured drivers testing positive for medicinal drugs at levels above the Danish legal limit was 6.8%. Benzodiazepines and Z-drugs (6.4%) comprised the majority of this group. One or more illegal drugs (primarily amphetamines and cannabis) were found to be above the Danish legal limit in 4.9% of injured drivers. Young men (median age 31 years) were over-represented among injured drivers who violated Danish law for alcohol and drugs. Diazepam (4.4%), tramadol (3.2%), and clonazepam (3.0%) were the medicinal drugs most frequently detected at levels above LOQ, whereas amphetamines (5.4%) (amphetamine [5.2%] and methamphetamine [1.5%]), tetrahydrocannabinol (3.7%), and cocaine (3.3%), including the metabolite benzoylecgonine, were the most frequently detected illegal drugs. A driver could be positive for more than one substance; therefore, percentages are not mutually exclusive. Poly-drug use was observed in 112 (13%) seriously injured drivers. Tramadol was detected above DRUID cutoffs in 2.1% of seriously injured drivers. This is 3.5 times that observed in a Danish survey of randomly selected drivers. Moreover, illegal and medicinal drug levels above the Danish legal limit were present more than 10 times as frequently as in injured drivers, whereas ethanol was present more than 30 times as frequently than in randomly selected drivers. The results indicate that there is an increased risk in traffic when driving under the influence of psychoactive drugs, especially alcohol in young male drivers. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Identification of constrained cancer driver genes based on mutation timing.

PubMed

Sakoparnig, Thomas; Fried, Patrick; Beerenwinkel, Niko

2015-01-01

Cancer drivers are genomic alterations that provide cells containing them with a selective advantage over their local competitors, whereas neutral passengers do not change the somatic fitness of cells. Cancer-driving mutations are usually discriminated from passenger mutations by their higher degree of recurrence in tumor samples. However, there is increasing evidence that many additional driver mutations may exist that occur at very low frequencies among tumors. This observation has prompted alternative methods for driver detection, including finding groups of mutually exclusive mutations and incorporating prior biological knowledge about gene function or network structure. Dependencies among drivers due to epistatic interactions can also result in low mutation frequencies, but this effect has been ignored in driver detection so far. Here, we present a new computational approach for identifying genomic alterations that occur at low frequencies because they depend on other events. Unlike passengers, these constrained mutations display punctuated patterns of occurrence in time. We test this driver-passenger discrimination approach based on mutation timing in extensive simulation studies, and we apply it to cross-sectional copy number alteration (CNA) data from ovarian cancer, CNA and single-nucleotide variant (SNV) data from breast tumors and SNV data from colorectal cancer. Among the top ranked predicted drivers, we find low-frequency genes that have already been shown to be involved in carcinogenesis, as well as many new candidate drivers. The mutation timing approach is orthogonal and complementary to existing driver prediction methods. It will help identifying from cancer genome data the alterations that drive tumor progression.

Detecting alcohol and illicit drugs in oral fluid samples collected from truck drivers in the state of São Paulo, Brazil.

PubMed

Yonamine, Mauricio; Sanches, Livia Rentas; Paranhos, Beatriz Aparecida Passos Bismara; de Almeida, Rafael Menck; Andreuccetti, Gabriel; Leyton, Vilma

2013-01-01

Alcohol and drug use by truck drivers is a current problem in Brazil. Though there is evidence that alcohol consumption is occurring in higher proportions, the use of stimulant drugs to avoid fatigue and to maintain the work schedule has also been reported. The purpose of this study was to estimate the incidence of alcohol and illicit drug use among truck drivers on São Paulo state roads. São Paulo is the most populous state in Brazil and has the largest industrial park and economic production in the country. Data were assessed not only using a questionnaire but also, and more reliably, through toxicological analysis of oral fluid samples. Between the years 2002 and 2008, 1250 oral fluid samples were collected from truck drivers on the roads during morning hours. The samples were tested for the presence of alcohol, cocaine, tetrahydrocannabinol (THC), and amphetamine/methamphetamine. A previously published, validated gas chromatographic (gas chromatography-flame ionization detection and gas chromatography-mass spectrometry) method was applied to the samples for alcohol and drug detection. Of the total analyzed samples, 3.1 percent (n = 39) were positive: 1.44 percent (n = 18) were positive for alcohol, 0.64 percent (n = 8) for amphetamines, 0.56 percent (n = 7) for cocaine, and 0.40 percent (n = 5) for THC. In one case, cocaine and THC were detected. The results are indicative of the extent of alcohol and drug use by truck drivers in the state of São Paulo, Brazil. This research provides evidence that not only alcohol but also illicit drug use is a real problem among professional drivers. The use of these substances should be controlled to better promote safe driving conditions on Brazilian roads.

A comparative descriptive study examining the perceptions of cancer patients, family caregivers, and nurses on patient symptom severity in Turkey.

PubMed

Akin, Semiha; Durna, Zehra

2013-02-01

Perform a comparative descriptive study that aims to describe the symptom severity of patients receiving chemotherapy and to compare patient self-reports of symptom severity with inferences made by nurses and family caregivers. The study was performed in the chemotherapy unit of a university hospital. The study was conducted on 119 patients undergoing chemotherapy that had a family caregiver and a nurse (n = 7) primarily responsible for their care. Symptom assessments were completed using the Edmonton Symptom Assessment System (ESAS). Symptoms were rated independently by the patient, caregiver and nurse. The patients reported severe tiredness, loss of well-being, anxiety, drowsiness, appetite changes, depression, pain and nausea. The patients and caregivers showed a strong agreement of the patients' symptoms (P < .001). Patients and nurses showed poor to fair agreement of the symptoms of pain, tiredness, nausea, depression, drowsiness, appetite, loss of well-being, skin and nail changes, mouth sores, and hand numbness (P < .05). The patients' mean scores of symptoms such as pain, depression, anxiety, drowsiness and loss of well-being were lower than those of the caregivers. The patients' mean scores of symptoms such as tiredness, shortness of breath, skin and nail changes and mouth sores were higher than scores of nurses (P < .05). Perceptions of formal or informal caregivers about symptoms in patients with cancer will help clinicians to develop strategies or approaches to improve the caregiver symptom assessment. Copyright © 2012 Elsevier Ltd. All rights reserved.

Predictors of responses to corticosteroids for anorexia in advanced cancer patients: a multicenter prospective observational study.

PubMed

Matsuo, Naoki; Morita, Tatsuya; Matsuda, Yoshinobu; Okamoto, Kenichiro; Matsumoto, Yoshihisa; Kaneishi, Keisuke; Odagiri, Takuya; Sakurai, Hiroki; Katayama, Hideki; Mori, Ichiro; Yamada, Hirohide; Watanabe, Hiroaki; Yokoyama, Taro; Yamaguchi, Takashi; Nishi, Tomohiro; Shirado, Akemi; Hiramoto, Shuji; Watanabe, Toshio; Kohara, Hiroyuki; Shimoyama, Satofumi; Aruga, Etsuko; Baba, Mika; Sumita, Koki; Iwase, Satoru

2017-01-01

Although corticosteroids are widely used to relieve anorexia, information regarding the factors predicting responses to corticosteroids remains limited. The purpose of the study is to identify potential factors predicting responses to corticosteroids for anorexia in advanced cancer patients. Inclusion criteria for this multicenter prospective observational study were patients who had metastatic or locally advanced cancer and had an anorexia intensity score of 4 or more on a 0-10 Numerical Rating Scale (NRS). Univariate and multivariate analyses were conducted to identify the factors predicting ≥2-point reduction in NRS on day 3. Among 180 patients who received corticosteroids, 99 (55 %; 95 % confidence interval [CI], 47-62 %) had a response with ≥2-point reduction. Factors that significantly predicted responses were Palliative Performance Scale (PPS) > 40 and absence of drowsiness. In addition, factors that tended to be associated with ≥2-point reduction in NRS included PS 0-3, absence of diabetes mellitus, absence of peripheral edema, presence of lung metastasis, absence of peritoneal metastasis, baseline anorexia NRS of >6, presence of pain, and presence of constipation. A multivariate analysis showed that the independent factors predicting responses were PPS of >40 (odds ratio = 2.7 [95 % CI = 1.4-5.2]), absence of drowsiness (2.6 [1.3-5.0]), and baseline NRS of >6 (2.4 [1.1-4.8]). Treatment responses to corticosteroids for anorexia may be predicted by PPS, drowsiness, and baseline symptom intensity. Larger prospective studies are needed to confirm these results.

IC Treatment: Antidepressants

MedlinePlus

... prescribes you a TCA, take it in the early evening to eliminate unwanted morning drowsiness. For constipation, increase the amount of fiber in your diet. Consider taking Metamucil or a stool softener such as Colace. Pregnancy & Warnings None of the antidepressants in any of ...

Emergency Contraception

MedlinePlus

... levonorgestrel ECP, but this medicine can make a person feel drowsy. Who Uses It? Emergency contraception is not recommended as a ... Editorial Policy Permissions Guidelines Privacy Policy & Terms of ... is for educational purposes only. For specific medical advice, diagnoses, and treatment, consult your doctor. © ...

Quantitative analysis on electrooculography (EOG) for neurodegenerative disease

NASA Astrophysics Data System (ADS)

Liu, Chang-Chia; Chaovalitwongse, W. Art; Pardalos, Panos M.; Seref, Onur; Xanthopoulos, Petros; Sackellares, J. C.; Skidmore, Frank M.

2007-11-01

Many studies have documented abnormal horizontal and vertical eye movements in human neurodegenerative disease as well as during altered states of consciousness (including drowsiness and intoxication) in healthy adults. Eye movement measurement may play an important role measuring the progress of neurodegenerative diseases and state of alertness in healthy individuals. There are several techniques for measuring eye movement, Infrared detection technique (IR). Video-oculography (VOG), Scleral eye coil and EOG. Among those available recording techniques, EOG is a major source for monitoring the abnormal eye movement. In this real-time quantitative analysis study, the methods which can capture the characteristic of the eye movement were proposed to accurately categorize the state of neurodegenerative subjects. The EOG recordings were taken while 5 tested subjects were watching a short (>120 s) animation clip. In response to the animated clip the participants executed a number of eye movements, including vertical smooth pursued (SVP), horizontal smooth pursued (HVP) and random saccades (RS). Detection of abnormalities in ocular movement may improve our diagnosis and understanding a neurodegenerative disease and altered states of consciousness. A standard real-time quantitative analysis will improve detection and provide a better understanding of pathology in these disorders.

Directional templates for real-time detection of coronal axis rotated faces

NASA Astrophysics Data System (ADS)

Perez, Claudio A.; Estevez, Pablo A.; Garate, Patricio

2004-10-01

Real-time face and iris detection on video images has gained renewed attention because of multiple possible applications in studying eye function, drowsiness detection, virtual keyboard interfaces, face recognition, video processing and multimedia retrieval. In this paper, a study is presented on using directional templates in the detection of faces rotated in the coronal axis. The templates are built by extracting the directional image information from the regions of the eyes, nose and mouth. The face position is determined by computing a line integral using the templates over the face directional image. The line integral reaches a maximum when it coincides with the face position. It is shown an improvement in localization selectivity by the increased value in the line integral computed with the directional template. Besides, improvements in the line integral value for face size and face rotation angle was also found through the computation of the line integral using the directional template. Based on these results the new templates should improve selectivity and hence provide the means to restrict computations to a fewer number of templates and restrict the region of search during the face and eye tracking procedure. The proposed method is real time, completely non invasive and was applied with no background limitation and normal illumination conditions in an indoor environment.

Automatic detection of intoxicated drivers

DOT National Transportation Integrated Search

1972-01-01

As the evidence of the contribution of : intoxicated drivers to vehicular fatalities : continues to mount, interest has : grown in the development of novel countermeasures. : One approach now being considered : involves the use of a device : installe...

Test analysis and research on static choice reaction ability of commercial vehicle drivers

NASA Astrophysics Data System (ADS)

Zhang, Lingchao; Wei, Lang; Qiao, Jie; Tian, Shun; Wang, Shengchang

2017-03-01

Drivers' choice reaction ability has a certain relation with safe driving. It has important significance to research its influence on traffic safety. Firstly, the paper uses a choice reaction detector developed by research group to detect drivers' choice reaction ability of commercial vehicles, and gets 2641 effective samples. Then by using mathematical statistics method, the paper founds that average reaction time from accident group has no difference with non-accident group, and then introduces a variance rate of reaction time as a new index to replace it. The result shows that the test index choice reaction errors and variance rate of reaction time have positive correlations with accidents. Finally, according to testing results of the detector, the paper formulates a detection threshold with four levels for helping transportation companies to assess commercial vehicles drivers.

Study of driving fatigue alleviation by transcutaneous acupoints electrical stimulations.

PubMed

Wang, Fuwang; Wang, Hong

2014-01-01

Driving fatigue is more likely to bring serious safety trouble to traffic. Therefore, accurately and rapidly detecting driving fatigue state and alleviating fatigue are particularly important. In the present work, the electrical stimulation method stimulating the Láogóng point (PC8) of human body is proposed, which is used to alleviate the mental fatigue of drivers. The wavelet packet decomposition (WPD) is used to extract θ, α, and β subbands of drivers' electroencephalogram (EEG) signals. Performances of the two algorithms (θ + α)/(α + β) and θ/β are also assessed as possible indicators for fatigue detection. Finally, the differences between the drivers with electrical stimulation and normal driving are discussed. It is shown that stimulating the Láogóng point (PC8) using electrical stimulation method can alleviate driver fatigue effectively during longtime driving.

Reliability of the Watch-PAT 200 in Detecting Sleep Apnea in Highway Bus Drivers

PubMed Central

Yuceege, Melike; Firat, Hikmet; Demir, Ahmet; Ardic, Sadik

2013-01-01

Objective: To predict the validity of Watch-PAT (WP) device for sleep disordered breathing (SDB) among highway bus drivers. Method: A total number of 90 highway bus drivers have undergone polysomnography (PSG) and Watch-PAT test simultaneously. Routine blood tests and the routine ear-nose-throat (ENT) exams have been done as well. Results: The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 89.1%, 76.9%, 82% and 85.7% for RDI > 15, respectively. WRDI, WODI, W < 90% duration and Wmean SaO2 results were well correlated with the PSG results. In the sensitivity and specificity analysis, when diagnosis of sleep apnea was defined for different cut-off values of RDI of 5, 10 and 15, AUC (95%CI) were found as 0.84 (0.74-0.93), 0.87 (95%CI: 0.79-0.94) and 0.91 (95%CI: 0.85-0.97), respectively. There were no statistically significant differences between Stage1+2/Wlight and Stage REM/WREM. The percentage of Stage 3 sleep had difference significant statistically from the percentage of Wdeep. Total sleep times in PSG and WP showed no statistically important difference. Total NREM duration and total WNREM duration had no difference either. Conclusion: Watch-PAT device is helpful in detecting SDB with RDI > 15 in highway bus drivers, especially in drivers older than 45 years, but has limited value in drivers younger than 45 years old who have less risk for OSA. Therefore, WP can be used in the former group when PSG is not easily available. Citation: Yuceege M; Firat F; Demir A; Ardic S. Reliability of the Watch-PAT 200 in detecting sleep apnea in highway bus drivers. J Clin Sleep Med 2013;9(4):339-344. PMID:23585749

Examining the effects of an eco-driving message on driver distraction.

PubMed

Rouzikhah, Hossein; King, Mark; Rakotonirainy, Andry

2013-01-01

This paper examines the effects of an eco-driving message on driver distraction. Two in-vehicle distracter tasks were compared with an eco-driving task and a baseline task in an advanced driving simulator. N=22 subjects were asked to perform an eco-driving, CD changing, and a navigation task while engaged in critical manoeuvres during which they were expected to respond to a peripheral detection task (PDT) with total duration of 3.5h. The study involved two sessions over two consecutive days. The results show that drivers' mental workloads are significantly higher during navigation and CD changing tasks in comparison to the two other scenarios. However, eco-driving mental workload is still marginally significant (p∼.05) across different manoeuvres. Similarly, event detection tasks show that drivers miss significantly more events in the navigation and CD changing scenarios in comparison to both the baseline and eco-driving scenario. Analysis of the practice effect shows that drivers' baseline scenario and navigation scenario exhibit significantly less demand on the second day. Drivers also can detect significantly more events on the second day for all scenarios. The authors conclude that even reading a simple message while driving could potentially lead to missing an important event, especially when executing critical manoeuvres. However, there is some evidence of a practice effect which suggests that future research should focus on performance with habitual rather than novel tasks. It is recommended that sending text as an eco-driving message analogous to the study circumstances should not be delivered to drivers on-line when vehicle is in motion. Copyright © 2012 Elsevier Ltd. All rights reserved.

Mechanisms underlying cognitive conspicuity in the detection of cyclists by car drivers.

PubMed

Rogé, Joceline; Ndiaye, Daniel; Aillerie, Isabelle; Aillerie, Stéphane; Navarro, Jordan; Vienne, Fabrice

2017-07-01

The aim of this study was to evaluate the visibility of cyclists for motorists in a simulated car driving task. In several cases involving collisions between cars and cyclists, car drivers failed to detect the latter in time to avoid collision because of their low conspicuity. 2 groups of motorists (29.2 years old), including 12 cyclist-motorists and 13 non-cyclist-motorists, performed a vulnerable road user detection task in a car-driving simulator. They had to detect cyclists and pedestrians in an urban setting and evaluate the realism of the cyclists, the traffic, the city, the infrastructure, the car driven and the situations. Cyclists appeared in critical situations derived from previous accounts given by injured cyclists and from cyclists' observations in real-life situations. Cyclist's levels of visibility for car drivers were either high or low in these situations according to the cyclists. Realism scores were similar and high in both groups. Cyclist-motorists had fewer collisions with cyclists and detected cyclists at a greater distance in all situations, irrespective of cyclist visibility. Several mechanisms underlying the cognitive conspicuity of cyclists for car drivers were considered. The attentional selection of a cyclist in the road environment during car driving depends on top-down processing. We consider the practical implications of these results for the safety of vulnerable road users and future directions of research. Copyright © 2017 Elsevier Ltd. All rights reserved.

Driver Vigilance in Automated Vehicles: Hazard Detection Failures Are a Matter of Time.

PubMed

Greenlee, Eric T; DeLucia, Patricia R; Newton, David C

2018-06-01

The primary aim of the current study was to determine whether monitoring the roadway for hazards during automated driving results in a vigilance decrement. Although automated vehicles are relatively novel, the nature of human-automation interaction within them has the classic hallmarks of a vigilance task. Drivers must maintain attention for prolonged periods of time to detect and respond to rare and unpredictable events, for example, roadway hazards that automation may be ill equipped to detect. Given the similarity with traditional vigilance tasks, we predicted that drivers of a simulated automated vehicle would demonstrate a vigilance decrement in hazard detection performance. Participants "drove" a simulated automated vehicle for 40 minutes. During that time, their task was to monitor the roadway for roadway hazards. As predicted, hazard detection rate declined precipitously, and reaction times slowed as the drive progressed. Further, subjective ratings of workload and task-related stress indicated that sustained monitoring is demanding and distressing and it is a challenge to maintain task engagement. Monitoring the roadway for potential hazards during automated driving results in workload, stress, and performance decrements similar to those observed in traditional vigilance tasks. To the degree that vigilance is required of automated vehicle drivers, performance errors and associated safety risks are likely to occur as a function of time on task. Vigilance should be a focal safety concern in the development of vehicle automation.

EzyAmp signal amplification cascade enables isothermal detection of nucleic acid and protein targets.

PubMed

Linardy, Evelyn M; Erskine, Simon M; Lima, Nicole E; Lonergan, Tina; Mokany, Elisa; Todd, Alison V

2016-01-15

Advancements in molecular biology have improved the ability to characterize disease-related nucleic acids and proteins. Recently, there has been an increasing desire for tests that can be performed outside of centralised laboratories. This study describes a novel isothermal signal amplification cascade called EzyAmp (enzymatic signal amplification) that is being developed for detection of targets at the point of care. EzyAmp exploits the ability of some restriction endonucleases to cleave substrates containing nicks within their recognition sites. EzyAmp uses two oligonucleotide duplexes (partial complexes 1 and 2) which are initially cleavage-resistant as they lack a complete recognition site. The recognition site of partial complex 1 can be completed by hybridization of a triggering oligonucleotide (Driver Fragment 1) that is generated by a target-specific initiation event. Binding of Driver Fragment 1 generates a completed complex 1, which upon cleavage, releases Driver Fragment 2. In turn, binding of Driver Fragment 2 to partial complex 2 creates completed complex 2 which when cleaved releases additional Driver Fragment 1. Each cleavage event separates fluorophore quencher pairs resulting in an increase in fluorescence. At this stage a cascade of signal production becomes independent of further target-specific initiation events. This study demonstrated that the EzyAmp cascade can facilitate detection and quantification of nucleic acid targets with sensitivity down to aM concentration. Further, the same cascade detected VEGF protein with a sensitivity of 20nM showing that this universal method for amplifying signal may be linked to the detection of different types of analytes in an isothermal format. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

[Drug use and involvement in risky driving styles in a sample of university students. The uniHcos project].

PubMed

Jiménez-Mejías, Eladio; Medina-García, Miguel Ángel; Martínez-Ruiz, Virginia; Pulido-Manzanero, José; Fernández-Villa, Tania

2015-09-01

Drug and alcohol use are known to increase the risk of traffic accidents, especially among youth. However, the association between habitual drug use and the adoption of risky driving behavior is not well known. The aim of this study was to identify and quantify the association between habitual drug use and involvement in risky driving practices overall and by gender among university students. A cross sectional study was conducted. The study population was composed of 559 car drivers younger than 31 years who completed an online questionnaire during the 2011-2012 academic year. Among other factors, the questionnaire assessed the following items: habitual drug consumption (20 or more days) during the last year and involvement in other risky driving practices during the last month. A total of 27.7% of students reported they had used drugs regularly during the last year. Drug use was associated with a higher frequency of involvement in risky driving practices. In men, the factors most strongly associated with drug consumption were speeding, driving under influence of alcohol, and feeling drowsy while driving. In women, drug consumption was mainly associated with smoking while driving, drunk driving, and driving without rest. The results of our study support the hypothesis that habitual drug use is associated with an increased frequency of risky driving behavior. Copyright © 2014 SESPAS. Published by Elsevier Espana. All rights reserved.

Impaired-driving prevalence among US high school students: associations with substance use and risky driving behaviors.

PubMed

Li, Kaigang; Simons-Morton, Bruce G; Hingson, Ralph

2013-11-01

We examined the prevalence of impaired driving among US high school students and associations with substance use and risky driving behavior. We assessed driving while alcohol or drug impaired (DWI) and riding with alcohol- or drug-impaired drivers (RWI) in a nationally representative sample of 11th-grade US high school students (n = 2431). We examined associations with drinking and binge drinking, illicit drug use, risky driving, and demographic factors using multivariate sequential logistic regression analysis. Thirteen percent of 11th-grade students reported DWI at least 1 of the past 30 days, and 24% reported RWI at least once in the past year. Risky driving was positively associated with DWI (odds ratio [OR] = 1.25; P < .001) and RWI (OR = 1.09; P < .05), controlling for binge drinking (DWI: OR = 3.17; P < .01; RWI: OR = 6.12; P < .001) and illicit drug use (DWI: OR = 5.91; P < .001; RWI: OR = 2.29; P = .05). DWI was higher for adolescents who drove after midnight (OR = 15.7), drove while sleepy or drowsy (OR = 8.6), read text messages (OR = 11.8), sent text messages (OR = 5.0), and made cell phone calls (OR = 3.2) while driving. Our findings suggest the need for comprehensive approaches to the prevention of DWI, RWI, and other risky driving behavior.

Assisting People with Developmental Disabilities to Improve Pointing Efficiency with a Dual Cursor Automatic Pointing Assistive Program

ERIC Educational Resources Information Center

Shih, Ching-Hsiang; Chung, Chiao-Chen; Chiang, Ming-Shan; Shih, Ching-Tien

2010-01-01

This study evaluated whether two persons with developmental disabilities would be able to improve their pointing performance through a Dual Cursor Automatic Pointing Assistive Program (DCAPAP) with a newly developed mouse driver (i.e., a new mouse driver replaces standard mouse driver, and is able to intercept/detect mouse movement action). First,…

76 FR 11418 - Rear Visibility; Federal Motor Vehicle Safety Standard, Rearview Mirrors; Federal Motor Vehicle...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-02

... mirrors to improve the ability of a driver of a vehicle to detect pedestrians in the area immediately..., NHTSA proposed to specify an area immediately behind each vehicle that the driver must be able to see... agency's Federal motor vehicle safety standard on rearview mirrors to improve the ability of a driver to...

High-risk behaviors and experiences with traffic law among night drivers in Curitiba, Brazil.

PubMed

Ulinski, Sandra L; Moysés, Simone T; Werneck, Renata I; Moysés, Samuel J

2016-01-08

To explore high-risk behaviors and experiences with traffic law among night drivers in Curitiba, Brazil. Data from 398 drivers on sociodemographic parameters, high-risk behaviors, experiences with traffic law, and traffic law violations were collected through interviews conducted at sobriety checkpoints. Exploratory-descriptive and analytical statistics were used. The mean age of the participants was 32.6±11.2 years (range, 18 to 75 years). Half of the drivers reported having driven after drinking in the last year, predominantly single men aged 18 to 29 years who drive cars and drink alcohol frequently. Only 55% of the drivers who had driven after drinking in the last year self-reported some concern about being detected in a police operation. A significant association was found between sociodemographic variables and behavior, which can help tailor public interventions to a specific group of drivers: young men who exhibit high-risk behaviors in traffic, such as driving after drinking alcohol, some of whom report heavy alcohol consumption. This group represents a challenge for educational and enforcement interventions, particularly because they admit to violating current laws and have a low perception of punishment due to the low risk of being detected by the police.

Driver performance and attention allocation in use of logo signs on freeway exit ramps.

PubMed

Zahabi, Maryam; Machado, Patricia; Lau, Mei Ying; Deng, Yulin; Pankok, Carl; Hummer, Joseph; Rasdorf, William; Kaber, David B

2017-11-01

The objective of this research was to quantify the effects of driver age, ramp signage configuration, including number of panels, logo format and sign familiarity, on driver performance and attention allocation when exiting freeways. Sixty drivers participated in a simulator study and analysis of variance models were used to assess response effects of the controlled manipulations. Results revealed elderly drivers to demonstrate worse performance and conservative control strategies as compared to middle-aged and young drivers. Elderly drivers also exhibited lower off-road fixation frequency and shorter off-road glance durations compared to middle-aged and young drivers. In general, drivers adopted a more conservative strategy when exposed to nine-panel signs as compared to six-panel signs and were more accurate in target detection when searching six-panels vs. nine and with familiar vs. unfamiliar logos. These findings provide an applicable guide for agency design of freeway ramp signage accounting for driver demographics. Copyright © 2017 Elsevier Ltd. All rights reserved.

32 CFR 634.36 - Detection, apprehension, and testing of intoxicated drivers.

Code of Federal Regulations, 2014 CFR

2014-07-01

... unusual or abnormal driving behavior. Drivers showing such behavior will be stopped immediately. The cause of the unusual driving behavior will be determined, and proper enforcement action will be taken. (b...

32 CFR 634.36 - Detection, apprehension, and testing of intoxicated drivers.

Code of Federal Regulations, 2013 CFR

2013-07-01

... unusual or abnormal driving behavior. Drivers showing such behavior will be stopped immediately. The cause of the unusual driving behavior will be determined, and proper enforcement action will be taken. (b...

32 CFR 634.36 - Detection, apprehension, and testing of intoxicated drivers.

Code of Federal Regulations, 2012 CFR

2012-07-01

... unusual or abnormal driving behavior. Drivers showing such behavior will be stopped immediately. The cause of the unusual driving behavior will be determined, and proper enforcement action will be taken. (b...

Identification of Constrained Cancer Driver Genes Based on Mutation Timing

PubMed Central

Sakoparnig, Thomas; Fried, Patrick; Beerenwinkel, Niko

2015-01-01

Cancer drivers are genomic alterations that provide cells containing them with a selective advantage over their local competitors, whereas neutral passengers do not change the somatic fitness of cells. Cancer-driving mutations are usually discriminated from passenger mutations by their higher degree of recurrence in tumor samples. However, there is increasing evidence that many additional driver mutations may exist that occur at very low frequencies among tumors. This observation has prompted alternative methods for driver detection, including finding groups of mutually exclusive mutations and incorporating prior biological knowledge about gene function or network structure. Dependencies among drivers due to epistatic interactions can also result in low mutation frequencies, but this effect has been ignored in driver detection so far. Here, we present a new computational approach for identifying genomic alterations that occur at low frequencies because they depend on other events. Unlike passengers, these constrained mutations display punctuated patterns of occurrence in time. We test this driver–passenger discrimination approach based on mutation timing in extensive simulation studies, and we apply it to cross-sectional copy number alteration (CNA) data from ovarian cancer, CNA and single-nucleotide variant (SNV) data from breast tumors and SNV data from colorectal cancer. Among the top ranked predicted drivers, we find low-frequency genes that have already been shown to be involved in carcinogenesis, as well as many new candidate drivers. The mutation timing approach is orthogonal and complementary to existing driver prediction methods. It will help identifying from cancer genome data the alterations that drive tumor progression. PMID:25569148

RUBIC identifies driver genes by detecting recurrent DNA copy number breaks

PubMed Central

van Dyk, Ewald; Hoogstraat, Marlous; ten Hoeve, Jelle; Reinders, Marcel J. T.; Wessels, Lodewyk F. A.

2016-01-01

The frequent recurrence of copy number aberrations across tumour samples is a reliable hallmark of certain cancer driver genes. However, state-of-the-art algorithms for detecting recurrent aberrations fail to detect several known drivers. In this study, we propose RUBIC, an approach that detects recurrent copy number breaks, rather than recurrently amplified or deleted regions. This change of perspective allows for a simplified approach as recursive peak splitting procedures and repeated re-estimation of the background model are avoided. Furthermore, we control the false discovery rate on the level of called regions, rather than at the probe level, as in competing algorithms. We benchmark RUBIC against GISTIC2 (a state-of-the-art approach) and RAIG (a recently proposed approach) on simulated copy number data and on three SNP6 and NGS copy number data sets from TCGA. We show that RUBIC calls more focal recurrent regions and identifies a much larger fraction of known cancer genes. PMID:27396759

Detection of illicit drugs in impaired driver saliva by a field-usable SERS analyzer

NASA Astrophysics Data System (ADS)

Shende, Chetan; Huang, Hermes; Farquharson, Stuart

2014-05-01

One of the greatest dangers of drug use is in combination with driving. According to the most recent National Highway Traffic Safety Administration (NHTSA) studies, more than 11% of drivers tested positive for illicit drugs, while 18% of drivers killed in accidents tested positive for illicit, prescription or over-the-counter drugs. Consequently, there is a need for a rapid, noninvasive, roadside drug testing device, similar to the breathalyzers used by law enforcement officials to estimate blood alcohol levels of impaired drivers. In an effort to satisfy this need we have been developing a sampling kit that allows extraction of drugs from 1 mL of saliva and detection by surfaceenhanced Raman spectroscopy using a portable Raman analyzer. Here we describe the development of the sampling kit and present measurements of diazepam at sub μg/mL concentrations measured in ~15 minutes.

Study of Driving Fatigue Alleviation by Transcutaneous Acupoints Electrical Stimulations

PubMed Central

Wang, Fuwang; Wang, Hong

2014-01-01

Driving fatigue is more likely to bring serious safety trouble to traffic. Therefore, accurately and rapidly detecting driving fatigue state and alleviating fatigue are particularly important. In the present work, the electrical stimulation method stimulating the Láogóng point (劳宫PC8) of human body is proposed, which is used to alleviate the mental fatigue of drivers. The wavelet packet decomposition (WPD) is used to extract θ, α, and β subbands of drivers' electroencephalogram (EEG) signals. Performances of the two algorithms (θ + α)/(α + β) and θ/β are also assessed as possible indicators for fatigue detection. Finally, the differences between the drivers with electrical stimulation and normal driving are discussed. It is shown that stimulating the Láogóng point (劳宫PC8) using electrical stimulation method can alleviate driver fatigue effectively during longtime driving. PMID:25254242

A study on obstacle detection method of the frontal view using a camera on highway

NASA Astrophysics Data System (ADS)

Nguyen, Van-Quang; Park, Jeonghyeon; Seo, Changjun; Kim, Heungseob; Boo, Kwangsuck

2018-03-01

In this work, we introduce an approach to detect vehicles for driver assistance, or warning system. For driver assistance system, it must detect both lanes (left and right side lane), and discover vehicles ahead of the test vehicle. Therefore, in this study, we use a camera, it is installed on the windscreen of the test vehicle. Images from the camera are used to detect three lanes, and detect multiple vehicles. In lane detection, line detection and vanishing point estimation are used. For the vehicle detection, we combine the horizontal and vertical edge detection, the horizontal edge is used to detect the vehicle candidates, and then the vertical edge detection is used to verify the vehicle candidates. The proposed algorithm works with of 480 × 640 image frame resolution. The system was tested on the highway in Korea.

What the drivers do and do not tell you: using verbal protocol analysis to investigate driver behaviour in emergency situations.

PubMed

Banks, Victoria A; Stanton, Neville A; Harvey, Catherine

2014-01-01

Although task analysis of pedestrian detection can provide us with useful insights into how a driver may behave in emergency situations, the cognitive elements of driver decision-making are less well understood. To assist in the design of future Advanced Driver Assistance Systems, such as Autonomous Emergency Brake systems, it is essential that the cognitive elements of the driving task are better understood. This paper uses verbal protocol analysis in an exploratory fashion to uncover the thought processes underlying behavioural outcomes represented by hard data collected using the Southampton University Driving Simulator.

Development of an algorithm for an EEG-based driver fatigue countermeasure.

PubMed

Lal, Saroj K L; Craig, Ashley; Boord, Peter; Kirkup, Les; Nguyen, Hung

2003-01-01

Fatigue affects a driver's ability to proceed safely. Driver-related fatigue and/or sleepiness are a significant cause of traffic accidents, which makes this an area of great socioeconomic concern. Monitoring physiological signals while driving provides the possibility of detecting and warning of fatigue. The aim of this paper is to describe an EEG-based fatigue countermeasure algorithm and to report its reliability. Changes in all major EEG bands during fatigue were used to develop the algorithm for detecting different levels of fatigue. The software was shown to be capable of detecting fatigue accurately in 10 subjects tested. The percentage of time the subjects were detected to be in a fatigue state was significantly different than the alert phase (P<.01). This is the first countermeasure software described that has shown to detect fatigue based on EEG changes in all frequency bands. Field research is required to evaluate the fatigue software in order to produce a robust and reliable fatigue countermeasure system. The development of the fatigue countermeasure algorithm forms the basis of a future fatigue countermeasure device. Implementation of electronic devices for fatigue detection is crucial for reducing fatigue-related road accidents and their associated costs.

Quality of life after whole brain radiotherapy compared with radiosurgery of the tumor bed: results from a randomized trial.

PubMed

Kepka, L; Tyc-Szczepaniak, D; Osowiecka, K; Sprawka, A; Trąbska-Kluch, B; Czeremszynska, B

2018-02-01

A recent randomized trial (NCT01535209) demonstrated no difference in neurocognitive function between stereotactic radiotherapy of the tumor bed (SRT-TB) and whole brain radiotherapy (WBRT) in patients with resected single brain metastasis. Patients treated with SRT-TB had lower overall survival compared with the WBRT arm. Here, we compared the health-related quality of life (HRQOL) in patients who received WBRT vs. SRT-TB. A self-reported questionnaire was used to assess HRQOL (EORTC QLQ-C30 with the QLQ-BN20 module) before RT, 2 months after RT, and every 3 months thereafter. HRQOL results are presented as mean scores and compared between groups. Of 59 randomized patients, 37 (64%) were eligible for HRQOL analysis, 15 received SRT-TB, and 22 had WBRT. There were no differences between groups in global health status and main function scales/symptoms (except for drowsiness and appetite loss, which were worse with WBRT 2 months after RT). Global health status decreased 2 and 5 months after RT, but significantly only for SRT-TB (p = 0.025). Physical function decreased significantly 5 months after SRT-TB (p = 0.008). Future uncertainty worsened after RT, but significantly only for SRT-TB after 2 months (p = 0.036). Patients treated with WBRT had significant worsening of appetite, hair loss, and drowsiness after treatment. Despite higher symptom burden after WBRT attributed to the side effects of RT (such as appetite loss, drowsiness, and hair loss), global health status, physical functioning, and future uncertainty favored WBRT compared with SRT-TB. This may be related to the compromised brain tumor control with omission of WBRT.

Promethazine and its use as a treatment for space motion sickness

NASA Technical Reports Server (NTRS)

Bagian, James P.; Beck, Bradley G.

1993-01-01

Until Mar. 1989, no effective treatment--either prophylactic or symptomatic--for space motion sickness (SMS) had been discovered. Since Mar. 1989, intramuscular (IM) promethazine (PMZ) has been used in the treatment of SMS with extremely favorably results reported by the crew. A retrospective study was undertaken to quantify the efficacy of IM PMZ since its institution and the incidence of its major anticipated side-effect drowsiness and sedation. The results from a standardized crew medical debriefing conducted immediately after landing and follow-up interviews with the crews were used in establishing the efficacy and incidence of side effects from treatment. Only crews from the first 44 Shuttle flights on their first mission were considered. For a total of 132 crewmembers, 96 exhibited symptoms of SMS; and, of these, 20 were treated with IM PMZ. Ninety percent of those receiving IM PMZ 25-50mg received nearly immediate (less than 2 hours) relief of symptoms and 75 percent required no further treatment through the first 2 days of spaceflight. Those not receiving this treatment did not have any near-term resolution of their symptoms, and 50 percent were still ill through the second day of flight. This represents a significant difference at the p = 0.46 level. In stark contrast to the 60 percent to 73 percent incidence of sedation or drowsiness reported in individuals treated with PMZ in terrestrial environment at the doses used here, less than 5 percent reported these symptoms during spaceflight. IM PMZ is an effective therapy for SMS and is associated with minimal incidence of sedation or drowsiness. This combination of efficacy that is absent of significant side effects represents a substantial improvement in the operational situation of crewmembers afflicted with SMS. Studies to understand the mechanisms underlying these observations will be undertaken in the future.

ECG on the road: robust and unobtrusive estimation of heart rate.

PubMed

Wartzek, Tobias; Eilebrecht, Benjamin; Lem, Jeroen; Lindner, Hans-Joachim; Leonhardt, Steffen; Walter, Marian

2011-11-01

Modern automobiles include an increasing number of assistance systems to increase the driver's safety. This feasibility study investigated unobtrusive capacitive ECG measurements in an automotive environment. Electrodes integrated into the driving seat allowed to measure a reliable ECG in 86% of the drivers; when only (light) cotton clothing was worn by the drivers, this value increased to 95%. Results show that an array of sensors is needed that can adapt to the different drivers and sitting positions. Measurements while driving show that traveling on the highway does not distort the signal any more than with the car engine turned OFF, whereas driving in city traffic results in a lowered detection rate due to the driver's heavier movements. To enable robust and reliable estimation of heart rate, an algorithm is presented (based on principal component analysis) to detect and discard time intervals with artifacts. This, then, allows a reliable estimation of heart rate of up to 61% in city traffic and up to 86% on the highway: as a percentage of the total driving period with at least four consecutive QRS complexes.

Recurrent chromosomal gains and heterogeneous driver mutations characterise papillary renal cancer evolution

PubMed Central

Kovac, Michal; Navas, Carolina; Horswell, Stuart; Salm, Max; Bardella, Chiara; Rowan, Andrew; Stares, Mark; Castro-Giner, Francesc; Fisher, Rosalie; de Bruin, Elza C.; Kovacova, Monika; Gorman, Maggie; Makino, Seiko; Williams, Jennet; Jaeger, Emma; Jones, Angela; Howarth, Kimberley; Larkin, James; Pickering, Lisa; Gore, Martin; Nicol, David L.; Hazell, Steven; Stamp, Gordon; O’Brien, Tim; Challacombe, Ben; Matthews, Nik; Phillimore, Benjamin; Begum, Sharmin; Rabinowitz, Adam; Varela, Ignacio; Chandra, Ashish; Horsfield, Catherine; Polson, Alexander; Tran, Maxine; Bhatt, Rupesh; Terracciano, Luigi; Eppenberger-Castori, Serenella; Protheroe, Andrew; Maher, Eamonn; El Bahrawy, Mona; Fleming, Stewart; Ratcliffe, Peter; Heinimann, Karl; Swanton, Charles; Tomlinson, Ian

2015-01-01

Papillary renal cell carcinoma (pRCC) is an important subtype of kidney cancer with a problematic pathological classification and highly variable clinical behaviour. Here we sequence the genomes or exomes of 31 pRCCs, and in four tumours, multi-region sequencing is undertaken. We identify BAP1, SETD2, ARID2 and Nrf2 pathway genes (KEAP1, NHE2L2 and CUL3) as probable drivers, together with at least eight other possible drivers. However, only ~10% of tumours harbour detectable pathogenic changes in any one driver gene, and where present, the mutations are often predicted to be present within cancer sub-clones. We specifically detect parallel evolution of multiple SETD2 mutations within different sub-regions of the same tumour. By contrast, large copy number gains of chromosomes 7, 12, 16 and 17 are usually early, monoclonal changes in pRCC evolution. The predominance of large copy number variants as the major drivers for pRCC highlights an unusual mode of tumorigenesis that may challenge precision medicine approaches. PMID:25790038

Rootkit Detection Using a Cross-View Clean Boot Method

DTIC Science & Technology

2013-03-01

FindNextFile: [2] Kernel32.dll 4. SSDTHooks r -- ... CALL NtQueryDirectoryFile 5. Code Patch ing - 6. Layered Driver 4 NtQueryDirectoryFile : 7...NTFS Driver 0 Volume Manger Disk Driver [2] I. Disk Driver r ! J IAT hooks take advantage of function calls in applications [13]. When an...f36e923898161fa7be50810288e2f48a 61 Appendix D: Windows Source Code Windows Batch File @echo o f f py thon walk . py pause shutdown − r − t 0 Walk.py in

Model enforcement program against suspended and revoked drivers : guidelines for motor vehicle administrators.

DOT National Transportation Integrated Search

1985-01-01

To develop more effective countermeasures for the detection/prosecution of suspended/revoked drivers who continue to drive, the National Highway Traffic Safety Administration (NHTSA) contracted with the American Association of Motor Vehicle Administr...

Investigation Of Alternative Displays For Side Collision Avoidance Systems, Final Report

DOT National Transportation Integrated Search

1996-12-01

DRIVER-VEHICLE INTERFACE OR DVI, HUMAN FACTORS, DRIVER PREFERENCES, INTELLIGENT VEHICLE INITIATIVE OR IVI : SIDE COLLISION AVOIDANCE SYSTEMS (SCAS) ARE DESIGNED TO WARN OF IMPENDING COLLISIONS AND CAN DETECT NOT ONLY ADJACENT VEHICLES BUT VEHICLES...

Change detection in urban and rural driving scenes: Effects of target type and safety relevance on change blindness.

PubMed

Beanland, Vanessa; Filtness, Ashleigh J; Jeans, Rhiannon

2017-03-01

The ability to detect changes is crucial for safe driving. Previous research has demonstrated that drivers often experience change blindness, which refers to failed or delayed change detection. The current study explored how susceptibility to change blindness varies as a function of the driving environment, type of object changed, and safety relevance of the change. Twenty-six fully-licenced drivers completed a driving-related change detection task. Changes occurred to seven target objects (road signs, cars, motorcycles, traffic lights, pedestrians, animals, or roadside trees) across two environments (urban or rural). The contextual safety relevance of the change was systematically manipulated within each object category, ranging from high safety relevance (i.e., requiring a response by the driver) to low safety relevance (i.e., requiring no response). When viewing rural scenes, compared with urban scenes, participants were significantly faster and more accurate at detecting changes, and were less susceptible to "looked-but-failed-to-see" errors. Interestingly, safety relevance of the change differentially affected performance in urban and rural environments. In urban scenes, participants were more efficient at detecting changes with higher safety relevance, whereas in rural scenes the effect of safety relevance has marginal to no effect on change detection. Finally, even after accounting for safety relevance, change blindness varied significantly between target types. Overall the results suggest that drivers are less susceptible to change blindness for objects that are likely to change or move (e.g., traffic lights vs. road signs), and for moving objects that pose greater danger (e.g., wild animals vs. pedestrians). Copyright © 2017 Elsevier Ltd. All rights reserved.

Detection of driving fatigue by using noncontact EMG and ECG signals measurement system.

PubMed

Fu, Rongrong; Wang, Hong

2014-05-01

Driver fatigue can be detected by constructing a discriminant mode using some features obtained from physiological signals. There exist two major challenges of this kind of methods. One is how to collect physiological signals from subjects while they are driving without any interruption. The other is to find features of physiological signals that are of corresponding change with the loss of attention caused by driver fatigue. Driving fatigue is detected based on the study of surface electromyography (EMG) and electrocardiograph (ECG) during the driving period. The noncontact data acquisition system was used to collect physiological signals from the biceps femoris of each subject to tackle the first challenge. Fast independent component analysis (FastICA) and digital filter were utilized to process the original signals. Based on the statistical analysis results given by Kolmogorov-Smirnov Z test, the peak factor of EMG (p < 0.001) and the maximum of the cross-relation curve of EMG and ECG (p < 0.001) were selected as the combined characteristic to detect fatigue of drivers. The discriminant criterion of fatigue was obtained from the training samples by using Mahalanobis distance, and then the average classification accuracy was given by 10-fold cross-validation. The results showed that the method proposed in this paper can give well performance in distinguishing the normal state and fatigue state. The noncontact, onboard vehicle drivers' fatigue detection system was developed to reduce fatigue-related risks.

Deep Learning-Based Gaze Detection System for Automobile Drivers Using a NIR Camera Sensor

PubMed Central

Naqvi, Rizwan Ali; Arsalan, Muhammad; Batchuluun, Ganbayar; Yoon, Hyo Sik; Park, Kang Ryoung

2018-01-01

A paradigm shift is required to prevent the increasing automobile accident deaths that are mostly due to the inattentive behavior of drivers. Knowledge of gaze region can provide valuable information regarding a driver’s point of attention. Accurate and inexpensive gaze classification systems in cars can improve safe driving. However, monitoring real-time driving behaviors and conditions presents some challenges: dizziness due to long drives, extreme lighting variations, glasses reflections, and occlusions. Past studies on gaze detection in cars have been chiefly based on head movements. The margin of error in gaze detection increases when drivers gaze at objects by moving their eyes without moving their heads. To solve this problem, a pupil center corneal reflection (PCCR)-based method has been considered. However, the error of accurately detecting the pupil center and corneal reflection center is increased in a car environment due to various environment light changes, reflections on glasses surface, and motion and optical blurring of captured eye image. In addition, existing PCCR-based methods require initial user calibration, which is difficult to perform in a car environment. To address this issue, we propose a deep learning-based gaze detection method using a near-infrared (NIR) camera sensor considering driver head and eye movement that does not require any initial user calibration. The proposed system is evaluated on our self-constructed database as well as on open Columbia gaze dataset (CAVE-DB). The proposed method demonstrated greater accuracy than the previous gaze classification methods. PMID:29401681

Temperature and behavioral responses of squirrel monkeys to 2Gz acceleration

NASA Technical Reports Server (NTRS)

Fuller, C. A.; Tremor, J.; Connolly, J. P.; Williams, B. A.

1982-01-01

This study examines the responses of squirrel monkeys to acute +2Gz exposure. Body temperature responses of loosely restrained animals were recorded via a thermistor in the colon. Behavioral responses were recorded by video monitoring. After baseline recording at 1G, monkeys were exposed to 2G for 60 min. The body temperature started to fall within 10 min of the onset of centrifugation and declined an average of 1.4 C in 60 min. This is in contrast to a stable body temperature during the control period. Further, after a few minutes at 2G, the animals became drowsy and appeared to fall asleep. During the control period, however, they were alert and continually shifting their gaze about the cage. Thus, primates are susceptible to hypergravic fields in the +Gz orientation. The depression in primate body temperature was consistent and significant. Further, the observed drowsiness in this study has significant ramifications regarding alertness and performance in man.

Evaluation of an active wildlife-sensing and driver warning system at Trapper's Point.

DOT National Transportation Integrated Search

2009-04-01

Collisions with wildlife are a serious concern on American highways. In Wyoming, the concern has prompted the Wyoming Department of Transportation : to construct an experimental wildlife detection and driver warning system at Trappers Point, north...

Combating the drug-impaired driver : a prescription for safer highways.

DOT National Transportation Integrated Search

1985-01-01

In recent years, the Commonwealth of Virginia has increased its efforts to improve highway safety by combating the problems created by drunken drivers. However, law enforcement officials still face major obstacles in their efforts to detect and prose...

EEG-Based Detection of Braking Intention Under Different Car Driving Conditions

PubMed Central

Hernández, Luis G.; Mozos, Oscar Martinez; Ferrández, José M.; Antelis, Javier M.

2018-01-01

The anticipatory recognition of braking is essential to prevent traffic accidents. For instance, driving assistance systems can be useful to properly respond to emergency braking situations. Moreover, the response time to emergency braking situations can be affected and even increased by different driver's cognitive states caused by stress, fatigue, and extra workload. This work investigates the detection of emergency braking from driver's electroencephalographic (EEG) signals that precede the brake pedal actuation. Bioelectrical signals were recorded while participants were driving in a car simulator while avoiding potential collisions by performing emergency braking. In addition, participants were subjected to stress, workload, and fatigue. EEG signals were classified using support vector machines (SVM) and convolutional neural networks (CNN) in order to discriminate between braking intention and normal driving. Results showed significant recognition of emergency braking intention which was on average 71.1% for SVM and 71.8% CNN. In addition, the classification accuracy for the best participant was 80.1 and 88.1% for SVM and CNN, respectively. These results show the feasibility of incorporating recognizable driver's bioelectrical responses into advanced driver-assistance systems to carry out early detection of emergency braking situations which could be useful to reduce car accidents. PMID:29910722

A telephoto camera system with shooting direction control by gaze detection

NASA Astrophysics Data System (ADS)

Teraya, Daiki; Hachisu, Takumi; Yendo, Tomohiro

2015-05-01

For safe driving, it is important for driver to check traffic conditions such as traffic lights, or traffic signs as early as soon. If on-vehicle camera takes image of important objects to understand traffic conditions from long distance and shows these to driver, driver can understand traffic conditions earlier. To take image of long distance objects clearly, the focal length of camera must be long. When the focal length is long, on-vehicle camera doesn't have enough field of view to check traffic conditions. Therefore, in order to get necessary images from long distance, camera must have long-focal length and controllability of shooting direction. In previous study, driver indicates shooting direction on displayed image taken by a wide-angle camera, a direction controllable camera takes telescopic image, and displays these to driver. However, driver uses a touch panel to indicate the shooting direction in previous study. It is cause of disturb driving. So, we propose a telephoto camera system for driving support whose shooting direction is controlled by driver's gaze to avoid disturbing drive. This proposed system is composed of a gaze detector and an active telephoto camera whose shooting direction is controlled. We adopt non-wear detecting method to avoid hindrance to drive. The gaze detector measures driver's gaze by image processing. The shooting direction of the active telephoto camera is controlled by galvanometer scanners and the direction can be switched within a few milliseconds. We confirmed that the proposed system takes images of gazing straight ahead of subject by experiments.

Brainwave Monitoring Software Improves Distracted Minds

NASA Technical Reports Server (NTRS)

2014-01-01

Neurofeedback technology developed at Langley Research Center to monitor pilot awareness inspired Peter Freer to develop software for improving student performance. His company, Fletcher, North Carolina-based Unique Logic and Technology Inc., has gone on to develop technology for improving workplace and sports performance, monitoring drowsiness, and encouraging relaxation.

Factor Structure of a Sluggish Cognitive Tempo Scale in Clinically-Referred Children

ERIC Educational Resources Information Center

Jacobson, Lisa A.; Murphy-Bowman, Sarah C.; Pritchard, Alison E.; Tart-Zelvin, Ariana; Zabel, T. Andrew; Mahone, E. Mark

2012-01-01

"Sluggish cognitive tempo" (SCT) is a construct hypothesized to describe a constellation of behaviors that includes daydreaming, lethargy, drowsiness, difficulty sustaining attention, and underactivity. Although the construct has been inconsistently defined, measures of SCT have shown associations with symptoms of attention-deficit/hyperactivity…

The involvement of prescribed drugs in road trauma.

PubMed

Drummer, Olaf H; Yap, Suwan

2016-08-01

Coroners files and toxicological records of fatally-injured drivers in Victoria from 2000 to 2006 and from 2007 to 2013 were reviewed in separate studies to establish the role of prescribed drugs on crash risk. 2638 driver fatalities were included in the study, which represented over 97% of all driver fatalities in this period. The detection limits of the drugs were at the low end of those seen with common illicit drugs or prescribed drugs. Drugs of any type were found in 34.4% of the study group, medicinal drugs 21.2%, and alcohol (≥0.05 gram/100mL) was found in 24.8%. The prevalence of the most common drugs detected that are legally available by prescription were anti-depressants (7.9%), benzodiazepines (7.0%), opiates/opioids (6.6%), and sedating anti-histamines (1.1%). Each driver was assessed for responsibility using a previously published and validated method. The crash risk of drivers taking opioids, benzodiazepines, or anti-depressants (primarily the serotonin reuptake inhibitors), were not significantly over-represented compared to the drug-free control group, although there was a suggestion of increased crash risk for benzodiazepines. Crash risk was elevated for drivers using cannabis (by presence of THC in blood at>2ng/mL) and amphetamines. These data show that drivers using medicinal drugs alone are unlikely to show significant crash risk even if drugs are potentially impairing. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A Pooled Sequencing Approach Identifies a Candidate Meiotic Driver in Drosophila

PubMed Central

Wei, Kevin H.-C.; Reddy, Hemakumar M.; Rathnam, Chandramouli; Lee, Jimin; Lin, Deanna; Ji, Shuqing; Mason, James M.; Clark, Andrew G.; Barbash, Daniel A.

2017-01-01

Meiotic drive occurs when a selfish element increases its transmission frequency above the Mendelian ratio by hijacking the asymmetric divisions of female meiosis. Meiotic drive causes genomic conflict and potentially has a major impact on genome evolution, but only a few drive loci of large effect have been described. New methods to reliably detect meiotic drive are therefore needed, particularly for discovering moderate-strength drivers that are likely to be more prevalent in natural populations than strong drivers. Here, we report an efficient method that uses sequencing of large pools of backcross (BC1) progeny to test for deviations from Mendelian segregation genome-wide with single-nucleotide polymorphisms (SNPs) that distinguish the parental strains. We show that meiotic drive can be detected by a characteristic pattern of decay in distortion of SNP frequencies, caused by recombination unlinking the driver from distal loci. We further show that control crosses allow allele-frequency distortion caused by meiotic drive to be distinguished from distortion resulting from developmental effects. We used this approach to test whether chromosomes with extreme telomere-length differences segregate at Mendelian ratios, as telomeric regions are a potential hotspot for meiotic drive due to their roles in meiotic segregation and multiple observations of high rates of telomere sequence evolution. Using four different pairings of long and short telomere strains, we find no evidence that extreme telomere-length variation causes meiotic drive in Drosophila. However, we identify one candidate meiotic driver in a centromere-linked region that shows an ∼8% increase in transmission frequency, corresponding to a ∼54:46 segregation ratio. Our results show that candidate meiotic drivers of moderate strength can be readily detected and localized in pools of BC1 progeny. PMID:28258181

Prevalence of psychoactive substances, alcohol and illicit drugs, in Spanish drivers: A roadside study in 2015.

PubMed

Domingo-Salvany, Antonia; Herrero, M Jesús; Fernandez, Beatriz; Perez, Julio; Del Real, Pilar; González-Luque, Juan Carlos; de la Torre, Rafael

2017-09-01

A survey was conducted during 2015 to monitor psychoactive substance use in a sample of drivers in Spanish roads and cities. Traffic police officers recruited drivers at sites carefully chosen to achieve representativeness of the driver population. A brief questionnaire included the date, time, and personal and driving patterns data. Alcohol use was ascertained through ethanol breath test at the roadside and considered positive if concentrations >0.05mg alcohol/L were detected. Four drug classes were assessed on-site through an oral fluid screening test that, if positive, was confirmed through a second oral fluid sample at a reference laboratory. Laboratory confirmation analyses screened for 26 psychoactive substances. To evaluate the association between drug findings and age, sex, road type (urban/interurban), and period of the week (weekdays, weeknights, weekend days, weekend nights), logistic regression analyses were done (overall, and separately for alcohol, cannabis and cocaine). A total of 2744 drivers, mean age of 37.5 years, 77.8% men, were included. Overall, 11.6% of the drivers had at least one positive finding to the substances assessed. Substances more frequently testing positive were cannabis (7.5%), cocaine (4.7%) and alcohol (2.6%). More than one substance was detected in 4% of the subjects. The proportion of positive results decreased with age, and was more likely among men and on urban roads. The pattern for alcohol use was similar but did not change with age and increased among drivers recruited at night. Cannabis was more likely to be detected at younger ages and cocaine was associated with night driving. Alcohol use before driving has decreased over the last decade; however, the consumption of other illegal drugs seems to have increased. The pattern of illegal psychoactive substance observed is similar to that declared in surveys of the general population of adults. Copyright © 2017. Published by Elsevier B.V.

Tracking wakefulness as it fades: Micro-measures of alertness.

PubMed

Jagannathan, Sridhar R; Ezquerro-Nassar, Alejandro; Jachs, Barbara; Pustovaya, Olga V; Bareham, Corinne A; Bekinschtein, Tristan A

2018-08-01

A major problem in psychology and physiology experiments is drowsiness: around a third of participants show decreased wakefulness despite being instructed to stay alert. In some non-visual experiments participants keep their eyes closed throughout the task, thus promoting the occurrence of such periods of varying alertness. These wakefulness changes contribute to systematic noise in data and measures of interest. To account for this omnipresent problem in data acquisition we defined criteria and code to allow researchers to detect and control for varying alertness in electroencephalography (EEG) experiments under eyes-closed settings. We first revise a visual-scoring method developed for detection and characterization of the sleep-onset process, and adapt the same for detection of alertness levels. Furthermore, we show the major issues preventing the practical use of this method, and overcome these issues by developing an automated method (micro-measures algorithm) based on frequency and sleep graphoelements, which are capable of detecting micro variations in alertness. The validity of the micro-measures algorithm was verified by training and testing using a dataset where participants are known to fall asleep. In addition, we tested generalisability by independent validation on another dataset. The methods developed constitute a unique tool to assess micro variations in levels of alertness and control trial-by-trial retrospectively or prospectively in every experiment performed with EEG in cognitive neuroscience under eyes-closed settings. Copyright © 2018. Published by Elsevier Inc.

Real-time EEG-based detection of fatigue driving danger for accident prediction.

PubMed

Wang, Hong; Zhang, Chi; Shi, Tianwei; Wang, Fuwang; Ma, Shujun

2015-03-01

This paper proposes a real-time electroencephalogram (EEG)-based detection method of the potential danger during fatigue driving. To determine driver fatigue in real time, wavelet entropy with a sliding window and pulse coupled neural network (PCNN) were used to process the EEG signals in the visual area (the main information input route). To detect the fatigue danger, the neural mechanism of driver fatigue was analyzed. The functional brain networks were employed to track the fatigue impact on processing capacity of brain. The results show the overall functional connectivity of the subjects is weakened after long time driving tasks. The regularity is summarized as the fatigue convergence phenomenon. Based on the fatigue convergence phenomenon, we combined both the input and global synchronizations of brain together to calculate the residual amount of the information processing capacity of brain to obtain the dangerous points in real time. Finally, the danger detection system of the driver fatigue based on the neural mechanism was validated using accident EEG. The time distributions of the output danger points of the system have a good agreement with those of the real accident points.

Limits of Spatial Attention in Three-Dimensional Space and Dual-task Driving Performance

PubMed Central

Andersen, George J.; Ni, Rui; Bian, Zheng; Kang, Julie

2010-01-01

The present study examined the limits of spatial attention while performing two driving relevant tasks that varied in depth. The first task was to maintain a fixed headway distance behind a lead vehicle that varied speed. The second task was to detect a light-change target in an array of lights located above the roadway. In Experiment 1 the light detection task required drivers to encode color and location. The results indicated that reaction time to detect a light-change target increased and accuracy decreased as a function of the horizontal location of the light-change target and as a function of the distance from the driver. In a second experiment the light change task was changed to a singleton search (detect the onset of a yellow light) and the workload of the car following task was systematically varied. The results of Experiment 2 indicated that RT increased as a function of task workload, the 2D position of the light-change target and the distance of the light-change target. A multiple regression analysis indicated that the effect of distance on light detection performance was not due to changes in the projected size of the light target. In Experiment 3 we found that the distance effect in detecting a light change could not be explained by the location of eye fixations. The results demonstrate that when drivers attend to a roadway scene attention is limited in three-dimensional space. These results have important implications for developing tests for assessing crash risk among drivers as well as the design of in vehicle technologies such as head-up displays. PMID:21094336

Identifying types of drug intoxication : laboratory evaluation of a subject-examination procedure

DOT National Transportation Integrated Search

1985-05-01

The Los Angeles Police Department (LAPD) has developed a rating procedures for use in detecting drug-impaired drivers. The purpose of the rating procedures is to determine whether the driver is impaired and to identify the responsible drug class (e.g...

Complex Cognitive Performance and Antihistamine Use

DTIC Science & Technology

1990-04-01

22 Antihistamine Use and Sedation ...........................................24 Antihistamine Use and Physiological Measures...Reactivity and Sedation in Healthy Volunteers after Administration of Hismanal, Alone or in Combination with Central Nervous System Depressants...cross the blood-brain barrier easily, resulting in central nervous system effects such as sedation , drowsiness, and altered psychomotor performance

Amplicon-based next-generation sequencing of plasma cell-free DNA for detection of driver and resistance mutations in advanced non-small cell lung cancer.

PubMed

Guibert, N; Hu, Y; Feeney, N; Kuang, Y; Plagnol, V; Jones, G; Howarth, K; Beeler, J F; Paweletz, C P; Oxnard, G R

2018-04-01

Genomic analysis of plasma cell-free DNA is transforming lung cancer care; however, available assays are limited by cost, turnaround time, and imperfect accuracy. Here, we study amplicon-based plasma next-generation sequencing (NGS), rather than hybrid-capture-based plasma NGS, hypothesizing this would allow sensitive detection and monitoring of driver and resistance mutations in advanced non-small cell lung cancer (NSCLC). Plasma samples from patients with NSCLC and a known targetable genotype (EGFR, ALK/ROS1, and other rare genotypes) were collected while on therapy and analyzed blinded to tumor genotype. Plasma NGS was carried out using enhanced tagged amplicon sequencing of hotspots and coding regions from 36 genes, as well as intronic coverage for detection of ALK/ROS1 fusions. Diagnostic accuracy was compared with plasma droplet digital PCR (ddPCR) and tumor genotype. A total of 168 specimens from 46 patients were studied. Matched plasma NGS and ddPCR across 120 variants from 80 samples revealed high concordance of allelic fraction (R2 = 0.95). Pretreatment, sensitivity of plasma NGS for the detection of EGFR driver mutations was 100% (30/30), compared with 87% for ddPCR (26/30). A full spectrum of rare driver oncogenic mutations could be detected including sensitive detection of ALK/ROS1 fusions (8/9 detected, 89%). Studying 25 patients positive for EGFR T790M that developed resistance to osimertinib, 15 resistance mechanisms could be detected including tertiary EGFR mutations (C797S, Q791P) and mutations or amplifications of non-EGFR genes, some of which could be detected pretreatment or months before progression. This blinded analysis demonstrates the ability of amplicon-based plasma NGS to detect a full range of targetable genotypes in NSCLC, including fusion genes, with high accuracy. The ability of plasma NGS to detect a range of preexisting and acquired resistance mechanisms highlights its potential value as an alternative to single mutation digital PCR-based plasma assays for personalizing treatment of TKI resistance in lung cancer.

Wireless sleep monitoring headband to identify sleep and track fatigue

NASA Astrophysics Data System (ADS)

Ramasamy, Mouli; Oh, Sechang; Varadan, Vijay K.

2014-04-01

Detection of sleepiness and drowsiness in human beings has been a daunting task for both engineering and medical technologies. Accuracy, precision and promptness of detection have always been an issue that has to be dealt by technologists. Commonly, the rudimentary bio potential signals - ECG, EOG, EEG and EMG are used to classify and discriminate sleep from being awake. However, the potential drawbacks may be high false detections, low precision, obtrusiveness, aftermath analysis, etc. To overcome the disadvantages, this paper proposes the design of a wireless and a real time monitoring system to track sleep and detect fatigue. This concept involves the use of EOG and EEG to measure the blink rate and asses the person's condition. In this user friendly and intuitive approach, EOG and EEG signals are obtained by the dry gold wire nano-sensors fabricated on the inner side of a flexible headband. The acquired signals are then electrically transmitted to the data processing and transmission unit, which transmits the processed data to the receiver/monitoring module through WCDMA/GSM communication. This module is equipped with a software program to process, feature extract, analyze, display and store the information. Thereby, immediate detection of a person falling asleep is made feasible and, tracking the sleep cycle continuously provides an insight about the experienced fatigue level. The novel approach of using a wireless, real time, dry sensor on a flexible substrate reduces the obtrusiveness, and techniques adopted in the electronics and software facilitates and substantial increase in efficiency, accuracy and precision.

Effect of directional speech warnings on road hazard detection.

PubMed

Serrano, Jesús; Di Stasi, Leandro L; Megías, Alberto; Catena, Andrés

2011-12-01

In the last 2 decades, cognitive science and the transportation psychology field have dedicated a lot of effort to designing advanced driver support systems. Verbal warning systems are increasingly being implemented in modern automobiles in an effort to increase road safety. The study presented here investigated the impact of directional speech alert messages on the participants' speed to judge whether or not naturalistic road scenes depicted a situation of impending danger. Thirty-eight volunteers performed a computer-based key-press reaction time task. Findings indicated that semantic content of verbal warning signals can be used for increasing driving safety and improving hazard detection. Furthermore, the classical result regarding signal accuracy is confirmed: directional informative speech messages lead to faster hazard detection compared to drivers who received a high rate of false alarms. Notwithstanding some study limitations (lack of driver experience and low ecological validity), this evidence could provide important information for the specification of future Human-Machine-interaction (HMI) design guidelines.

Impaired-Driving Prevalence Among US High School Students: Associations With Substance Use and Risky Driving Behaviors

PubMed Central

Li, Kaigang; Simons-Morton, Bruce G.; Hingson, Ralph

2013-01-01

Objectives. We examined the prevalence of impaired driving among US high school students and associations with substance use and risky driving behavior. Methods. We assessed driving while alcohol or drug impaired (DWI) and riding with alcohol- or drug-impaired drivers (RWI) in a nationally representative sample of 11th-grade US high school students (n = 2431). We examined associations with drinking and binge drinking, illicit drug use, risky driving, and demographic factors using multivariate sequential logistic regression analysis. Results. Thirteen percent of 11th-grade students reported DWI at least 1 of the past 30 days, and 24% reported RWI at least once in the past year. Risky driving was positively associated with DWI (odds ratio [OR] = 1.25; P < .001) and RWI (OR = 1.09; P < .05), controlling for binge drinking (DWI: OR = 3.17; P < .01; RWI: OR = 6.12; P < .001) and illicit drug use (DWI: OR = 5.91; P < .001; RWI: OR = 2.29; P = .05). DWI was higher for adolescents who drove after midnight (OR = 15.7), drove while sleepy or drowsy (OR = 8.6), read text messages (OR = 11.8), sent text messages (OR = 5.0), and made cell phone calls (OR = 3.2) while driving. Conclusions. Our findings suggest the need for comprehensive approaches to the prevention of DWI, RWI, and other risky driving behavior. PMID:24028236

The effects of mutational processes and selection on driver mutations across cancer types.

PubMed

Temko, Daniel; Tomlinson, Ian P M; Severini, Simone; Schuster-Böckler, Benjamin; Graham, Trevor A

2018-05-10

Epidemiological evidence has long associated environmental mutagens with increased cancer risk. However, links between specific mutation-causing processes and the acquisition of individual driver mutations have remained obscure. Here we have used public cancer sequencing data from 11,336 cancers of various types to infer the independent effects of mutation and selection on the set of driver mutations in a cancer type. First, we detect associations between a range of mutational processes, including those linked to smoking, ageing, APOBEC and DNA mismatch repair (MMR) and the presence of key driver mutations across cancer types. Second, we quantify differential selection between well-known alternative driver mutations, including differences in selection between distinct mutant residues in the same gene. These results show that while mutational processes have a large role in determining which driver mutations are present in a cancer, the role of selection frequently dominates.

Skills of novices early trained or traditionaly trained versus experienced drivers confronted to simulated urban accidents' scenarios.

PubMed

Berthelon, Catherine; Damm, Loïc

2012-01-01

In order to prevent the over-representation of young drivers in car crashes, France instated an early driver training from the age of 16, but the positive effects of this opportunity have not yet been proven. Three groups of male drivers (12 subjects each) were confronted with some prototypical accident scenarios introduced in a simulated urban circuit. The first and second groups were composed of young drivers having less than one month of driving licence; twelve have had a traditional learning course, and twelve had followed, in addition to the initial course, an early driver training under the supervision of an adult. The third group was composed of experienced drivers. Strategies of the three groups were analyzed through their response time, speed and maneuvers. No difference appeared across groups regarding obstacle detection. But traditionally-trained drivers' position control was more conservative than the two others groups, which were more likely to involve efficient evasive action. The exposure gained during early training could thus increase the development of visuo-motor coordination and involve better skills in case of difficult situations. Others accidents' scenarios could be used to confront young drivers with difficult situations not commonly encountered in natural driving.

A non-contact capacitance based electrocardiograph and associated heart-rate detection using enhanced Fourier interpolation method.

PubMed

Kumar Thakur, Rupak; Anoop, C S

2015-08-01

Cardio-vascular health monitoring has gained considerable attention in the recent years. Principle of non-contact capacitive electrocardiograph (ECG) and its applicability as a valuable, low-cost, easy-to-use scheme for cardio-vascular health monitoring has been demonstrated in some recent research papers. In this paper, we develop a complete non-contact ECG system using a suitable front-end electronic circuit and a heart-rate (HR) measurement unit using enhanced Fourier interpolation technique. The front-end electronic circuit is realized using low-cost, readily available components and the proposed HR measurement unit is designed to achieve fairly accurate results. The entire system has been extensively tested to verify its efficacy and test results show that the developed system can estimate HR with an accuracy of ±2 beats. Detailed tests have been conducted to validate the performance of the system for different cloth thicknesses of the subject. Some basic tests which illustrate the application of the proposed system for heart-rate variability estimation has been conducted and results reported. The developed system can be used as a portable, reliable, long-term cardiac health monitoring device and can be extended to human drowsiness detection.

Hazard detection in noise-related incidents - the role of driving experience with battery electric vehicles.

PubMed

Cocron, Peter; Bachl, Veronika; Früh, Laura; Koch, Iris; Krems, Josef F

2014-12-01

The low noise emission of battery electric vehicles (BEVs) has led to discussions about how to address potential safety issues for other road users. Legislative actions have already been undertaken to implement artificial sounds. In previous research, BEV drivers reported that due to low noise emission they paid particular attention to pedestrians and bicyclists. For the current research, we developed a hazard detection task to test whether drivers with BEV experience respond faster to incidents, which arise due to the low noise emission, than inexperienced drivers. The first study (N=65) revealed that BEV experience only played a minor role in drivers' response to hazards resulting from low BEV noise. The tendency to respond, reaction times and hazard evaluations were similar among experienced and inexperienced BEV drivers; only small trends in the assumed direction were observed. Still, both groups clearly differentiated between critical and non-critical scenarios and responded accordingly. In the second study (N=58), we investigated additionally if sensitization to low noise emission of BEVs had an effect on hazard perception in incidents where the noise difference is crucial. Again, participants in all groups differentiated between critical and non-critical scenarios. Even though trends in response rates and latencies occurred, experience and sensitization to low noise seemed to only play a minor role in detecting hazards due to low BEV noise. An additional global evaluation of BEV noise further suggests that even after a short test drive, the lack of noise is perceived more as a comfort feature than a safety threat. Copyright © 2014 Elsevier Ltd. All rights reserved.

Effect of clebopride on lower esophageal sphincter pressure.

PubMed

Ribeiro, V; da Silva, A L; Castro, L de P

1981-01-01

In 12 individuals without gastrointestinal symptoms, the IV administration of metoclopramide and of clebopride produced both a significant increase on the lower esophageal sphincter pressure. The increase induced by clebopride was significantly higher than that induced by metoclopramide. The tolerability of clebopride was satisfactory with just mild drowsiness being noted in most cases.

49 CFR Appendix D to Part 228 - Guidance on Fatigue Management Plans

Code of Federal Regulations, 2012 CFR

2012-10-01

... treatment of any medical condition that may affect alertness or fatigue, including sleep disorders; (3... employee fatigue and cumulative sleep loss; (5) Methods to minimize accidents and incidents that occur as a... drowsiness and fatigue while an employee is on duty; (7) Opportunities to obtain restful sleep at lodging...

49 CFR Appendix D to Part 228 - Guidance on Fatigue Management Plans

Code of Federal Regulations, 2013 CFR

2013-10-01

... treatment of any medical condition that may affect alertness or fatigue, including sleep disorders; (3... employee fatigue and cumulative sleep loss; (5) Methods to minimize accidents and incidents that occur as a... drowsiness and fatigue while an employee is on duty; (7) Opportunities to obtain restful sleep at lodging...

49 CFR Appendix D to Part 228 - Guidance on Fatigue Management Plans

Code of Federal Regulations, 2014 CFR

2014-10-01

... treatment of any medical condition that may affect alertness or fatigue, including sleep disorders; (3... employee fatigue and cumulative sleep loss; (5) Methods to minimize accidents and incidents that occur as a... drowsiness and fatigue while an employee is on duty; (7) Opportunities to obtain restful sleep at lodging...

SAM survey on "drugs and fatal accidents": search of substances consumed and comparison between drivers involved under the influence of alcohol or cannabis.

PubMed

Biecheler, Marie-Berthe; Peytavin, Jean-François; Facy, Françoise; Martineau, Hélène

2008-03-01

A survey was conducted to produce reliable epidemiological data concerning the role played by alcohol and drugs in fatal road accidents in France. The aims are to describe the conduct of the survey, evaluate the overall quality of the findings, and analyze the substances consumed by the involved drivers. A comparison between drivers involved under the influence of alcohol only, cannabis only, or both substances is emphasized. By a June 1999 law, all drivers in France involved in an immediate fatality accident between October 2001 and 2003 had to undergo a urine test and, if that was not possible or the test proved positive, had a blood sample taken in order to test for drugs (cannabis, cocaine, heroin, amphetamines). The results were combined with the usual procedures of the police force, which include the results of tests for illegal alcohol levels. A unique and reliable set of accident data on the role of drugs was thus compiled for epidemiological purposes: 10,000 accident reports involving over 17,000 drivers were analyzed. The responsibility level of each driver involved in an accident was determined. Results were generated for a representative sample of about 11,000 drivers. Alcohol levels above the legal limit (0.5 g/L of blood) were found in 21% of all drivers involved in accidents (killed, injured, or unharmed). Cannabis headed the list of illicit drugs detected, with a prevalence of 6.8% (THC > or = 1 ng/mL); it was present in the under-35s and especially the under-25s. About 40% of drivers under the influence of cannabis also had an illegal alcohol level. The other drugs, whether alone or in association with cannabis, are relatively rare. Accident characteristics of drivers detected positive for cannabis only are markedly different from drivers under the influence of alcohol. The overrepresentation of drivers responsible, from 1.7 over the whole population, rises to 2.3 for cannabis alone (THC > or = 1 ng/mL), to 9.4 for alcohol alone (> or =0.5 mg/L), and to 14.1 for the alcohol-cannabis combination. The high incidence (26%) of alcohol or drugs among the population of drivers involved in fatal accidents highlights the importance for road safety of the consumption of these substances. Alcohol remains the major risk at any age. Young drivers consuming alcohol and cannabis represent a priority target for prevention.

Positive emotion word use and longevity in famous deceased psychologists.

PubMed

Pressman, Sarah D; Cohen, Sheldon

2012-05-01

This study examined whether specific types of positive and negative emotional words used in the autobiographies of well-known deceased psychologists were associated with longevity. For each of the 88 psychologists, the percent of emotional words used in writing was calculated and categorized by valence (positive or negative) and arousal (activated [e.g., lively, anxious] or not activated [e.g., calm, drowsy]) based on existing emotion scales and models of emotion categorization. After controlling for sex, year of publication, health (based on disclosed illness in autobiography), native language, and year of birth, the use of more activated positive emotional words (e.g., lively, vigorous, attentive, humorous) was associated with increased longevity. Negative terms (e.g., angry, afraid, drowsy, sluggish) and unactivated positive terms (e.g., peaceful, calm) were not related to longevity. The association of activated positive emotions with longevity was also independent of words indicative of social integration, optimism, and the other affect/activation categories. Results indicate that in writing, not every type of emotion correlates with longevity and that there may be value to considering different categories beyond emotional valence in health relevant outcomes.

Driving fatigue in professional drivers: a survey of truck and taxi drivers.

PubMed

Meng, Fanxing; Li, Shuling; Cao, Lingzhi; Li, Musen; Peng, Qijia; Wang, Chunhui; Zhang, Wei

2015-01-01

Fatigue among truck drivers has been studied extensively; however, less is known regarding the fatigue experience of taxi drivers in heavily populated metropolitan areas. This study aimed to compare the differences and similarities between truck and taxi driver fatigue to provide implications for the fatigue management and education of professional drivers. A sample of 274 truck drivers and 286 taxi drivers in Beijing was surveyed via a questionnaire, which included items regarding work characteristics, fatigue experience, accident information, attitude toward fatigue, and methods of counteracting fatigue. Driver fatigue was prevalent among professional drivers, and it was even more serious for taxi drivers. Taxi drivers reported more frequent fatigue experiences and were involved in more accidents. Among the contributing factors to fatigue, prolonged driving time was the most important factor identified by both driver groups. Importantly, the reason for the engagement in prolonged driving was neither due to the lack of awareness concerning the serious outcome of fatigue driving nor because of their poor detection of fatigue. The most probable reason was the optimism bias, as a result of which these professional drivers thought that fatigue was more serious for other drivers than for themselves, and they thought that they were effective in counteracting the effect of fatigue on their driving performance. Moreover, truck drivers tended to employ methods that require stopping to counteract fatigue, whereas taxi drivers preferred methods that were simultaneous with driving. Although both driver groups considered taking a nap as one of the most effective means to address fatigue, this method was not commonly used. Interestingly, these drivers were aware that the methods they frequently used were not the most effective means to counteract fatigue. This study provides knowledge on truck and taxi drivers' characteristics in fatigue experience, fatigue attitude, and fatigue countermeasures, and these findings have practical implications for the fatigue management and education of professional drivers.

Minimum Required Attention: A Human-Centered Approach to Driver Inattention.

PubMed

Kircher, Katja; Ahlstrom, Christer

2017-05-01

To propose a driver attention theory based on the notion of driving as a satisficing and partially self-paced task and, within this framework, present a definition for driver inattention. Many definitions of driver inattention and distraction have been proposed, but they are difficult to operationalize, and they are either unreasonably strict and inflexible or suffer from hindsight bias. Existing definitions of driver distraction are reviewed and their shortcomings identified. We then present the minimum required attention (MiRA) theory to overcome these shortcomings. Suggestions on how to operationalize MiRA are also presented. MiRA describes which role the attention of the driver plays in the shared "situation awareness of the traffic system." A driver is considered attentive when sampling sufficient information to meet the demands of the system, namely, that he or she fulfills the preconditions to be able to form and maintain a good enough mental representation of the situation. A driver should only be considered inattentive when information sampling is not sufficient, regardless of whether the driver is concurrently executing an additional task or not. The MiRA theory builds on well-established driver attention theories. It goes beyond available driver distraction definitions by first defining what a driver needs to be attentive to, being free from hindsight bias, and allowing the driver to adapt to the current demands of the traffic situation through satisficing and self-pacing. MiRA has the potential to provide the stepping stone for unbiased and operationalizable inattention detection and classification.

Carcass Persistence and Detectability: Reducing the Uncertainty Surrounding Wildlife-Vehicle Collision Surveys

PubMed Central

Santos-Reis, Margarida; Picanço de Figueiredo, Almir; Bager, Alex; Aguiar, Ludmilla M. S.

2016-01-01

Carcass persistence time and detectability are two main sources of uncertainty on roadkill surveys. In this study, we evaluate the influence of these uncertainties on roadkill surveys and estimates. To estimate carcass persistence time, three observers (including the driver) surveyed 114km by car on a monthly basis for two years, searching for wildlife-vehicle collisions (WVC). Each survey consisted of five consecutive days. To estimate carcass detectability, we randomly selected stretches of 500m to be also surveyed on foot by two other observers (total 292 walked stretches, 146 km walked). We expected that body size of the carcass, road type, presence of scavengers and weather conditions to be the main drivers influencing the carcass persistence times, but their relative importance was unknown. We also expected detectability to be highly dependent on body size. Overall, we recorded low median persistence times (one day) and low detectability (<10%) for all vertebrates. The results indicate that body size and landscape cover (as a surrogate of scavengers’ presence) are the major drivers of carcass persistence. Detectability was lower for animals with body mass less than 100g when compared to carcass with higher body mass. We estimated that our recorded mortality rates underestimated actual values of mortality by 2–10 fold. Although persistence times were similar to previous studies, the detectability rates here described are very different from previous studies. The results suggest that detectability is the main source of bias across WVC studies. Therefore, more than persistence times, studies should carefully account for differing detectability when comparing WVC studies. PMID:27806125

NASA direct detection laser diode driver

NASA Technical Reports Server (NTRS)

Seery, B. D.; Hornbuckle, C. A.

1989-01-01

TRW has developed a prototype driver circuit for GaAs laser diodes as part of the NASA/Goddard Space Flight Center's Direct Detection Laser Transceiver (DDLT) program. The circuit is designed to drive the laser diode over a range of user-selectable data rates from 1.7 to 220 Mbps, Manchester-encoded, while ensuring compatibility with 8-bit and quaternary pulse position modulation (QPPM) formats for simulating deep space communications. The resulting hybrid circuit has demonstrated 10 to 90 percent rise and fall times of less than 300 ps at peak currents exceeding 100 mA.

Mine countermeasures (MCM) sensor technology drivers

NASA Astrophysics Data System (ADS)

Skinner, David P.

1995-06-01

In recent years, MCM has moved to the forefront of the Navy's attention. This paper describes the general problems that drive the technology requirements of classical sea mine countermeasure (MCM) sensors for those working outside of this specialized area. Sensor requirements for MCM are compared with those for antisubmarine warfare. This highlights the unique environmental issues and crucial false target problems. The elimination of false targets, not mine detection, is the principal driver of MCM sensor requirements and places special emphasis on the technologies needed for the sequential operations of detection, classification, and identification.

Sleep-Wake Disturbances in Sedentary Community-Dwelling Elders With Functional Limitations

PubMed Central

Vaz Fragoso, Carlos A.; Miller, Michael E.; Fielding, Roger A.; King, Abby C.; Kritchevsky, Stephen B.; McDermott, Mary M.; Myers, Valerie; Newman, Anne B.; Pahor, Marco; Gill, Thomas M.

2014-01-01

OBJECTIVES To evaluate sleep-wake disturbances in sedentary community-dwelling elders with functional limitations. DESIGN Cross-sectional. SETTING Lifestyle Interventions and Independence in Elder (LIFE) Study. PARTICIPANTS 1635 community-dwelling persons, mean age 78.9, who spent <20 minutes/week in the past month of regular physical activity and <125 minutes/week of moderate physical activity, and had a Short Physical Performance Battery (SPPB) score <10. MEASUREMENTS Mobility was evaluated by the 400-meter walk time (slow gait speed defined as <0.8 m/s) and SPPB score (≤7 defined moderate-to-severe mobility impairment). Physical inactivity was defined by sedentary time, as percent of accelerometry wear time with activity <100 counts/min); top quartile established high sedentary time. Sleep-wake disturbances were evaluated by the Insomnia Severity Index (ISI) (range 0–28; ≥8 defined insomnia), Epworth Sleepiness Scale (ESS) (range 0–24; ≥10 defined daytime drowsiness), Pittsburgh Sleep Quality Index (PSQI) (range 0–21; >5 defined poor sleep quality), and Berlin Questionnaire (high risk of sleep apnea). RESULTS Prevalence rates were 43.5% for slow gait speed and 44.7% for moderate-to-severe mobility impairment, with 77.0% of accelerometry wear time spent as sedentary time. Prevalence rates were 33.0% for insomnia, 18.1% for daytime drowsiness, 47.8% for poor sleep quality, and 32.9% for high risk of sleep apnea. Participants with insomnia, daytime drowsiness, and poor sleep quality had mean values of 12.1 for ISI, 12.5 for ESS, and 9.2 for PSQI, respectively. In adjusted models, measures of mobility and physical inactivity were generally not associated with sleep-wake disturbances, using continuous or categorical variables. CONCLUSION In a large sample of sedentary community-dwelling elders with functional limitations, sleep-wake disturbances were prevalent but only mildly severe, and were generally not associated with mobility impairment or physical inactivity. PMID:24889836

Patient-reported symptoms during radiotherapy : Clinically relevant symptom burden in patients treated with palliative and curative intent.

PubMed

Körner, Philipp; Ehrmann, Katja; Hartmannsgruber, Johann; Metz, Michaela; Steigerwald, Sabrina; Flentje, Michael; van Oorschot, Birgitt

2017-07-01

The benefits of patient-reported symptom assessment combined with integrated palliative care are well documented. This study assessed the symptom burden of palliative and curative-intent radiation oncology patients. Prior to first consultation and at the end of RT, all adult cancer patients planned to receive fractionated percutaneous radiotherapy (RT) were asked to answer the Edmonton Symptom Assessment Scale (ESAS; nine symptoms from 0 = no symptoms to 10 = worst possible symptoms). Mean values were used for curative vs. palliative and pre-post comparisons, and the clinical relevance was evaluated (symptom values ≥ 4). Of 163 participating patients, 151 patients (90.9%) completed both surveys (116 curative and 35 palliative patients). Before beginning RT, 88.6% of palliative and 72.3% of curative patients showed at least one clinically relevant symptom. Curative patients most frequently named decreased general wellbeing (38.6%), followed by tiredness (35.0%), anxiety (32.4%), depression (30.0%), pain (26.3%), lack of appetite (23.5%), dyspnea (17.8%), drowsiness (8.0%) and nausea (6.1%). Palliative patients most frequently named decreased general wellbeing (62.8%), followed by pain (62.8%), tiredness (60.0%), lack of appetite (40.0%), anxiety (38.0%), depression (33.3%), dyspnea (28.5%), drowsiness (25.7%) and nausea (14.2%). At the end of RT, the proportion of curative and palliative patients with a clinically relevant symptom had increased significantly to 79.8 and 91.4%, respectively; whereas the proportion of patients reporting clinically relevant pain had decreased significantly (42.8 vs. 62.8%, respectively). Palliative patients had significantly increased tiredness. Curative patients reported significant increases in pain, tiredness, nausea, drowsiness, lack of appetite and restrictions in general wellbeing. Assessment of patient-reported symptoms was successfully realized in radiation oncology routine. Overall, both groups showed a high symptom burden. The results prove the need of systematic symptom assessment and programs for early integrated supportive and palliative care in radiation oncology.

Ventilation is unstable during drowsiness before sleep onset.

PubMed

Thomson, Stuart; Morrell, Mary J; Cordingley, Jeremy J; Semple, Stephen J

2005-11-01

Ventilation is unstable during drowsiness before sleep onset. We have studied the effects of transitory changes in cerebral state during drowsiness on breath duration and lung volume in eight healthy subjects in the absence of changes in airway resistance and fluctuations of ventilation and CO2 tension, characteristic of the onset of non-rapid eye movement sleep. A volume-cycled ventilator in the assist control mode was used to maintain CO2 tension close to that when awake. Changes in cerebral state were determined by the EEG on a breath-by-breath basis and classified as alpha or theta breaths. Breath duration and the pause in gas flow between the end of expiratory airflow and the next breath were computed for two alpha breaths which preceded a theta breath and for the theta breath itself. The group mean (SD) results for this alpha-to-theta transition was associated with a prolongation in breath duration from 5.2 (SD 1.3) to 13.0 s (SD 2.1) and expiratory pause from 0.7 (SD 0.4) to 7.5 s (SD 2.2). Because the changes in arterial CO2 tension (PaCO2) are unknown during the theta breaths, we made in two subjects a continuous record of PaCO2 in the radial artery. PaCO2 remained constant from the alpha breaths through to the expiratory period of the theta breath by which time the duration of breath was already prolonged, representing an immediate and altered ventilatory response to the prevailing PaCO2. In the eight subjects, the CO2 tension awake was 39.6 Torr (SD 2.3) and on assisted ventilation 38.0 Torr (1.4). We conclude that the ventilatory instability recorded in the present experiments is due to the apneic threshold for CO2 being at or just below that when awake.

The effect of age and comedication on lamotrigine clearance, tolerability, and efficacy.

PubMed

Arif, Hiba; Svoronos, Alexandra; Resor, Stanley R; Buchsbaum, Richard; Hirsch, Lawrence J

2011-10-01

To compare pharmacokinetics, tolerability, and efficacy of lamotrigine (LTG) in older versus younger adults. We studied 686 adult outpatients seen at our center over 5 years. We compared apparent clearance (CL) of LTG in the youngest (16-36 years; n = 247) and oldest (55-92 years; n = 155) tertiles. We analyzed one-year retention for younger and older adults newly started on LTG, frequency of adverse effects causing intolerability, and rates of specific adverse effects. We also investigated 6-month seizure freedom. Median LTG CL of older adults taking LTG in monotherapy was approximately 22% lower compared to younger adults (28.8 vs. 36.5 ml/h/kg; p < 0.001). LTG CL in older adults was lower compared to younger adults in patients on polytherapy and on polytherapy without enzyme inducers or valproate. One-year retention for LTG was comparable in older (78.1%, 121/155) and younger (72.4%, 179/247) adults. Intolerability to LTG was higher in older (34.8%) versus younger adults (24.2%; p = 0.005). Imbalance, drowsiness, and dizziness were common intolerable side effects in both groups. Older patients had higher rates of intolerability due to imbalance (16% vs. 4%), drowsiness (13% vs. 7%), and tremor (5% vs. 2%) compared with younger patients. Rates of 6-month seizure freedom were comparable, and small numbers of each group benefited from very high levels of LTG (>15 μg/ml). LTG CL in monotherapy in older adults is approximately 20% lower than in younger adults. For a given serum LTG level, older adults are twice as likely to have significant adverse effects compared to younger adults. Older patients are more likely to experience imbalance, drowsiness, and tremor than younger patients. Younger adults tolerate LTG better than older adults, but one-year retention is comparable. Some patients may benefit from high serum levels of LTG. Wiley Periodicals, Inc. © 2011 International League Against Epilepsy.

Anesthesia Practice and Clinical Trends in Interventional Radiology: A European Survey

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haslam, Philip J.; Yap, Bernard; Mueller, Peter R.

Purpose: To determine current European practice in interventional radiology regarding nursing care, anesthesia, and clinical care trends.Methods: A survey was sent to 977 European interventional radiologists to assess the use of sedoanalgesia, nursing care, monitoring equipment, pre- and postprocedural care, and clinical trends in interventional radiology. Patterns of sedoanalgesia were recorded for both vascular and visceral interventional procedures. Responders rated their preferred level of sedoanalgesia for each procedure as follows: (a) awake/alert, (b) drowsy/arousable, (c) asleep/arousable, (d) deep sedation, and (e) general anesthesia. Sedoanalgesic drugs and patient care trends were also recorded. A comparison was performed with data derived frommore » a similar survey of interventional practice in the United States.Results: Two hundred and forty-three of 977 radiologists responded (25%). The total number of procedures analyzed was 210,194. The majority (56%) of diagnostic and therapeutic vascular procedures were performed at the awake/alert level of sedation, 32% were performed at the drowsy/arousable level, and 12% at deeper levels of sedation. The majority of visceral interventional procedures were performed at the drowsy/arousable level of sedation (41%), 29% were performed at deeper levels of sedation, and 30% at the awake/alert level. In general, more sedoanalgesia is used in the United States. Eighty-three percent of respondents reported the use of a full-time radiology nurse, 67% used routine blood pressure/pulse oximetry monitoring, and 46% reported the presence of a dedicated recovery area. Forty-nine percent reported daily patient rounds, 30% had inpatient hospital beds, and 51% had day case beds.Conclusion: This survey shows clear differences in the use of sedation for vascular and visceral interventional procedures. Many, often complex, procedures are performed at the awake/alert level of sedation in Europe, whereas deeper levels of sedation are used in the United States. Trends toward making interventional radiology a clinical specialty are evident, with 51% of respondents having day case beds, and 30% having inpatient beds.« less

Predictors of Responses to Corticosteroids for Cancer-Related Fatigue in Advanced Cancer Patients: A Multicenter, Prospective, Observational Study.

PubMed

Matsuo, Naoki; Morita, Tatsuya; Matsuda, Yoshinobu; Okamoto, Kenichiro; Matsumoto, Yoshihisa; Kaneishi, Keisuke; Odagiri, Takuya; Sakurai, Hiroki; Katayama, Hideki; Mori, Ichiro; Yamada, Hirohide; Watanabe, Hiroaki; Yokoyama, Taro; Yamaguchi, Takashi; Nishi, Tomohiro; Shirado, Akemi; Hiramoto, Shuji; Watanabe, Toshio; Kohara, Hiroyuki; Shimoyama, Satofumi; Aruga, Etsuko; Baba, Mika; Sumita, Koki; Iwase, Satoru

2016-07-01

Although corticosteroids are widely used to relieve cancer-related fatigue (CRF), information regarding the factors predicting responses to corticosteroids remains limited. The aim of this study was to identify potential factors predicting responses to corticosteroids for CRF in advanced cancer patients. Inclusion criteria for this multicenter, prospective, observational study were patients who had metastatic or locally advanced cancer and had a fatigue intensity score of 4 or more on a 0-10 Numerical Rating Scale (NRS). Univariate and multivariate analyses were conducted to identify the factors predicting two-point reduction or more in NRS on day 3. Among 179 patients who received corticosteroids, 86 (48%; 95% CI 41%-56%) had a response with two-point reduction or more. Factors that significantly predicted responses were performance status score of 3 or more, Palliative Performance Scale score more than 40, absence of ascites, absence of drowsiness, absence of depression, serum albumin level greater than 3 mg/dL, serum sodium level greater than 135 mEq/L, and baseline NRS score greater than 5. A multivariate analysis showed that the independent factors predicting responses were baseline NRS score greater than 5 (odds ratio [OR] 6.6, 95% CI 2.8-15.4), Palliative Performance Scale score more than 40 (OR 4.4, 95% CI 2.1-9.3), absence of drowsiness (OR 3.4, 95% CI 1.7-6.9), absence of ascites (OR 2.3, 95% CI 1.1-4.7), and absence of pleural effusion (OR 2.2, 95% CI 1.0-5.0). Treatment responses to corticosteroids for CRF may be predicted by baseline symptom intensity, performance status, drowsiness, and severity of fluid retention symptoms. Larger prospective studies are needed to confirm these results. Copyright © 2016 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

Frequency and irregularity of heart rate in drivers suspected of driving under the influence of cannabis.

PubMed

Khiabani, Hassan Z; Mørland, Jørg; Bramness, Jørgen G

2008-12-01

Delta 9-tetrahydrocannabinol (THC) is the major active component of cannabis. Cardiovascular effects of THC have previously been reported: tachycardia after intake, but also bradycardia at higher doses. The purpose of this study was, firstly, to investigate the frequency and irregularity of heart rate in a group of cannabis users in their natural surroundings. We also compared THC-positive drivers with a regular pulse with THC-positive drivers with an irregular pulse. The division of Forensic Toxicology and Drug Abuse (DFTDA) at the Norwegian Institute of Public Heath analyzes blood samples from all drivers suspected of driving under the influence of drugs. We studied pulse rate and regularity in 502 THC-positive drivers who tested negative for other substances. As a control group, we randomly selected 125 drug-negative cases from the database of the DFTDA; no alcohol, narcotics, or medicinal drugs of abuse were detected. The Delta9-THC-positive drivers had a higher mean pulse rate than the control group [82.8 beats/min (SD 16.3) versus 75.6 beats/min (SD 9.2)] and more cases with tachycardia were detected in the Delta9-THC-positive group (19.4% versus 1.6%). There was only one driver with an irregular heart beat in the control group, while there were nine among the Delta9-THC-positive drivers. The drivers with an irregular pulse were over-represented amongst those with the lowest blood Delta9-THC concentrations. This report represents a large study of subjects in a real-life situation and includes observations on pulse frequency, regularity, and blood Delta9-THC concentration. A substantial fraction of Delta9-THC-positive drivers had tachycardia, but there was no correlation between blood Delta9-THC concentration and pulse rate in the present study. We had no further diagnostic information on the cause of the pulse irregularities, but our results indicate that occasional users of cannabis tend to have irregular heart rates at low THC concentrations and at low pulse rates.

The effects of age and workload on 3D spatial attention in dual-task driving.

PubMed

Pierce, Russell S; Andersen, George J

2014-06-01

In the present study we assessed whether the limits in visual-spatial attention associated with aging affect the spatial extent of attention in depth during driving performance. Drivers in the present study performed a car-following and light-detection task. To assess the extent of visual-spatial attention, we compared reaction times and accuracy to light change targets that varied in horizontal position and depth location. In addition, because workload has been identified as a factor that can change the horizontal and vertical extent of attention, we tested whether variability of the lead car speed influenced the extent of spatial attention for younger or older drivers. For younger drivers, reaction time (RT) to light-change targets varied as a function of distance and horizontal position. For older drivers RT varied only as a function of distance. There was a distance by horizontal position interaction for younger drivers but not for older drivers. Specifically, there was no effect of horizontal position at any given level of depth for older drivers. However, for younger drivers there was an effect of horizontal position for targets further in depth but not for targets nearer in depth. With regards to workload, we found no statistically reliable evidence that variability of the lead car speed had an effect on the spatial extent of attention for younger or older drivers. In a control experiment, we examined the effects of depth on light detection when the projected size and position of the targets was constant. Consistent with our previous results, we found that drivers' reaction time to light-change targets varied as a function of distance even when 2D position and size were controlled. Given that depth is an important dimension in driving performance, an important issue for assessing driving safety is to consider the limits of attention in the depth dimension. Therefore, we suggest that future research should consider the importance of depth as a dimension of spatial attention in relation to the assessment of driving performance. Copyright © 2014 Elsevier Ltd. All rights reserved.

In the eye of the beholder: A simulator study of the impact of Google Glass on driving performance.

PubMed

Young, Kristie L; Stephens, Amanda N; Stephan, Karen L; Stuart, Geoffrey W

2016-01-01

This study examined whether, and to what extent, driving is affected by reading text on Google Glass. Reading text requires a high level of visual resources and can interfere with safe driving. However, it is currently unclear if the impact of reading text on a head-mounted display, such as Google Glass (Glass), will differ from that found with more traditional head-down electronic devices, such as a dash-mounted smartphone. A total of 20 drivers (22-48 years) completed the Lane Change Test while driving undistracted and while reading text on Glass and on a smartphone. Measures of lateral vehicle control and event detection were examined along with subjective workload and secondary task performance. Results revealed that drivers' lane keeping ability was significantly impaired by reading text on both Glass and the smartphone. When using Glass, drivers also failed to detect a greater number of lane change signs compared to when using the phone or driving undistracted. In terms of subjective workload, drivers rated reading on Glass as subjectively easier than on the smartphone, which may possibly encourage greater use of this device while driving. Overall, the results suggest that, despite Glass allowing drivers to better maintain their visual attention on the forward scene, drivers are still not able to effectively divide their cognitive attention across the Glass display and the road environment, resulting in impaired driving performance. Copyright © 2015 Elsevier Ltd. All rights reserved.

Sudden illness while driving a vehicle--a retrospective analysis of commercial drivers in Japan.

PubMed

Hitosugi, Masahito; Gomei, Sayaka; Okubo, Takao; Tokudome, Shogo

2012-01-01

We performed a retrospective analysis of commercial drivers to clarify the background of incidents of sudden illness while driving. The analysis used reports submitted by employers to the Japan Ministry of Land, Infrastructure, Transport, and Tourism regarding commercial drivers who had been ordered to stop driving owing to health problems. Of 211 cases with an average work history of 15.2 years, there were 88 bus drivers, 70 taxi drivers, and 53 truck drivers, 36.0% of who had died as a result of their disease. Among taxi and truck drivers, more than 70% of incidents were due to cardiac, aortic, and cerebrovascular disease. More than 80% of these were unable to avoid traffic accidents caused by sudden illness. However, among bus drivers, cardiac, aortic, and cerebrovascular disease accounted for only 23.5% of incidents, and accidents were avoided in more than half of the cases. The duration between starting work and the incident time was significantly shorter among bus drivers [mean 3.3 hours, standard deviation (SD) 3.1] than taxi (7.7 hours, SD 5.8) and truck (7.2 hours, SD 6.3) drivers (P<0.01). The difference between the sudden illness rates of taxi and truck drivers and those of bus drivers is due to both reporting bias and differences in the awareness needed to prevent disabling events while driving. As a precaution, physicians should advise commercial drivers to stop driving as soon as they detect slight discomfort. To prevent accidents, more assertive health promotion aimed at professional drivers is needed.

Vehicle technologies to prevent crashes involving alcohol-impaired drivers

DOT National Transportation Integrated Search

2006-08-11

Review focused on domestic and international alcohol detection. Determine research needs for possible alcohol detection. Develop a concept of operations for an in-vehicle system addressing alcohol impairments.

Effect of glaucoma on eye movement patterns and laboratory-based hazard detection ability

PubMed Central

Black, Alex A.; Wood, Joanne M.

2017-01-01

Purpose The mechanisms underlying the elevated crash rates of older drivers with glaucoma are poorly understood. A key driving skill is timely detection of hazards; however, the hazard detection ability of drivers with glaucoma has been largely unexplored. This study assessed the eye movement patterns and visual predictors of performance on a laboratory-based hazard detection task in older drivers with glaucoma. Methods Participants included 30 older drivers with glaucoma (71±7 years; average better-eye mean deviation (MD) = −3.1±3.2 dB; average worse-eye MD = −11.9±6.2 dB) and 25 age-matched controls (72±7 years). Visual acuity, contrast sensitivity, visual fields, useful field of view (UFoV; processing speeds), and motion sensitivity were assessed. Participants completed a computerised Hazard Perception Test (HPT) while their eye movements were recorded using a desk-mounted Tobii TX300 eye-tracking system. The HPT comprises a series of real-world traffic videos recorded from the driver’s perspective; participants responded to road hazards appearing in the videos, and hazard response times were determined. Results Participants with glaucoma exhibited an average of 0.42 seconds delay in hazard response time (p = 0.001), smaller saccades (p = 0.010), and delayed first fixation on hazards (p<0.001) compared to controls. Importantly, larger saccades were associated with faster hazard responses in the glaucoma group (p = 0.004), but not in the control group (p = 0.19). Across both groups, significant visual predictors of hazard response times included motion sensitivity, UFoV, and worse-eye MD (p<0.05). Conclusions Older drivers with glaucoma had delayed hazard response times compared to controls, with associated changes in eye movement patterns. The association between larger saccades and faster hazard response time in the glaucoma group may represent a compensatory behaviour to facilitate improved performance. PMID:28570621

Driver behavior at rail-highway grade crossings : a signal detection theory analysis

DOT National Transportation Integrated Search

1996-01-01

Signal Detection Theory (SDT) is often used in studies of sensory psychology and perception to describe laboratory experiments in which subjects are asked to detect small changes in very wellcontrolled, precisely defined stimuli such as the intensity...

Evaluating the effectiveness of a post-license education program for young novice drivers in Belgium.

PubMed

Brijs, Kris; Cuenen, Ariane; Brijs, Tom; Ruiter, Robert A C; Wets, Geert

2014-05-01

The disproportionately large number of traffic accidents of young novice drivers highlights the need for an effective driver education program. The Goals for Driving Education (GDE) matrix shows that driver education must target both lower and higher levels of driver competences. Research has indicated that current education programs do not emphasize enough the higher levels, for example awareness and insight. This has raised the importance of insight programs. On the Road (OtR), a Flemish post-license driver education program, is such an insight program that aims to target these higher levels. The program focus is on risky driving behavior like speeding and drink driving. In addition, the program addresses risk detection and risk-related knowledge. The goal of the study was to do an effect evaluation of this insight program at immediate post-test and 2 months follow-up. In addition, the study aimed to generalize the results of this program to comparable programs in order to make usable policy recommendations. A questionnaire based on the Theory of Planned Behavior (TPB) was used in order to measure participants' safety consciousness of speeding and drink driving. Moreover, we focused on risk detection and risk-related knowledge. Participants (N=366) were randomly assigned to a baseline-follow-up group or a post-test-follow-up group. Regarding speeding and driving, we found OtR to have little effect on the TPB variables. Regarding risk detection, we found no significant effect, even though participants clearly needed substantial improvement when stepping into the program. Regarding risk-related knowledge, the program did result in a significant improvement at post-test and follow-up. It is concluded that the current program format is a good starting point, but that it requires further attention to enhance high level driving skills. Program developers are encouraged to work in a more evidence-based manner when they select target variables and methods to influence these variables. Copyright © 2014 Elsevier Ltd. All rights reserved.

Detection of driver metabolites in the human liver metabolic network using structural controllability analysis

PubMed Central

2014-01-01

Background Abnormal states in human liver metabolism are major causes of human liver diseases ranging from hepatitis to hepatic tumor. The accumulation in relevant data makes it feasible to derive a large-scale human liver metabolic network (HLMN) and to discover important biological principles or drug-targets based on network analysis. Some studies have shown that interesting biological phenomenon and drug-targets could be discovered by applying structural controllability analysis (which is a newly prevailed concept in networks) to biological networks. The exploration on the connections between structural controllability theory and the HLMN could be used to uncover valuable information on the human liver metabolism from a fresh perspective. Results We applied structural controllability analysis to the HLMN and detected driver metabolites. The driver metabolites tend to have strong ability to influence the states of other metabolites and weak susceptibility to be influenced by the states of others. In addition, the metabolites were classified into three classes: critical, high-frequency and low-frequency driver metabolites. Among the identified 36 critical driver metabolites, 27 metabolites were found to be essential; the high-frequency driver metabolites tend to participate in different metabolic pathways, which are important in regulating the whole metabolic systems. Moreover, we explored some other possible connections between the structural controllability theory and the HLMN, and find that transport reactions and the environment play important roles in the human liver metabolism. Conclusion There are interesting connections between the structural controllability theory and the human liver metabolism: driver metabolites have essential biological functions; the crucial role of extracellular metabolites and transport reactions in controlling the HLMN highlights the importance of the environment in the health of human liver metabolism. PMID:24885538

Augmented reality cues to assist older drivers with gap estimation for left-turns.

PubMed

Rusch, Michelle L; Schall, Mark C; Lee, John D; Dawson, Jeffrey D; Rizzo, Matthew

2014-10-01

The objective of this study was to assess the effects of augmented reality (AR) cues designed to assist middle-aged and older drivers with a range of UFOV impairments, judging when to make left-turns across oncoming traffic. Previous studies have shown that AR cues can help middle-aged and older drivers respond to potential roadside hazards by increasing hazard detection without interfering with other driving tasks. Intersections pose a critical challenge for cognitively impaired drivers, prone to misjudge time-to-contact with oncoming traffic. We investigated whether AR cues improve or interfere with hazard perception in left-turns across oncoming traffic for drivers with age-related cognitive decline. Sixty-four middle-aged and older drivers with a range of UFOV impairment judged when it would be safe to turn left across oncoming traffic approaching the driver from the opposite direction in a rural stop-sign controlled intersection scenario implemented in a static base driving simulator. Outcome measures used to evaluate the effectiveness of AR cueing included: Time-to-Contact (TTC), Gap Time Variation (GTV), Response Rate, and Gap Response Variation (GRV). All drivers estimated TTCs were shorter in cued than in uncued conditions. In addition, drivers responded more often in cued conditions than in uncued conditions and GRV decreased for all drivers in scenarios that contained AR cues. For both TTC and response rate, drivers also appeared to adjust their behavior to be consistent with the cues, especially drivers with the poorest UFOV scores (matching their behavior to be close to middle-aged drivers). Driver ratings indicated that cueing was not considered to be distracting. Further, various conditions of reliability (e.g., 15% miss rate) did not appear to affect performance or driver ratings. Copyright © 2014 Elsevier Ltd. All rights reserved.

AUGMENTED REALITY CUES TO ASSIST OLDER DRIVERS WITH GAP ESTIMATION FOR LEFT-TURNS

PubMed Central

Rusch, Michelle L.; Schall, Mark C.; Lee, John D.; Dawson, Jeffrey D.; Rizzo, Matthew

2014-01-01

The objective of this study was to assess the effects of augmented reality (AR) cues designed to assist middle-aged and older drivers with a range of UFOV impairments, judging when to make left-turns across oncoming traffic. Previous studies have shown that AR cues can help middle-aged and older drivers respond to potential roadside hazards by increasing hazard detection without interfering with other driving tasks. Intersections pose a critical challenge for cognitively impaired drivers, prone to misjudge time-to-contact with oncoming traffic. We investigated whether AR cues improve or interfere with hazard perception in left-turns across oncoming traffic for drivers with age-related cognitive decline. Sixty-four middle-aged and older drivers with a range of UFOV impairment judged when it would be safe to turn left across oncoming traffic approaching the driver from the opposite direction in a rural stop-sign controlled intersection scenario implemented in a static base driving simulator. Outcome measures used to evaluate the effectiveness of AR cueing included: Time-to-Contact (TTC), Gap Time Variation (GTV), Response Rate, and Gap Response Variation (GRV). All drivers estimated TTCs were shorter in cued than in uncued conditions. In addition, drivers responded more often in cued conditions than in uncued conditions and GRV decreased for all drivers in scenarios that contained AR cues. For both TTC and response rate, drivers also appeared to adjust their behavior to be consistent with the cues, especially drivers with the poorest UFOV scores (matching their behavior to be close to middle-aged drivers). Driver ratings indicated that cueing was not considered to be distracting. Further, various conditions of reliability (e.g., 15% miss rate) did not appear to affect performance or driver ratings. PMID:24950128

Lane Detection on the iPhone

NASA Astrophysics Data System (ADS)

Ren, Feixiang; Huang, Jinsheng; Terauchi, Mutsuhiro; Jiang, Ruyi; Klette, Reinhard

A robust and efficient lane detection system is an essential component of Lane Departure Warning Systems, which are commonly used in many vision-based Driver Assistance Systems (DAS) in intelligent transportation. Various computation platforms have been proposed in the past few years for the implementation of driver assistance systems (e.g., PC, laptop, integrated chips, PlayStation, and so on). In this paper, we propose a new platform for the implementation of lane detection, which is based on a mobile phone (the iPhone). Due to physical limitations of the iPhone w.r.t. memory and computing power, a simple and efficient lane detection algorithm using a Hough transform is developed and implemented on the iPhone, as existing algorithms developed based on the PC platform are not suitable for mobile phone devices (currently). Experiments of the lane detection algorithm are made both on PC and on iPhone.

Real-time stop sign detection and distance estimation using a single camera

NASA Astrophysics Data System (ADS)

Wang, Wenpeng; Su, Yuxuan; Cheng, Ming

2018-04-01

In modern world, the drastic development of driver assistance system has made driving a lot easier than before. In order to increase the safety onboard, a method was proposed to detect STOP sign and estimate distance using a single camera. In STOP sign detection, LBP-cascade classifier was applied to identify the sign in the image, and the principle of pinhole imaging was based for distance estimation. Road test was conducted using a detection system built with a CMOS camera and software developed by Python language with OpenCV library. Results shows that that the proposed system reach a detection accuracy of maximum of 97.6% at 10m, a minimum of 95.00% at 20m, and 5% max error in distance estimation. The results indicate that the system is effective and has the potential to be used in both autonomous driving and advanced driver assistance driving systems.

New psychoactive substances in oral fluid of French and Belgian drivers in 2016.

PubMed

Richeval, Camille; Wille, Sarah Maria Richarda; Nachon-Phanithavong, Mélodie; Samyn, Nele; Allorge, Delphine; Gaulier, Jean-Michel

2018-04-06

Driving under the influence of drugs (DUID) is a worldwide problem with potentially major judiciary and life-threatening consequences. Up to now, only classical drugs of abuse (DOA) are tested for DUID detection. A challenging issue for drafting up-dated international drug policies is to take into account the recent and expanding new psychoactive substances (NPS) market. NPS consist in various narcotic or psychotropic drugs, most of them having a "legal" status, that replicate chemical structures and/or pharmacological effects of classical DOA. Although it is obvious that NPS can lead to impaired driving, the prevalence of NPS use in a DUID context is unknown since the applied roadside screening tests are not yet adapted for these compounds. Between January and December 2016, a total of 391 oral fluid specimens were obtained from used roadside immunochemical test devices for DOA (Drugwipe-5S ® device). These specimens were analyzed using liquid chromatography coupled with tandem mass spectrometry and high resolution mass spectrometry. NPS (mainly cathinone derivatives) were detected in 33 out of the 391 oral fluid samples. This NPS positivity rate of 8.4% in oral fluid of drivers who were submitted to a roadside drug testing in 2016 in France and in Belgium is comparable to the available blood data (NPS positivity rate of 7%) observed in 2015 in similar populations. Our results demonstrate the reality of driving after NPS use in French and Belgian drivers who were submitted to a roadside DOA test. As there is a lack of on-site detection methods to screen for NPS, the detection of NPS in a rapid and cost-effective DUID detection strategy is currently impossible. The expanding use of NPS, notably by drivers as reported here, and the inability of currently used drug detection tests, should be urgently addressed by road safety and law enforcement authorities. Copyright © 2018 Elsevier B.V. All rights reserved.

Circuits of cancer drivers revealed by convergent misregulation of transcription factor targets across tumor types.

PubMed

Gonzalez-Perez, Abel

2016-01-20

Large tumor genome sequencing projects have now uncovered a few hundred genes involved in the onset of tumorigenesis, or drivers, in some two dozen malignancies. One of the main challenges emerging from this catalog of drivers is how to make sense of their heterogeneity in most cancer types. This is key not only to understand how carcinogenesis appears and develops in these malignancies to be able to early diagnose them, but also to open up the possibility to employ therapeutic strategies targeting a driver protein to counteract the alteration of another connected driver. Here, I focus on driver transcription factors and their connection to tumorigensis in several tumor types through the alteration of the expression of their targets. First, I explore their involvement in tumorigenesis as mutational drivers in 28 different tumor types. Then, I collect a list of downstream targets of the all driver transcription factors (TFs), and identify which of them exhibit a differential expression upon alterations of driver transcription factors. I identify the subset of targets of each TF most likely mediating the tumorigenic effect of their driver alterations in each tumor type, and explore their overlap. Furthermore, I am able to identify other driver genes that cause tumorigenesis through the alteration of very similar sets of targets. I thus uncover these circuits of connected drivers which cause tumorigenesis through the perturbation of overlapping cellular pathways in a pan-cancer manner across 15 malignancies. The systematic detection of these circuits may be key to propose novel therapeutic strategies indirectly targeting driver alterations in tumors.

Stress-oriented driver assistance system for electric vehicles.

PubMed

Athanasiou, Georgia; Tsotoulidis, Savvas; Mitronikas, Epaminondas; Lymberopoulos, Dimitrios

2014-01-01

Stress is physiological and physical reaction that appears in highly demanding situations and affects human's perception and reaction capability. Occurrence of stress events within highly dynamic road environment could lead to life-threatening situation. With the perspective of safety and comfort driving provision to anxious drivers, in this paper a stress-oriented Driver Assistance System (DAS) is proposed. The DAS deployed on Electric Vehicle. This novel DAS customizes driving command signal in respect to road context, when stress is detected. The effectiveness of this novel DAS is verified by simulation in MATLAB/SIMULINK environment.

Prevalence of drug use among drivers based on mandatory, random tests in a roadside survey

PubMed Central

Alcañiz, Manuela; Guillen, Montserrat

2018-01-01

Background In the context of road safety, this study aims to examine the prevalence of drug use in a random sample of drivers. Methods A stratified probabilistic sample was designed to represent vehicles circulating on non-urban roads. Random drug tests were performed during autumn 2014 on 521 drivers in Catalonia (Spain). Participation was mandatory. The prevalence of drug driving for cannabis, methamphetamines, amphetamines, cocaine, opiates and benzodiazepines was assessed. Results The overall prevalence of drug use is 16.4% (95% CI: 13.9; 18.9) and affects primarily younger male drivers. Drug use is similarly prevalent during weekdays and on weekends, but increases with the number of occupants. The likelihood of being positive for methamphetamines is significantly higher for drivers of vans and lorries. Conclusions Different patterns of use are detected depending on the drug considered. Preventive drug tests should not only be conducted on weekends and at night-time, and need to be reinforced for drivers of commercial vehicles. Active educational campaigns should focus on the youngest age-group of male drivers. PMID:29920542

Physiologic adaptation to space - Space adaptation syndrome

NASA Technical Reports Server (NTRS)

Vanderploeg, J. M.

1985-01-01

The adaptive changes of the neurovestibular system to microgravity, which result in space motion sickness (SMS), are studied. A list of symptoms, which range from vomiting to drowsiness, is provided. The two patterns of symptom development, rapid and gradual, and the duration of the symptoms are described. The concept of sensory conflict and rearrangements to explain SMS is being investigated.

State as Variable, as Obstacle and as Mediator of Stimulation in Infant Research.

ERIC Educational Resources Information Center

Korner, Anneliese F.

This paper is a discussion of the different contexts in which the concept of the infant's state is used in infant research. The infant states discussed are: regular sleep, irregular sleep, drowsiness, alert inactivity, waking activity, and crying. Also included are hunger periods and indeterminate states, those instances in which an infant's state…

Observed and projected drivers of emerging infectious diseases in Europe.

PubMed

Semenza, Jan C; Rocklöv, Joacim; Penttinen, Pasi; Lindgren, Elisabet

2016-10-01

Emerging infectious diseases are of international concern because of the potential for, and impact of, pandemics; however, they are difficult to predict. To identify the drivers of disease emergence, we analyzed infectious disease threat events (IDTEs) detected through epidemic intelligence collected at the European Centre for Disease Prevention and Control (ECDC) between 2008 and 2013, and compared the observed results with a 2008 ECDC foresight study of projected drivers of future IDTEs in Europe. Among 10 categories of IDTEs, foodborne and waterborne IDTEs were the most common, vaccine-preventable IDTEs caused the highest number of cases, and airborne IDTEs caused the most deaths. Observed drivers for each IDTE were sorted into three main groups: globalization and environmental drivers contributed to 61% of all IDTEs, public health system drivers contributed to 21%, and social and demographic drivers to 18%. A multiple logistic regression analysis showed that four of the top five drivers for observed IDTEs were in the globalization and environment group. In the observational study, the globalization and environment group was related to all IDTE categories, but only to five of eight categories in the foresight study. Directly targeting these drivers with public health interventions may diminish the chances of IDTE occurrence from the outset. © 2016 New York Academy of Sciences.

Are drivers aware of sleepiness and increasing crash risk while driving?

PubMed

Williamson, Ann; Friswell, Rena; Olivier, Jake; Grzebieta, Raphael

2014-09-01

Drivers are advised to take breaks when they feel too tired to drive, but there is question over whether they are able to detect increasing fatigue and sleepiness sufficiently to decide when to take a break. The aim of this study was to investigate the extent to which drivers have access to cognitive information about their current state of sleepiness, likelihood of falling asleep, and the implications for driving performance and the likelihood of crashing. Ninety drivers were recruited to do a 2h drive in a driving simulator. They were divided into three groups: one made ratings of their sleepiness, likelihood of falling asleep and likelihood of crashing over the next few minutes at prompts occurring at 200s intervals throughout the drive, the second rated sleepiness and likelihood of falling asleep at prompts but pressed a button on the steering wheel at any time if they felt they were near to crashing and the third made no ratings and only used a button-press if they felt a crash was likely. Fatigue and sleepiness was encouraged by monotonous driving conditions, an imposed shorter than usual sleep on the night before and by afternoon testing. Drivers who reported that they were possibly, likely or very likely to fall asleep in the next few minutes, were more than four times more likely to crash subsequently. Those who rated themselves as sleepy or likely to fall asleep had a more than 9-fold increase in the hazards of a centerline crossing compared to those who rated themselves as alert. The research shows clearly that drivers can detect changes in their levels of sleepiness sufficiently to make a safe decision to stop driving due to sleepiness. Therefore, road safety policy needs to move from reminding drivers of the signs of sleepiness and focus on encouraging drivers to respond to obvious indicators of fatigue and sleepiness and consequent increased crash risk. Copyright © 2014 Elsevier Ltd. All rights reserved.

An innovative multi dof TMD system for motorcycle handlebars designed to reduce structural vibrations and human exposure

NASA Astrophysics Data System (ADS)

Agostoni, S.; Cheli, F.; Leo, E.; Pezzola, M.

2012-08-01

Motor vehicle ride comfort is mainly affected by reciprocating engine inertia unbalances. These forces are transmitted to the driver through the main frame, the engine mounts, and the auxiliary sub systems—all components with which he physically comes into contact. On-road traction vehicle engines are mainly characterized by transient exercise. Thus, an excitation frequency range from 800 RPM (≈15 Hz for stationary vehicles) up to 15,000 RPM (≈250 Hz as a cut off condition) occurs. Several structural resonances are induced by the unbalancing forces spectrum, thus exposing the driver to amplified vibrations. The aim of this research is to reduce driver vibration exposure, by acting on the modal response of structures with which the driver comes into contact. An experimental methodology, capable of identifying local vibration modes was developed. The application of this methodology on a reference vehicle allows us to detect if/when/how the above mentioned resonances are excited. Numerical models were used to study structural modifications. In this article, a handlebar equipped with an innovative multi reciprocating tuned mass damper was optimized. All structural modifications were designed, developed and installed on a vehicle. Modal investigations were then performed in order to predict modification efficiency. Furthermore, functional solution efficiency was verified during sweep tests performed on a target vehicle, by means of a roller bench capable of replicating on-road loads. Three main investigation zones of the vehicle were detected and monitored using accelerometers: (1) engine mounts, to characterize vibration emissions; (2) bindings connecting the engine to the frame, in order to detect vibration transfer paths, with particular attention being paid to local dynamic amplifications due to compliances and (3) the terminal components with which the driver comes into contact.

Young drivers' perception of adult and child pedestrians in potential street-crossing situations.

PubMed

Ābele, Līva; Haustein, Sonja; Møller, Mette

2018-04-03

Despite overall improvements in road traffic safety, pedestrian accidents continue to be a serious public health problem. Due to lack of experience, limited cognitive and motoric skills, and smaller size, children have a higher injury risk as pedestrians than adults. To what extent drivers adjust their driving behaviour to children's higher vulnerability is largely unknown. To determine whether young male drivers' behaviour and scanning pattern differs when approaching a child and an adult pedestrian in a potential street-crossing situation, sixty-five young (18-24) male drivers' speed, lateral position and eye movements were recorded in a driving simulator. Results showed that fewer drivers responded by slowing down and that drivers had a higher driving speed when approaching a child pedestrian, although the time of the first fixation on both types of pedestrians was the same. However, drivers drove farther away from a child than an adult pedestrian. Additionally, fewer drivers who did not slow down fixated on the speedometer while approaching the child pedestrian. The results show that young drivers behave differently when approaching a child and an adult pedestrian, though not in a way that appropriately accounts for the limitations of a child pedestrian. A better understanding of how drivers respond to different types of pedestrians and why could contribute to the development of pedestrian detection and emergency braking systems. Copyright © 2018 Elsevier Ltd. All rights reserved.

"Driverless" Shocks in the Interplanetary Medium

NASA Technical Reports Server (NTRS)

Gopalswamy, N.; Kaiser, M. L.; Lara, A.

1999-01-01

Many interplanetary shocks have been detected without an obvious driver behind them. These shocks have been thought to be either blast waves from solar flares or shocks due to sudden increase in solar wind speed caused by interactions between large scale open and closed field lines of the Sun. We investigated this problem using a set of interplanetary shock detected {\\it in situ} by the Wind space craft and tracing their solar origins using low frequency radio data obtained by the Wind/WAVES experiment. For each of these "driverless shocks" we could find a unique coronal mass ejections (CME) event observed by the SOHO (Solar and Heliospheric Observatory) coronagraphs. We also found that these CMEs were ejected at large angles from the Sun-Earth line. It appears that the "driverless shocks" are actually driver shocks, but the drivers were not intercepted by the spacecraft. We conclude that the interplanetary shocks are much more extended than the driving CMEs.

Effects of exposure to lead among lead-acid battery factory workers in Sudan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mohamed, A.A.E.K.; Hamed, A.A.S.; Elhaimi, Y.A.A.

Health effects of occupational exposure to lead were investigated among 92 exposed workers in lead-acid battery factory and 40 nonexposed workers serving as a control group from an oil mill in Khartoum North industrial area. The two groups were closely similar in age, stature, body weight, and socioeconomic conditions. A highly significant increase (P<.01) was recorded in blood lead, urinary coproporphyrin, and basophilic stippled red blood cells of the exposed group in comparison to the control group. Central nervous system symptoms (insomnia, fatigue, weakness, and drowsiness) were reported by 50% and other symptoms such as abdominal colic and constipation weremore » reported by 41% of the exposed group. Blue line on the gum was detected only on 2% of the exposed group. Strong associations between exposure to lead and the prevalence of central nervous system symptoms, abdominal colic, and constipation were recorded. Exposure to exceedingly high levels of lead in the working environment causes adverse health effects.« less

An Orientation Sensor-Based Head Tracking System for Driver Behaviour Monitoring.

PubMed

Zhao, Yifan; Görne, Lorenz; Yuen, Iek-Man; Cao, Dongpu; Sullman, Mark; Auger, Daniel; Lv, Chen; Wang, Huaji; Matthias, Rebecca; Skrypchuk, Lee; Mouzakitis, Alexandros

2017-11-22

Although at present legislation does not allow drivers in a Level 3 autonomous vehicle to engage in a secondary task, there may become a time when it does. Monitoring the behaviour of drivers engaging in various non-driving activities (NDAs) is crucial to decide how well the driver will be able to take over control of the vehicle. One limitation of the commonly used face-based head tracking system, using cameras, is that sufficient features of the face must be visible, which limits the detectable angle of head movement and thereby measurable NDAs, unless multiple cameras are used. This paper proposes a novel orientation sensor based head tracking system that includes twin devices, one of which measures the movement of the vehicle while the other measures the absolute movement of the head. Measurement error in the shaking and nodding axes were less than 0.4°, while error in the rolling axis was less than 2°. Comparison with a camera-based system, through in-house tests and on-road tests, showed that the main advantage of the proposed system is the ability to detect angles larger than 20° in the shaking and nodding axes. Finally, a case study demonstrated that the measurement of the shaking and nodding angles, produced from the proposed system, can effectively characterise the drivers' behaviour while engaged in the NDAs of chatting to a passenger and playing on a smartphone.

Rare discrepancies in a driver gene alteration within histologically heterogeneous primary lung cancers.

PubMed

Zhong, Wen-zhao; Su, Jian; Xu, Fang-ping; Zhai, Hao-ran; Zhang, Xu-chao; Yang, Xue-ning; Chen, Zhi-yong; Chen, Zhi-hong; Li, Wei; Dong, Song; Zhou, Qing; Yang, Jin-ji; Liu, Yan-hui; Wu, Yi-long

2015-11-01

Most lung adenocarcinomas consist of mixtures of histological subtypes harboring different frequencies of driver gene mutations. However, little is known about intratumoral heterogeneity(ITH) within histologically heterogeneous primary lung cancers. Investigating key driver genes in respective morphological pattern is crucial to personalized treatment. Morphologically different areas within the same surgically resected adenocarcinomas were extracted from tissues to analyze gene status in each growth pattern. Driver genes, epidermal growth factor receptor (EGFR), KRAS and EML4-ALK, were assessed by assays with different sensitivities. Seventy-nine consecutive eligible patients harboring a driver gene (EGFR=65; KRAS=10; EML4-ALK=4) were enrolled. For EGFR mutations, ITH occurred in 13.3% (8/60) by direct sequencing (DS) and 1.7% (1/60) by amplification refractory mutation system (ARMS) (P=0.016) among adenocarcinomas, but consistent within five adeno-squamous cell carcinomas by both methods. ITH among KRAS mutations were detected in 20% (2/10) by DS, whereas consistent (10/10) by high resolution melting. No discrepancies in EML4-ALK rearrangements existed according to fluorescence in situ hybridization. Rare ITHs of EGFR/KRAS/EML4-ALK alterations within histologically heterogeneous primary lung adenocarcinomas existed by methods with higher sensitivity. Discrepancies might be due to abundance of mutant tumor cells and detection assays. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

SomInaClust: detection of cancer genes based on somatic mutation patterns of inactivation and clustering.

PubMed

Van den Eynden, Jimmy; Fierro, Ana Carolina; Verbeke, Lieven P C; Marchal, Kathleen

2015-04-23

With the advances in high throughput technologies, increasing amounts of cancer somatic mutation data are being generated and made available. Only a small number of (driver) mutations occur in driver genes and are responsible for carcinogenesis, while the majority of (passenger) mutations do not influence tumour biology. In this study, SomInaClust is introduced, a method that accurately identifies driver genes based on their mutation pattern across tumour samples and then classifies them into oncogenes or tumour suppressor genes respectively. SomInaClust starts from the observation that oncogenes mainly contain mutations that, due to positive selection, cluster at similar positions in a gene across patient samples, whereas tumour suppressor genes contain a high number of protein-truncating mutations throughout the entire gene length. The method was shown to prioritize driver genes in 9 different solid cancers. Furthermore it was found to be complementary to existing similar-purpose methods with the additional advantages that it has a higher sensitivity, also for rare mutations (occurring in less than 1% of all samples), and it accurately classifies candidate driver genes in putative oncogenes and tumour suppressor genes. Pathway enrichment analysis showed that the identified genes belong to known cancer signalling pathways, and that the distinction between oncogenes and tumour suppressor genes is biologically relevant. SomInaClust was shown to detect candidate driver genes based on somatic mutation patterns of inactivation and clustering and to distinguish oncogenes from tumour suppressor genes. The method could be used for the identification of new cancer genes or to filter mutation data for further data-integration purposes.

Reliability of the Watch-PAT 200 in detecting sleep apnea in highway bus drivers.

PubMed

Yuceege, Melike; Firat, Hikmet; Demir, Ahmet; Ardic, Sadik

2013-04-15

To predict the validity of Watch-PAT (WP) device for sleep disordered breathing (SDB) among highway bus drivers. A total number of 90 highway bus drivers have undergone polysomnography (PSG) and Watch-PAT test simultaneously. Routine blood tests and the routine ear-nose-throat (ENT) exams have been done as well. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 89.1%, 76.9%, 82% and 85.7% for RDI > 15, respectively. WRDI, WODI, W < 90% duration and Wmean SaO2 results were well correlated with the PSG results. In the sensitivity and specificity analysis, when diagnosis of sleep apnea was defined for different cut-off values of RDI of 5, 10 and 15, AUC (95%CI) were found as 0.84 (0.74-0.93), 0.87 (95%CI: 0.79-0.94) and 0.91 (95%CI: 0.85-0.97), respectively. There were no statistically significant differences between Stage1+2/Wlight and Stage REM/WREM. The percentage of Stage 3 sleep had difference significant statistically from the percentage of Wdeep. Total sleep times in PSG and WP showed no statistically important difference. Total NREM duration and total WNREM duration had no difference either. Watch-PAT device is helpful in detecting SDB with RDI > 15 in highway bus drivers, especially in drivers older than 45 years, but has limited value in drivers younger than 45 years old who have less risk for OSA. Therefore, WP can be used in the former group when PSG is not easily available.

Characteristics of on-road driving performance of persons with central vision loss who use bioptic telescopes.

PubMed

Wood, Joanne M; McGwin, Gerald; Elgin, Jennifer; Searcey, Karen; Owsley, Cynthia

2013-05-01

To compare the on-road driving performance of visually impaired drivers using bioptic telescopes with age-matched controls. Participants included 23 persons (mean age = 33 ± 12 years) with visual acuity of 20/63 to 20/200 who were legally licensed to drive through a state bioptic driving program, and 23 visually normal age-matched controls (mean age = 33 ± 12 years). On-road driving was assessed in an instrumented dual-brake vehicle along 14.6 miles of city, suburban, and controlled-access highways. Two backseat evaluators independently rated driving performance using a standardized scoring system. Vehicle control was assessed through vehicle instrumentation and video recordings used to evaluate head movements, lane-keeping, pedestrian detection, and frequency of bioptic telescope use. Ninety-six percent (22/23) of bioptic drivers and 100% (23/23) of controls were rated as safe to drive by the evaluators. There were no group differences for pedestrian detection, or ratings for scanning, speed, gap judgments, braking, indicator use, or obeying signs/signals. Bioptic drivers received worse ratings than controls for lane position and steering steadiness and had lower rates of correct sign and traffic signal recognition. Bioptic drivers made significantly more right head movements, drove more often over the right-hand lane marking, and exhibited more sudden braking than controls. Drivers with central vision loss who are licensed to drive through a bioptic driving program can display proficient on-road driving skills. This raises questions regarding the validity of denying such drivers a license without the opportunity to train with a bioptic telescope and undergo on-road evaluation.

Assessing Chinese coach drivers' fitness to drive: The development of a toolkit based on cognition measurements.

PubMed

Wang, Huarong; Mo, Xian; Wang, Ying; Liu, Ruixue; Qiu, Peiyu; Dai, Jiajun

2016-10-01

Road traffic accidents resulting in group deaths and injuries are often related to coach drivers' inappropriate operations and behaviors. Thus, the evaluation of coach drivers' fitness to drive is an important measure for improving the safety of public transportation. Previous related research focused on drivers' age and health condition. Comprehensive studies about commercial drivers' cognitive capacities are limited. This study developed a toolkit consisting of nine cognition measurements across driver perception/sensation, attention, and reaction. A total of 1413 licensed coach drivers in Jiangsu Province, China were investigated and tested. Results indicated that drivers with accident history within three years performed overwhelmingly worse (p<0.001) on dark adaptation, dynamic visual acuity, depth perception, attention concentration, attention span, and significantly worse (p<0.05) on reaction to complex tasks compared with drivers with clear accident records. These findings supported that in the assessment of fitness to drive, cognitive capacities are sensitive to the detection of drivers with accident proneness. We first developed a simple evaluation model based on the percentile distribution of all single measurements, which defined the normal range of "fit-to-drive" by eliminating a 5% tail of each measurement. A comprehensive evaluation model was later constructed based on the kernel principal component analysis, in which the eliminated 5% tail was calculated from on integrated index. Methods to categorizing qualified, good, and excellent coach drivers and criteria for evaluating and training Chinese coach drivers' fitness to drive were also proposed. Copyright © 2015 Elsevier Ltd. All rights reserved.

Driver landmark and traffic sign identification in early Alzheimer's disease.

PubMed

Uc, E Y; Rizzo, M; Anderson, S W; Shi, Q; Dawson, J D

2005-06-01

To assess visual search and recognition of roadside targets and safety errors during a landmark and traffic sign identification task in drivers with Alzheimer's disease. 33 drivers with probable Alzheimer's disease of mild severity and 137 neurologically normal older adults underwent a battery of visual and cognitive tests and were asked to report detection of specific landmarks and traffic signs along a segment of an experimental drive. The drivers with mild Alzheimer's disease identified significantly fewer landmarks and traffic signs and made more at-fault safety errors during the task than control subjects. Roadside target identification performance and safety errors were predicted by scores on standardised tests of visual and cognitive function. Drivers with Alzheimer's disease are impaired in a task of visual search and recognition of roadside targets; the demands of these targets on visual perception, attention, executive functions, and memory probably increase the cognitive load, worsening driving safety.

Twentieth century turnover of Mexican endemic avifaunas: Landscape change versus climate drivers.

PubMed

Peterson, A Townsend; Navarro-Sigüenza, Adolfo G; Martínez-Meyer, Enrique; Cuervo-Robayo, Angela P; Berlanga, Humberto; Soberón, Jorge

2015-05-01

Numerous climate change effects on biodiversity have been anticipated and documented, including extinctions, range shifts, phenological shifts, and breakdown of interactions in ecological communities, yet the relative balance of different climate drivers and their relationships to other agents of global change (for example, land use and land-use change) remains relatively poorly understood. This study integrated historical and current biodiversity data on distributions of 115 Mexican endemic bird species to document areas of concentrated gains and losses of species in local communities, and then related those changes to climate and land-use drivers. Of all drivers examined, at this relatively coarse spatial resolution, only temperature change had significant impacts on avifaunal turnover; neither precipitation change nor human impact on landscapes had detectable effects. This study, conducted across species' geographic distributions, and covering all of Mexico, thanks to two large-scale biodiversity data sets, could discern relative importance of specific climatic drivers of biodiversity change.

Low ground clearance vehicle detection and warning.

DOT National Transportation Integrated Search

2015-06-01

A Low Ground Clearance Vehicle Detection : System (LGCVDS) determines if a commercial : motor vehicle can successfully clear a highwayrail : grade crossing and notifies the driver when : his or her vehicle cannot safely traverse the : crossing. That ...

The visual detection of driving while intoxicated : field test of visual cues and detection methods

DOT National Transportation Integrated Search

1980-04-01

A Drunk Driver Detection Guide was developed and tested at a sample of 10 law enforcement agencies at locations throughout the United States. The test was designed to provide both longitudinal and cross-sectional analyses of several measures likely t...

Lowering thresholds for speed limit enforcement impairs peripheral object detection and increases driver subjective workload.

PubMed

Bowden, Vanessa K; Loft, Shayne; Tatasciore, Monica; Visser, Troy A W

2017-01-01

Speed enforcement reduces incidences of speeding, thus reducing traffic accidents. Accordingly, it has been argued that stricter speed enforcement thresholds could further improve road safety. Effective speed monitoring however requires driver attention and effort, and human information-processing capacity is limited. Emphasizing speed monitoring may therefore reduce resource availability for other aspects of safe vehicle operation. We investigated whether lowering enforcement thresholds in a simulator setting would introduce further competition for limited cognitive and visual resources. Eighty-four young adult participants drove under conditions where they could be fined for travelling 1, 6, or 11km/h over a 50km/h speed-limit. Stricter speed enforcement led to greater subjective workload and significant decrements in peripheral object detection. These data indicate that the benefits of reduced speeding with stricter enforcement may be at least partially offset by greater mental demands on drivers, reducing their responses to safety-critical stimuli on the road. It is likely these results under-estimate the impact of stricter speed enforcement on real-world drivers who experience significantly greater pressures to drive at or above the speed limit. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comprehensive analysis of transcriptome variation uncovers known and novel driver events in T-cell acute lymphoblastic leukemia.

PubMed

Atak, Zeynep Kalender; Gianfelici, Valentina; Hulselmans, Gert; De Keersmaecker, Kim; Devasia, Arun George; Geerdens, Ellen; Mentens, Nicole; Chiaretti, Sabina; Durinck, Kaat; Uyttebroeck, Anne; Vandenberghe, Peter; Wlodarska, Iwona; Cloos, Jacqueline; Foà, Robin; Speleman, Frank; Cools, Jan; Aerts, Stein

2013-01-01

RNA-seq is a promising technology to re-sequence protein coding genes for the identification of single nucleotide variants (SNV), while simultaneously obtaining information on structural variations and gene expression perturbations. We asked whether RNA-seq is suitable for the detection of driver mutations in T-cell acute lymphoblastic leukemia (T-ALL). These leukemias are caused by a combination of gene fusions, over-expression of transcription factors and cooperative point mutations in oncogenes and tumor suppressor genes. We analyzed 31 T-ALL patient samples and 18 T-ALL cell lines by high-coverage paired-end RNA-seq. First, we optimized the detection of SNVs in RNA-seq data by comparing the results with exome re-sequencing data. We identified known driver genes with recurrent protein altering variations, as well as several new candidates including H3F3A, PTK2B, and STAT5B. Next, we determined accurate gene expression levels from the RNA-seq data through normalizations and batch effect removal, and used these to classify patients into T-ALL subtypes. Finally, we detected gene fusions, of which several can explain the over-expression of key driver genes such as TLX1, PLAG1, LMO1, or NKX2-1; and others result in novel fusion transcripts encoding activated kinases (SSBP2-FER and TPM3-JAK2) or involving MLLT10. In conclusion, we present novel analysis pipelines for variant calling, variant filtering, and expression normalization on RNA-seq data, and successfully applied these for the detection of translocations, point mutations, INDELs, exon-skipping events, and expression perturbations in T-ALL.

A New Perspective on Neonatal Smiling: Differences between the Judgments of Expert Coders and Naive Observers

ERIC Educational Resources Information Center

Dondi, Marco; Messinger, Daniel; Colle, Marta; Tabasso, Alessia; Simion, Francesca; Barba, Beatrice Dalla; Fogel, Alan

2007-01-01

To better understand the form and recognizability of neonatal smiling, 32 newborns (14 girls; M = 25.6 hr) were videorecorded in the behavioral states of alertness, drowsiness, active sleep, and quiet sleep. Baby Facial Action Coding System coding of both lip corner raising (simple or non-Duchenne) and lip corner raising with cheek raising…

Assessing contextual factors that influence acceptance of pedestrian alerts by a night vision system.

PubMed

Källhammer, Jan-Erik; Smith, Kip

2012-08-01

We investigated five contextual variables that we hypothesized would influence driver acceptance of alerts to pedestrians issued by a night vision active safety system to inform the specification of the system's alerting strategies. Driver acceptance of automotive active safety systems is a key factor to promote their use and implies a need to assess factors influencing driver acceptance. In a field operational test, 10 drivers drove instrumented vehicles equipped with a preproduction night vision system with pedestrian detection software. In a follow-up experiment, the 10 drivers and 25 additional volunteers without experience with the system watched 57 clips with pedestrian encounters gathered during the field operational test. They rated the acceptance of an alert to each pedestrian encounter. Levels of rating concordance were significant between drivers who experienced the encounters and participants who did not. Two contextual variables, pedestrian location and motion, were found to influence ratings. Alerts were more accepted when pedestrians were close to or moving toward the vehicle's path. The study demonstrates the utility of using subjective driver acceptance ratings to inform the design of active safety systems and to leverage expensive field operational test data within the confines of the laboratory. The design of alerting strategies for active safety systems needs to heed the driver's contextual sensitivity to issued alerts.

Age-Related Differences in Vehicle Control and Eye Movement Patterns at Intersections: Older and Middle-Aged Drivers

PubMed Central

Yamani, Yusuke; Horrey, William J.; Liang, Yulan; Fisher, Donald L.

2016-01-01

Older drivers are at increased risk of intersection crashes. Previous work found that older drivers execute less frequent glances for detecting potential threats at intersections than middle-aged drivers. Yet, earlier work has also shown that an active training program doubled the frequency of these glances among older drivers, suggesting that these effects are not necessarily due to age-related functional declines. In light of findings, the current study sought to explore the ability of older drivers to coordinate their head and eye movements while simultaneously steering the vehicle as well as their glance behavior at intersections. In a driving simulator, older (M = 76 yrs) and middle-aged (M = 58 yrs) drivers completed different driving tasks: (1) travelling straight on a highway while scanning for peripheral information (a visual search task) and (2) navigating intersections with areas potential hazard. The results replicate that the older drivers did not execute glances for potential threats to the sides when turning at intersections as frequently as the middle-aged drivers. Furthermore, the results demonstrate costs of performing two concurrent tasks, highway driving and visual search task on the side displays: the older drivers performed more poorly on the visual search task and needed to correct their steering positions more compared to the middle-aged counterparts. The findings are consistent with the predictions and discussed in terms of a decoupling hypothesis, providing an account for the effects of the active training program. PMID:27736887

Reducing Runway Incursions: Can You Relate?

DOT National Transportation Integrated Search

1992-01-01

Side object detection systems (SODS) are collision warning systems which alert drivers to the presence of traffic alongside their vehicle within defined detection zones. The intent of SODS is to reduce collisions during lane changes and merging maneu...

On-road vehicle detection: a review.

PubMed

Sun, Zehang; Bebis, George; Miller, Ronald

2006-05-01

Developing on-board automotive driver assistance systems aiming to alert drivers about driving environments, and possible collision with other vehicles has attracted a lot of attention lately. In these systems, robust and reliable vehicle detection is a critical step. This paper presents a review of recent vision-based on-road vehicle detection systems. Our focus is on systems where the camera is mounted on the vehicle rather than being fixed such as in traffic/driveway monitoring systems. First, we discuss the problem of on-road vehicle detection using optical sensors followed by a brief review of intelligent vehicle research worldwide. Then, we discuss active and passive sensors to set the stage for vision-based vehicle detection. Methods aiming to quickly hypothesize the location of vehicles in an image as well as to verify the hypothesized locations are reviewed next. Integrating detection with tracking is also reviewed to illustrate the benefits of exploiting temporal continuity for vehicle detection. Finally, we present a critical overview of the methods discussed, we assess their potential for future deployment, and we present directions for future research.

The Wechsler Digit Symbol Substitution Test as the best indicator of the risk of impaired driving in Alzheimer disease and normal aging.

PubMed

Lafont, Sylviane; Marin-Lamellet, Claude; Paire-Ficout, Laurence; Thomas-Anterion, Catherine; Laurent, Bernard; Fabrigoule, Colette

2010-01-01

Our purpose was to identify cognitive tools associated with unsafe driving among elderly drivers of varying cognitive levels. Twenty drivers with early-stage dementia of the Alzheimer type and 56 nondemented drivers aged 65-85 were recruited. Various cognitive processes were measured and unsafe driving was evaluated during an in-traffic road test with 3 different indicators and a composite indicator. The Wechsler Digit Symbol Substitution Test score was the best cognitive measure to detect unsafe drivers using the composite driving indicator. The Digit Symbol Substitution Test may be used by physicians for the evaluation and follow-up of older patients, with or without Alzheimer-type dementia, as a screening tool of unsafe driving.

Far-Infrared Based Pedestrian Detection for Driver-Assistance Systems Based on Candidate Filters, Gradient-Based Feature and Multi-Frame Approval Matching

PubMed Central

Wang, Guohua; Liu, Qiong

2015-01-01

Far-infrared pedestrian detection approaches for advanced driver-assistance systems based on high-dimensional features fail to simultaneously achieve robust and real-time detection. We propose a robust and real-time pedestrian detection system characterized by novel candidate filters, novel pedestrian features and multi-frame approval matching in a coarse-to-fine fashion. Firstly, we design two filters based on the pedestrians’ head and the road to select the candidates after applying a pedestrian segmentation algorithm to reduce false alarms. Secondly, we propose a novel feature encapsulating both the relationship of oriented gradient distribution and the code of oriented gradient to deal with the enormous variance in pedestrians’ size and appearance. Thirdly, we introduce a multi-frame approval matching approach utilizing the spatiotemporal continuity of pedestrians to increase the detection rate. Large-scale experiments indicate that the system works in real time and the accuracy has improved about 9% compared with approaches based on high-dimensional features only. PMID:26703611

Far-Infrared Based Pedestrian Detection for Driver-Assistance Systems Based on Candidate Filters, Gradient-Based Feature and Multi-Frame Approval Matching.

PubMed

Wang, Guohua; Liu, Qiong

2015-12-21

Far-infrared pedestrian detection approaches for advanced driver-assistance systems based on high-dimensional features fail to simultaneously achieve robust and real-time detection. We propose a robust and real-time pedestrian detection system characterized by novel candidate filters, novel pedestrian features and multi-frame approval matching in a coarse-to-fine fashion. Firstly, we design two filters based on the pedestrians' head and the road to select the candidates after applying a pedestrian segmentation algorithm to reduce false alarms. Secondly, we propose a novel feature encapsulating both the relationship of oriented gradient distribution and the code of oriented gradient to deal with the enormous variance in pedestrians' size and appearance. Thirdly, we introduce a multi-frame approval matching approach utilizing the spatiotemporal continuity of pedestrians to increase the detection rate. Large-scale experiments indicate that the system works in real time and the accuracy has improved about 9% compared with approaches based on high-dimensional features only.

Traffic jam driving with NMV avoidance

NASA Astrophysics Data System (ADS)

Milanés, Vicente; Alonso, Luciano; Villagrá, Jorge; Godoy, Jorge; de Pedro, Teresa; Oria, Juan P.

2012-08-01

In recent years, the development of advanced driver assistance systems (ADAS) - mainly based on lidar and cameras - has considerably improved the safety of driving in urban environments. These systems provide warning signals for the driver in the case that any unexpected traffic circumstance is detected. The next step is to develop systems capable not only of warning the driver but also of taking over control of the car to avoid a potential collision. In the present communication, a system capable of autonomously avoiding collisions in traffic jam situations is presented. First, a perception system was developed for urban situations—in which not only vehicles have to be considered, but also pedestrians and other non-motor-vehicles (NMV). It comprises a differential global positioning system (DGPS) and wireless communication for vehicle detection, and an ultrasound sensor for NMV detection. Then, the vehicle's actuators - brake and throttle pedals - were modified to permit autonomous control. Finally, a fuzzy logic controller was implemented capable of analyzing the information provided by the perception system and of sending control commands to the vehicle's actuators so as to avoid accidents. The feasibility of the integrated system was tested by mounting it in a commercial vehicle, with the results being encouraging.

A Precise Drunk Driving Detection Using Weighted Kernel Based on Electrocardiogram.

PubMed

Wu, Chung Kit; Tsang, Kim Fung; Chi, Hao Ran; Hung, Faan Hei

2016-05-09

Globally, 1.2 million people die and 50 million people are injured annually due to traffic accidents. These traffic accidents cost $500 billion dollars. Drunk drivers are found in 40% of the traffic crashes. Existing drunk driving detection (DDD) systems do not provide accurate detection and pre-warning concurrently. Electrocardiogram (ECG) is a proven biosignal that accurately and simultaneously reflects human's biological status. In this letter, a classifier for DDD based on ECG is investigated in an attempt to reduce traffic accidents caused by drunk drivers. At this point, it appears that there is no known research or literature found on ECG classifier for DDD. To identify drunk syndromes, the ECG signals from drunk drivers are studied and analyzed. As such, a precise ECG-based DDD (ECG-DDD) using a weighted kernel is developed. From the measurements, 10 key features of ECG signals were identified. To incorporate the important features, the feature vectors are weighted in the customization of kernel functions. Four commonly adopted kernel functions are studied. Results reveal that weighted feature vectors improve the accuracy by 11% compared to the computation using the prime kernel. Evaluation shows that ECG-DDD improved the accuracy by 8% to 18% compared to prevailing methods.

Evaluation of Candidate Measures for Home-Based Screening of Sleep Disordered Breathing in Taiwanese Bus Drivers

PubMed Central

Ting, Hua; Huang, Ren-Jing; Lai, Ching-Hsiang; Chang, Shen-Wen; Chung, Ai-Hui; Kuo, Teng-Yao; Chang, Ching-Haur; Shih, Tung-Sheng; Lee, Shin-Da

2014-01-01

Background: Sleepiness-at-the-wheel has been identified as a major cause of highway accidents. The aim of our study is identifying the candidate measures for home-based screening of sleep disordered breathing in Taiwanese bus drivers, instead of polysomnography. Methods: Overnight polysomnography accompanied with simultaneous measurements of alternative screening devices (pulse oximetry, ApneaLink, and Actigraphy), heart rate variability, wake-up systolic blood pressure and questionnaires were completed by 151 eligible participants who were long-haul bus drivers with a duty period of more than 12 h a day and duty shifting. Results: 63.6% of professional bus drivers were diagnosed as having sleep disordered breathing and had a higher body mass index, neck circumference, systolic blood pressure, arousal index and desaturation index than those professional bus drivers without evidence of sleep disordered breathing. Simple home-based candidate measures: (1) Pulse oximetry, oxygen-desaturation indices by ≥3% and 4% (r = 0.87∼0.92); (2) Pulse oximetry, pulse-rising indices by ≥7% and 8% from a baseline (r = 0.61∼0.89); and (3) ApneaLink airflow detection, apnea-hypopnea indices (r = 0.70∼0.70), based on recording-time or Actigraphy-corrected total sleep time were all significantly correlated with, and had high agreement with, corresponding polysomnographic apnea-hypopnea indices [(1) 94.5%∼96.6%, (2) 93.8%∼97.2%, (3) 91.1%∼91.3%, respectively]. Conversely, no validities of SDB screening were found in the multi-variables apnea prediction questionnaire, Epworth Sleepiness Scale, night-sleep heart rate variability, wake-up systolic blood pressure and anthropometric variables. Conclusions: The indices of pulse oximetry and apnea flow detection are eligible criteria for home-based screening of sleep disordered breathing, specifically for professional drivers. PMID:24803198

A meta-analysis of in-vehicle and nomadic voice-recognition system interaction and driving performance.

PubMed

Simmons, Sarah M; Caird, Jeff K; Steel, Piers

2017-09-01

Driver distraction is a growing and pervasive issue that requires multiple solutions. Voice-recognition (V-R) systems may decrease the visual-manual (V-M) demands of a wide range of in-vehicle system and smartphone interactions. However, the degree that V-R systems integrated into vehicles or available in mobile phone applications affect driver distraction is incompletely understood. A comprehensive meta-analysis of experimental studies was conducted to address this knowledge gap. To meet study inclusion criteria, drivers had to interact with a V-R system while driving and doing everyday V-R tasks such as dialing, initiating a call, texting, emailing, destination entry or music selection. Coded dependent variables included detection, reaction time, lateral position, speed and headway. Comparisons of V-R systems with baseline driving and/or a V-M condition were also coded. Of 817 identified citations, 43 studies involving 2000 drivers and 183 effect sizes (r) were analyzed in the meta-analysis. Compared to baseline, driving while interacting with a V-R system is associated with increases in reaction time and lane positioning, and decreases in detection. When V-M systems were compared to V-R systems, drivers had slightly better performance with the latter system on reaction time, lane positioning and headway. Although V-R systems have some driving performance advantages over V-M systems, they have a distraction cost relative to driving without any system at all. The pattern of results indicates that V-R systems impose moderate distraction costs on driving. In addition, drivers minimally engage in compensatory performance adjustments such as reducing speed and increasing headway while using V-R systems. Implications of the results for theory, design guidelines and future research are discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Characteristics of On-Road Driving Performance of Persons With Central Vision Loss Who Use Bioptic Telescopes

PubMed Central

Wood, Joanne M.; McGwin, Gerald; Elgin, Jennifer; Searcey, Karen; Owsley, Cynthia

2013-01-01

Purpose. To compare the on-road driving performance of visually impaired drivers using bioptic telescopes with age-matched controls. Methods. Participants included 23 persons (mean age = 33 ± 12 years) with visual acuity of 20/63 to 20/200 who were legally licensed to drive through a state bioptic driving program, and 23 visually normal age-matched controls (mean age = 33 ± 12 years). On-road driving was assessed in an instrumented dual-brake vehicle along 14.6 miles of city, suburban, and controlled-access highways. Two backseat evaluators independently rated driving performance using a standardized scoring system. Vehicle control was assessed through vehicle instrumentation and video recordings used to evaluate head movements, lane-keeping, pedestrian detection, and frequency of bioptic telescope use. Results. Ninety-six percent (22/23) of bioptic drivers and 100% (23/23) of controls were rated as safe to drive by the evaluators. There were no group differences for pedestrian detection, or ratings for scanning, speed, gap judgments, braking, indicator use, or obeying signs/signals. Bioptic drivers received worse ratings than controls for lane position and steering steadiness and had lower rates of correct sign and traffic signal recognition. Bioptic drivers made significantly more right head movements, drove more often over the right-hand lane marking, and exhibited more sudden braking than controls. Conclusions. Drivers with central vision loss who are licensed to drive through a bioptic driving program can display proficient on-road driving skills. This raises questions regarding the validity of denying such drivers a license without the opportunity to train with a bioptic telescope and undergo on-road evaluation. PMID:23640044

Diagnostic algorithm for detection of targetable driver mutations in lung adenocarcinomas: Comprehensive analyses of 205 cases with immunohistochemistry, real-time PCR and fluorescence in situ hybridization methods.

PubMed

Kao, Hua-Lin; Yeh, Yi-Chen; Lin, Chin-Hsuan; Hsu, Wei-Fang; Hsieh, Wen-Yu; Ho, Hsiang-Ling; Chou, Teh-Ying

2016-11-01

Analysis of the targetable driver mutations is now recommended in all patients with advanced lung adenocarcinoma. Molecular-based methods are usually adopted, however, along with the implementation of highly sensitive and/or mutation-specific antibodies, immunohistochemistry (IHC) has been considered an alternative method for identifying driver mutations in lung adenocarcinomas. A total of 205 lung adenocarcinomas were examined for EGFR mutations and ALK and ROS1 rearrangements using real-time PCR, fluorescence in situ hybridization (FISH) and IHC in parallel. The performance of different commercially available IHC antibody clones toward targetable driver mutations was evaluated. The association between these driver mutations and clinicopathological characteristics was also analyzed. In 205 cases we studied, 58.5% were found to harbor EGFR mutations, 6.3% ALK rearrangements and 1.0% ROS1 rearrangements. Compared to molecular-based methods, IHC of EGFR mutations showed an excellent specificity but the sensitivity is suboptimal, while IHC of ALK and ROS1 rearrangements demonstrated high sensitivity and specificity. No significant difference regarding the performance of different antibody clones toward these driver mutations was observed, except that clone SP125 showed a higher sensitivity than 43B2 in the detection of p.L858R of EGFR. In circumstances such as poor quality of nucleic acids or low content of tumor cells, IHC of EGFR mutation-specific antibodies could be used as an alternative method. Patients negative for EGFR mutations are subjected to further analysis on ALK and ROS1 rearrangements using IHC methods. Herein, we proposed a lung adenocarcinoma testing algorithm for the application of IHC in therapeutic diagnosis. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Understanding driver behavior at grade crossings through signal detection theory.

DOT National Transportation Integrated Search

2013-01-31

This report uses signal detection theory (SDT) to model motorists decisionmaking strategies at grade crossings in order to understand the factors that influence such decisions and to establish a framework for evaluating the impact of proposed coun...

Understanding driver behavior at grade crossings through signal detection theory.

DOT National Transportation Integrated Search

2013-01-01

This report uses signal detection theory (SDT) to model motorists decisionmaking strategies at grade crossings in order to understand the factors that influence such decisions and to establish a framework for evaluating the impact of proposed coun...

Random breath testing in Queensland and Western Australia: examination of how the random breath testing rate influences alcohol related traffic crash rates.

PubMed

Ferris, Jason; Mazerolle, Lorraine; King, Mark; Bates, Lyndel; Bennett, Sarah; Devaney, Madonna

2013-11-01

In this paper we explore the relationship between monthly random breath testing (RBT) rates (per 1000 licensed drivers) and alcohol-related traffic crash (ARTC) rates over time, across two Australian states: Queensland and Western Australia. We analyse the RBT, ARTC and licensed driver rates across 12 years; however, due to administrative restrictions, we model ARTC rates against RBT rates for the period July 2004 to June 2009. The Queensland data reveals that the monthly ARTC rate is almost flat over the five year period. Based on the results of the analysis, an average of 5.5 ARTCs per 100,000 licensed drivers are observed across the study period. For the same period, the monthly rate of RBTs per 1000 licensed drivers is observed to be decreasing across the study with the results of the analysis revealing no significant variations in the data. The comparison between Western Australia and Queensland shows that Queensland's ARTC monthly percent change (MPC) is 0.014 compared to the MPC of 0.47 for Western Australia. While Queensland maintains a relatively flat ARTC rate, the ARTC rate in Western Australia is increasing. Our analysis reveals an inverse relationship between ARTC RBT rates, that for every 10% increase in the percentage of RBTs to licensed driver there is a 0.15 decrease in the rate of ARTCs per 100,000 licenced drivers. Moreover, in Western Australia, if the 2011 ratio of 1:2 (RBTs to annual number of licensed drivers) were to double to a ratio of 1:1, we estimate the number of monthly ARTCs would reduce by approximately 15. Based on these findings we believe that as the number of RBTs conducted increases the number of drivers willing to risk being detected for drinking driving decreases, because the perceived risk of being detected is considered greater. This is turn results in the number of ARTCs diminishing. The results of this study provide an important evidence base for policy decisions for RBT operations. Copyright © 2013 Elsevier Ltd. All rights reserved.

Review of Fatigue Management Technologies for Enhanced Military Vehicle Safety and Performance

DTIC Science & Technology

2013-09-01

Tung University, Taiwan), Quasar DSI 10/20 ( Quantum Science and Applied Research, Inc.; San Diego, CA), and the B-Alert systems (Advanced Brain...apnea; Drowsiness; Deception; Emotional response; Fall; Heart rate; Muscle tension; Motility; Relaxation; Sleep stages; Stales of consciousness ...Quasar EEG Dry Sensor Interface 10120 (05110120) Quantum Applied Science and Research Inc. (Quasar USA) \\YMv.quasarusa.com Readiband"’ Fatigue

The Analgesic Efficacy of Nonsteroidal Anti-inflammatory Agents (NSAIDs) in Patients Undergoing Cesarean Deliveries: A Meta-Analysis.

PubMed

Zeng, Angela M; Nami, Nina F; Wu, Christopher L; Murphy, Jamie D

Postoperative pain after cesarean delivery, which accounts for approximately 1 in 3 live births in the United States, can be severe in many patients. Nonsteroidal anti-inflammatory agents (NSAIDs) are potent analgesics that are effective in the treatment of postoperative pain. In this meta-analysis, we assessed the analgesic efficacy of NSAIDs in postoperative cesarean delivery patients. An electronic literature search of the Library of Medicine's PubMed, Cochrane CENTRAL, Scopus, and EMBASE databases was conducted in May 2013 and updated in January 2015 (Appendix, Supplemental Digital Content 1, http://links.lww.com/AAP/A174). Searches were limited to randomized controlled trials. The primary outcome variable was visual analog scale or numerical rating scale pain scores. Secondary outcomes included cumulative postoperative opioid consumption and opioid-related adverse effects (drowsiness/sedation, nausea, and vomiting). Data extraction was performed independently by 2 reviewers. Extracted data were input into Review Manager. Twenty-two randomized controlled trials compared a NSAID (n = 639) to a control (n = 674). Patients in the NSAID group versus control reported lower pain scores at 12 hours (P = 0.003) and at 24 hours (P < 0.001). Subgroup analysis showed a significant difference in pain scores at 24 hours, with patients receiving NSAIDs via intravenous/intramuscular (P < 0.001) route, but not the oral (P = 0.39) or rectal routes (P = 0.99). Significantly lower average pain scores were reported for pain with movement at 24 hours in the NSAID group (P = 0.001). Patients in the NSAID group versus controls consumed significantly less opioids (P < 0.001) and had significantly less drowsiness/sedation (P = 0.03), but there was no significant difference between the groups with regard to nausea or vomiting (P = 0.48 and P = 0.17, respectively). The perioperative use of NSAIDs in cesarean delivery patients will result in a significantly lower pain scores, less opioid consumption, and less drowsiness/sedation but no difference in nausea or vomiting compared to those who did not receive NSAIDs. Further research should address the optimal NSAID regimen and examine the effect of improved analgesia on patient-centered outcomes such as patient satisfaction and quality of breastfeeding.

Field evaluation of the Los Angeles Police Department drug detection procedure.

DOT National Transportation Integrated Search

1986-12-01

The Los Angeles Police Department (LAPD) has developed a drug recognition program designed to provide trained officers the ability to detect drug-impaired drivers and to identify the responsible drug class (e.g., stimulant, depressant, etc. ). As par...

Delirium diagnosis methodology used in research: a survey-based study.

PubMed

Neufeld, Karin J; Nelliot, Archana; Inouye, Sharon K; Ely, E Wesley; Bienvenu, O Joseph; Lee, Hochang Benjamin; Needham, Dale M

2014-12-01

To describe methodology used to diagnose delirium in research studies evaluating delirium detection tools. The authors used a survey to address reference rater methodology for delirium diagnosis, including rater characteristics, sources of patient information, and diagnostic process, completed via web or telephone interview according to respondent preference. Participants were authors of 39 studies included in three recent systematic reviews of delirium detection instruments in hospitalized patients. Authors from 85% (N = 33) of the 39 eligible studies responded to the survey. The median number of raters per study was 2.5 (interquartile range: 2-3); 79% were physicians. The raters' median duration of clinical experience with delirium diagnosis was 7 years (interquartile range: 4-10), with 5% having no prior clinical experience. Inter-rater reliability was evaluated in 70% of studies. Cognitive tests and delirium detection tools were used in the delirium reference rating process in 61% (N = 21) and 45% (N = 15) of studies, respectively, with 33% (N = 11) using both and 27% (N = 9) using neither. When patients were too drowsy or declined to participate in delirium evaluation, 70% of studies (N = 23) used all available information for delirium diagnosis, whereas 15% excluded such patients. Significant variability exists in reference standard methods for delirium diagnosis in published research. Increasing standardization by documenting inter-rater reliability, using standardized cognitive and delirium detection tools, incorporating diagnostic expert consensus panels, and using all available information in patients declining or unable to participate with formal testing may help advance delirium research by increasing consistency of case detection and improving generalizability of research results. Copyright © 2014 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

Assessing sleepiness and sleep disorders in Australian long-distance commercial vehicle drivers: self-report versus an "at home" monitoring device.

PubMed

Sharwood, Lisa N; Elkington, Jane; Stevenson, Mark; Grunstein, Ronald R; Meuleners, Lynn; Ivers, Rebecca Q; Haworth, Narelle; Norton, Robyn; Wong, Keith K

2012-04-01

As obstructive sleep apnea (OSA) is associated with a higher risk of motor vehicle crashes, there is increasing regulatory interest in the identification of commercial motor vehicle (CMV) drivers with this condition. This study aimed to determine the relationship between subjective versus objective assessment of OSA in CMV drivers. Cross-sectional survey. Heavy vehicle truck stops located across the road network of 2 large Australian states. A random sample of long distance commercial vehicle drivers (n = 517). None. Drivers were interviewed regarding their driving experience, personal health, shift schedules, payments, and various questions on sleep and tiredness in order to describe their sleep health across a range of variables. In addition, home recordings using a flow monitor were used during one night of sleep. Only 4.4% of drivers reported a previous diagnosis of sleep apnea, while our at home diagnostic test found a further 41% of long-distance heavy vehicle drivers likely to have sleep apnea. The multivariable apnea prediction index, based on self-report measures, showed poor agreement with the home-monitor detected sleep apnea (AUC 0.58, 95%CI = 0.49-0.62), and only 12% of drivers reported daytime sleepiness (Epworth Sleepiness Scale score > 10). Thirty-six percent of drivers were overweight and a further 50% obese; 49% of drivers were cigarette smokers. Sleep apnea remains a significant and unrecognized problem in CMV drivers, who we found to have multiple health risks. Objective testing for this sleep disorder needs to be considered, as symptom reports and self-identification appear insufficient to accurately identify those at risk.

The impact of high-risk drivers and benefits of limiting their driving degree of freedom.

PubMed

Habtemichael, Filmon G; de Picado-Santos, Luis

2013-11-01

The perception of drivers regarding risk-taking behaviour is widely varied. High-risk drivers are the segment of drivers who are disproportionately represented in the majority of crashes. This study examines the typologies of drivers in risk-taking behaviour, the common high-risk driving errors (speeding, close following, abrupt lane-changing and impaired driving), their safety consequences and the technological (ITS) devices for their detection and correction. Limiting the driving degree of freedom of high-risk drivers is proposed and its benefits on safety as well as traffic operations are quantified using VISSIM microscopic traffic simulation at various proportions of high-risk drivers; namely, 4%, 8% and 12%. Assessment of the safety benefits was carried out by using the technique of simulated vehicle conflicts which was validated against historic crashes, and reduction in travel time was used to quantify the operational benefits. The findings imply that limiting the freedom of high-risk drivers resulted in a reduction of crashes by 12%, 21% and 27% in congested traffic conditions; 9%, 13% and 18% in lightly congested traffic conditions as well as 9%, 10% and 17% in non-congested traffic conditions for high-risk drivers in proportions of 4%, 8% and 12% respectively. Moreover, the surrogate safety measures indicated that there was a reduction in crash severity levels. The operational benefits amounted to savings of nearly 1% in travel time for all the proportions of high-risk drivers considered. The study concluded that limiting the freedom of high-risk drivers has safety and operational benefits; though there could be social, legal and institutional concerns for its practical implementation. Copyright © 2013 Elsevier Ltd. All rights reserved.

Experiences of model year 2011 Dodge and Jeep owners with collision avoidance and related technologies.

PubMed

Cicchino, Jessica B; McCartt, Anne T

2015-01-01

Crash avoidance technologies have the potential to prevent or mitigate many crashes, but their effectiveness depends on drivers' acceptance and proper use. Owners of 2011 Dodge Charger, Dodge Durango, and Jeep Grand Cherokee vehicles were interviewed about their experiences with their vehicles' technologies. Interviews were conducted in April 2013 with 215 owners of Dodge and Jeep vehicles with adaptive cruise control and forward collision warning and 215 owners with blind spot monitoring and rear cross-path detection. Most owners said that they always keep each collision avoidance technology turned on, and more than 90% of owners with each system would want the technology again on their next vehicle. The majority believed that the systems had helped prevent a collision; this ranged from 54% of drivers with forward collision warning to more than three-quarters with blind spot monitoring and rear cross-path detection. Some owners reported behavioral changes with the systems, but over-reliance on them is not prevalent. Reported use of the systems varied by the age and gender of the driver and duration of vehicle ownership to a greater degree than in previous surveys of luxury Volvo and Infiniti vehicles with collision avoidance technologies. Notably, drivers aged 40 and younger were most likely to report that forward collision warning had alerted them multiple times and that it had prevented a collision and that they follow the vehicle ahead less closely with adaptive cruise control. Reports of waiting for the alert from forward collision warning before braking were infrequent but increased with duration of ownership. However, these reports could reflect confusion of the system with adaptive cruise control, which alerts drivers when braking is necessary to maintain a preset speed or following distance but a crash is not imminent. Consistent with previous surveys of luxury vehicle owners with collision avoidance technologies, acceptance and use remains high among owners of more mainstream vehicles. Varying experiences with the technologies by driver age and gender suggest that safety benefits are not uniform for all drivers, and differential benefits may become increasingly apparent as collision avoidance technologies become available to a more heterogeneous population of drivers. The potential for over-reliance on the technologies should continue to be monitored, especially as drivers gain more experience with them.

High-Throughput Functional Validation of Progression Drivers in Lung Adenocarcinoma

DTIC Science & Technology

2013-09-01

2) a novel molecular barcoding approach that facilitates cost- effective detection of driver events following in vitro and in vivo functional screens...aberration construction pipeline, which we named High-Throughput 3 Mutagenesis and Molecular Barcoding (HiTMMoB; Fig.1). We have therefore been able...lentiviral vector specially constructed for this project. This vector is compatible with our flexible molecular barcoding technology (Fig. 1), thus each

Sclerochronology - tool for uncovering environmental drivers in a semi-enclosed sea

NASA Astrophysics Data System (ADS)

Vilibic, I.; Peharda, M.; Dzoic, T.; Markulin, K.; Dunic, N.; Mihanovic, H.; Gacic, M.; Black, B.; Uvanovic, H.; Ezgeta-Balic, D.; Sepic, J.; Kovac, Z.; Zupan, I.

2017-12-01

A number of proxy-based methods have been developed in detection of long-term environmental changes. Among them is sclerochronology which, through analysis of inter annular variations in widths of growth increments, has been advancing in recent decades. Albeit the main focus has been directed towards species living over centuries and in cold seas (primarily Arctica islandica), application of sclerochronology in temperate seas has potential to contribute toward better understanding of physical and environmental properties and processes in semi-enclosed seas. Here, we are presenting the major results of the project SCOOL (Sclerochronology as a tool for detecting long-term Adriatic environmental changes, http://www.izor.hr/web/scool), aiming to relate relatively long-lived bivalve species Glycymeris pilosa to the major environmental drivers in a semi-enclosed sea of the Mediterranean, the Adriatic Sea. The open Adriatic Sea is known to be dominated by quasi-decadal oscillations in thermohaline and biogeochemical properties driven by the dense water formation, so a question has been posed to quantify its role in driving the bivalve growth with respect to other environmental drivers (like heat fluxes, river discharges, precipitation). It seems that these basin-wide oscillations are dominating over locally-driven processes, even in coastal regions that include very shallow northern Adriatic. The northern Adriatic has been previously considered as quasi-separated from the basin-wide dynamics; such conclusions have been reached from multi-decadal in situ sampling series of different physical and chemical parameters. Therefore, sclerochronology is documented to be a reliable tool for detection of environmental drivers in a coastal temperate sea.

Reducing the threat of wildlife-vehicle collisions during peak tourism periods using a Roadside Animal Detection System.

PubMed

Grace, Molly K; Smith, Daniel J; Noss, Reed F

2017-12-01

Roadside Animal Detection Systems (RADS) aim to reduce the frequency of wildlife-vehicle collisions. Unlike fencing and wildlife passages, RADS do not attempt to keep animals off the road; rather, they attempt to modify driver behavior by detecting animals near the road and warning drivers with flashing signs. A RADS was installed in Big Cypress National Park (Florida, USA) in 2012 in response to an increased number of Florida panther mortalities. To assess driver response, we measured the speed of individual cars on the road when the RADS was active (flashing) and inactive (not flashing) during the tourist season (November-March) and the off-season (April-October), which vary dramatically in traffic volume. We also used track beds and camera traps to assess whether roadside activity of large mammal species varied between seasons. In the tourist season, the activation of the RADS caused a significant reduction in vehicle speed. However, this effect was not observed in the off-season. Track and camera data showed that the tourist season coincided with peak periods of activity for several large mammals of conservation interest. Drivers in the tourist season generally drove faster than those in the off-season, so a reduction in speed in response to the RADS is more beneficial in the tourist season. Because traffic volume and roadside activity of several species of conservation interest both peak during the tourist season, our study indicates that the RADS has the potential to reduce the number of accidents during this period of heightened risk. Copyright © 2017 Elsevier Ltd. All rights reserved.

A System for Traffic Violation Detection

PubMed Central

Aliane, Nourdine; Fernandez, Javier; Mata, Mario; Bemposta, Sergio

2014-01-01

This paper describes the framework and components of an experimental platform for an advanced driver assistance system (ADAS) aimed at providing drivers with a feedback about traffic violations they have committed during their driving. The system is able to detect some specific traffic violations, record data associated to these faults in a local data-base, and also allow visualization of the spatial and temporal information of these traffic violations in a geographical map using the standard Google Earth tool. The test-bed is mainly composed of two parts: a computer vision subsystem for traffic sign detection and recognition which operates during both day and nighttime, and an event data recorder (EDR) for recording data related to some specific traffic violations. The paper covers firstly the description of the hardware architecture and then presents the policies used for handling traffic violations. PMID:25421737

A system for traffic violation detection.

PubMed

Aliane, Nourdine; Fernandez, Javier; Mata, Mario; Bemposta, Sergio

2014-11-24

This paper describes the framework and components of an experimental platform for an advanced driver assistance system (ADAS) aimed at providing drivers with a feedback about traffic violations they have committed during their driving. The system is able to detect some specific traffic violations, record data associated to these faults in a local data-base, and also allow visualization of the spatial and temporal information of these traffic violations in a geographical map using the standard Google Earth tool. The test-bed is mainly composed of two parts: a computer vision subsystem for traffic sign detection and recognition which operates during both day and nighttime, and an event data recorder (EDR) for recording data related to some specific traffic violations. The paper covers firstly the description of the hardware architecture and then presents the policies used for handling traffic violations.

Noise and contrast comparison of visual and infrared images of hazards as seen inside an automobile

NASA Astrophysics Data System (ADS)

Meitzler, Thomas J.; Bryk, Darryl; Sohn, Eui J.; Lane, Kimberly; Bednarz, David; Jusela, Daniel; Ebenstein, Samuel; Smith, Gregory H.; Rodin, Yelena; Rankin, James S., II; Samman, Amer M.

2000-06-01

The purpose of this experiment was to quantitatively measure driver performance for detecting potential road hazards in visual and infrared (IR) imagery of road scenes containing varying combinations of contrast and noise. This pilot test is a first step toward comparing various IR and visual sensors and displays for the purpose of an enhanced vision system to go inside the driver compartment. Visible and IR road imagery obtained was displayed on a large screen and on a PC monitor and subject response times were recorded. Based on the response time, detection probabilities were computed and compared to the known time of occurrence of a driving hazard. The goal was to see what combinations of sensor, contrast and noise enable subjects to have a higher detection probability of potential driving hazards.

Risk-taking on the road and in the mind: behavioural and neural patterns of decision making between risky and safe drivers.

PubMed

Ba, Yutao; Zhang, Wei; Peng, QiJia; Salvendy, Gavriel; Crundall, David

2016-01-01

Drivers' risk-taking is a key issue of road safety. This study explored individual differences in drivers' decision-making, linking external behaviours to internal neural activity, to reveal the cognitive mechanisms of risky driving. Twenty-four male drivers were split into two groups (risky vs. safe drivers) via the Drivier Behaviour Questionnaire-violation. The risky drivers demonstrated higher preference for the risky choices in the paradigms of Iowa Gambling Task and Balloon Analogue Risk Task. More importantly, the risky drivers showed lower amplitudes of feedback-related negativity (FRN) and loss-minus-gain FRN in both paradigms, which indicated their neural processing of error-detection. A significant difference of P300 amplitudes was also reported between groups, which indicated their neural processing of reward-evaluation and were modified by specific paradigm and feedback. These results suggested that the neural basis of risky driving was the decision patterns less revised by losses and more motivated by rewards. Risk-taking on the road is largely determined by inherent cognitive mechanisms, which can be indicated by the behavioural and neural patterns of decision-making. In this regard, it is feasible to quantize drivers’ riskiness in the cognitive stage before actual risky driving or accidents, and intervene accordingly.

The reliability and effectiveness of an electromagnetic animal detection and driver warning system.

DOT National Transportation Integrated Search

2012-03-01

"This report contains data on the reliability and effectiveness of an animal detection system project along US Hwy 160 : between Durango and Bayfield, Colorado. The system that was first installed was a Perimitrax system from Senstar : Corporation....

Evaluating the impact of grade crossing safety factors through signal detection theory

DOT National Transportation Integrated Search

2012-10-22

The purpose of this effort was to apply signal detection theory to descriptively model the impact : of five grade crossing safety factors to understand their effect on driver decision making. The : safety factors consisted of: improving commercial mo...

Risk and safety perception on urban and rural roads: Effects of environmental features, driver age and risk sensitivity.

PubMed

Cox, Jolene A; Beanland, Vanessa; Filtness, Ashleigh J

2017-10-03

The ability to detect changing visual information is a vital component of safe driving. In addition to detecting changing visual information, drivers must also interpret its relevance to safety. Environmental changes considered to have high safety relevance will likely demand greater attention and more timely responses than those considered to have lower safety relevance. The aim of this study was to explore factors that are likely to influence perceptions of risk and safety regarding changing visual information in the driving environment. Factors explored were the environment in which the change occurs (i.e., urban vs. rural), the type of object that changes, and the driver's age, experience, and risk sensitivity. Sixty-three licensed drivers aged 18-70 years completed a hazard rating task, which required them to rate the perceived hazardousness of changing specific elements within urban and rural driving environments. Three attributes of potential hazards were systematically manipulated: the environment (urban, rural); the type of object changed (road sign, car, motorcycle, pedestrian, traffic light, animal, tree); and its inherent safety risk (low risk, high risk). Inherent safety risk was manipulated by either varying the object's placement, on/near or away from the road, or altering an infrastructure element that would require a change to driver behavior. Participants also completed two driving-related risk perception tasks, rating their relative crash risk and perceived risk of aberrant driving behaviors. Driver age was not significantly associated with hazard ratings, but individual differences in perceived risk of aberrant driving behaviors predicted hazard ratings, suggesting that general driving-related risk sensitivity plays a strong role in safety perception. In both urban and rural scenes, there were significant associations between hazard ratings and inherent safety risk, with low-risk changes perceived as consistently less hazardous than high-risk impact changes; however, the effect was larger for urban environments. There were also effects of object type, with certain objects rated as consistently more safety relevant. In urban scenes, changes involving pedestrians were rated significantly more hazardous than all other objects, and in rural scenes, changes involving animals were rated as significantly more hazardous. Notably, hazard ratings were found to be higher in urban compared with rural driving environments, even when changes were matched between environments. This study demonstrates that drivers perceive rural roads as less risky than urban roads, even when similar scenarios occur in both environments. Age did not affect hazard ratings. Instead, the findings suggest that the assessment of risk posed by hazards is influenced more by individual differences in risk sensitivity. This highlights the need for driver education to account for appraisal of hazards' risk and relevance, in addition to hazard detection, when considering factors that promote road safety.

Multi-vehicle detection with identity awareness using cascade Adaboost and Adaptive Kalman filter for driver assistant system.

PubMed

Wang, Baofeng; Qi, Zhiquan; Chen, Sizhong; Liu, Zhaodu; Ma, Guocheng

2017-01-01

Vision-based vehicle detection is an important issue for advanced driver assistance systems. In this paper, we presented an improved multi-vehicle detection and tracking method using cascade Adaboost and Adaptive Kalman filter(AKF) with target identity awareness. A cascade Adaboost classifier using Haar-like features was built for vehicle detection, followed by a more comprehensive verification process which could refine the vehicle hypothesis in terms of both location and dimension. In vehicle tracking, each vehicle was tracked with independent identity by an Adaptive Kalman filter in collaboration with a data association approach. The AKF adaptively adjusted the measurement and process noise covariance through on-line stochastic modelling to compensate the dynamics changes. The data association correctly assigned different detections with tracks using global nearest neighbour(GNN) algorithm while considering the local validation. During tracking, a temporal context based track management was proposed to decide whether to initiate, maintain or terminate the tracks of different objects, thus suppressing the sparse false alarms and compensating the temporary detection failures. Finally, the proposed method was tested on various challenging real roads, and the experimental results showed that the vehicle detection performance was greatly improved with higher accuracy and robustness.

Driver Distraction Using Visual-Based Sensors and Algorithms.

PubMed

Fernández, Alberto; Usamentiaga, Rubén; Carús, Juan Luis; Casado, Rubén

2016-10-28

Driver distraction, defined as the diversion of attention away from activities critical for safe driving toward a competing activity, is increasingly recognized as a significant source of injuries and fatalities on the roadway. Additionally, the trend towards increasing the use of in-vehicle information systems is critical because they induce visual, biomechanical and cognitive distraction and may affect driving performance in qualitatively different ways. Non-intrusive methods are strongly preferred for monitoring distraction, and vision-based systems have appeared to be attractive for both drivers and researchers. Biomechanical, visual and cognitive distractions are the most commonly detected types in video-based algorithms. Many distraction detection systems only use a single visual cue and therefore, they may be easily disturbed when occlusion or illumination changes appear. Moreover, the combination of these visual cues is a key and challenging aspect in the development of robust distraction detection systems. These visual cues can be extracted mainly by using face monitoring systems but they should be completed with more visual cues (e.g., hands or body information) or even, distraction detection from specific actions (e.g., phone usage). Additionally, these algorithms should be included in an embedded device or system inside a car. This is not a trivial task and several requirements must be taken into account: reliability, real-time performance, low cost, small size, low power consumption, flexibility and short time-to-market. The key points for the development and implementation of sensors to carry out the detection of distraction will also be reviewed. This paper shows a review of the role of computer vision technology applied to the development of monitoring systems to detect distraction. Some key points considered as both future work and challenges ahead yet to be solved will also be addressed.

Driver Distraction Using Visual-Based Sensors and Algorithms

PubMed Central

Fernández, Alberto; Usamentiaga, Rubén; Carús, Juan Luis; Casado, Rubén

2016-01-01

Driver distraction, defined as the diversion of attention away from activities critical for safe driving toward a competing activity, is increasingly recognized as a significant source of injuries and fatalities on the roadway. Additionally, the trend towards increasing the use of in-vehicle information systems is critical because they induce visual, biomechanical and cognitive distraction and may affect driving performance in qualitatively different ways. Non-intrusive methods are strongly preferred for monitoring distraction, and vision-based systems have appeared to be attractive for both drivers and researchers. Biomechanical, visual and cognitive distractions are the most commonly detected types in video-based algorithms. Many distraction detection systems only use a single visual cue and therefore, they may be easily disturbed when occlusion or illumination changes appear. Moreover, the combination of these visual cues is a key and challenging aspect in the development of robust distraction detection systems. These visual cues can be extracted mainly by using face monitoring systems but they should be completed with more visual cues (e.g., hands or body information) or even, distraction detection from specific actions (e.g., phone usage). Additionally, these algorithms should be included in an embedded device or system inside a car. This is not a trivial task and several requirements must be taken into account: reliability, real-time performance, low cost, small size, low power consumption, flexibility and short time-to-market. The key points for the development and implementation of sensors to carry out the detection of distraction will also be reviewed. This paper shows a review of the role of computer vision technology applied to the development of monitoring systems to detect distraction. Some key points considered as both future work and challenges ahead yet to be solved will also be addressed. PMID:27801822

The NHTSA & NCSDR program to combat drowsy driving : a report to the House and Senate Appropriations Committees describing collaboration between National Highway Traffic Safety Administration and National Center on Sleep Disorders Research, National Heart, Lung and Blood Institute, National Institutes of Health

DOT National Transportation Integrated Search

1999-03-15

In 1996, the National Highway Traffic Safety Administration (NHTSA) embarked on a congressionally mandated effort to develop educational countermeasures to the effects of fatigue, sleep disorders, and inattention on highway safety. In collaboration w...

The Effect of Mild Motion Sickness and Sopite Syndrome on Multitasking Cognitive Performance

DTIC Science & Technology

2013-03-01

Ledin, & Falkmer, 2009), in command and control tasks ( Cowings , Toscano, DeRoshia, & Tauson, 2001), or in visual search (Golding & Kerguelen, 1992...common and frequent. Research has shown that drowsiness is among the most frequent symptoms associated with motion sickness ( Cowings et al., 2001...sickness ( Cowings , Naifeh, & Toscano, 1990; J. C. Miller, Sharkey, Graham, & McCauley, 1993). The following paragraphs will focus on the

Drug use among drivers who drank on alcohol outlets from Porto Alegre, Brazil.

PubMed

De Boni, Raquel B; Bastos, Francisco Inacio; de Vasconcellos, Mauricio; Oliveira, Fernanda; Limberger, Renata P; Pechansky, Flavio

2014-01-01

Driving under the influence of multiple substances is a public health concern, but there is little epidemiological data about their combined use and putative impact on driving in low and middle-income countries where traffic crashes have been clustering in recent years. The aim of this study is to estimate the prevalence of alcohol and drug use - as well as their associated factors - among drivers in the context of alcohol outlets (AOs). A probability three-stage sample survey was conducted in Porto Alegre, Brazil. Individuals who were leaving AO were screened, with the selection of 683 drivers who met the inclusion criteria. Drivers answered a structured interview, were breathalyzed, and had their saliva collected for drug screening. Prevalences were assessed using domain estimation and logistic regression models assessed covariates associated with substance use. Benzodiazepines 3.9% (SE 2.13) and cocaine 3.8% (SE 1.3) were the most frequently detected drugs in saliva. Among drivers who were going to drive, 11% had at least one drug identified by the saliva drug screening, 0.4% two, and 0.1% three drugs in addition to alcohol. In multivariable analyses, having a blood alcohol concentration (BAC)>0.06% was found to be associated with a 3.64 times (CI 95% 1.79-7.39) higher chance of drug detection, compared with interviewees with lower BACs. To drive under the influence of multiple substances is likely to be found in this setting, highlighting an association between harmful patterns of consume of alcohol and the misuse of other substances. Copyright © 2013 Elsevier Ltd. All rights reserved.

Hydrogen sulfide gas emissions in the human-occupied zone during disturbance and removal of stored spent mushroom compost.

PubMed

Velusami, B; Curran, T P; Grogan, H M

2013-10-01

Hydrogen sulfide (H2S) gas levels were monitored in the human-occupied zone at four spent mushroom compost (SMC) storage sites during removal of SMC for application on agricultural land. During SMC removal operations, H2S gas monitors were mounted on the outside of the tractor positioned at the SMC periphery, and worn by individual tractor drivers. The highest H2S concentrations (10 s average) detected outside the tractor, at the SMC periphery, and for the tractor driver were, respectively, 454, 249, and 100 ppm for the outdoor sites and 214, 75, and 51 ppm for the indoor sites. The highest short-term exposure values (STEV over a 15 min period) outside the tractor at the SMC periphery, and for the tractor driver were 147, 55, and 86 ppm for the outdoor sites and 19, 9, and 10 ppm for the indoor sites. The values exceeded the current maximum permissible concentration limit of 10 ppm for all the sites except for the SMC periphery and tractor driver at the indoor sites. Results suggest that H2S levels detected at indoor storage sites during SMC removal are lower compared to outdoor storage sites. Results indicate that there is a substantial health and safety risk associated with working in the vicinity of stored SMC when it is being disturbed and removed for land application, and that the risk is great for the tractor driver. This article discusses possible control measures and lists recommendations to reduce the risks.

Two visual systems in monitoring of dynamic traffic: effects of visual disruption.

PubMed

Zheng, Xianjun Sam; McConkie, George W

2010-05-01

Studies from neurophysiology and neuropsychology provide support for two separate object- and location-based visual systems, ventral and dorsal. In the driving context, a study was conducted using a change detection paradigm to explore drivers' ability to monitor the dynamic traffic flow, and the effects of visual disruption on these two visual systems. While driving, a discrete change, such as vehicle location, color, or identity, was occasionally made in one of the vehicles on the road ahead of the driver. Experiment results show that without visual disruption, all changes were detected very well; yet, these equally perceivable changes were disrupted differently by a brief blank display (150 ms): the detection of location changes was especially reduced. The disruption effects were also bigger for the parked vehicle compared to the moving ones. The findings support the different roles for two visual systems in monitoring the dynamic traffic: the "where", dorsal system, tracks vehicle spatiotemporal information on perceptual level, encoding information in a coarse and transient manner; whereas the "what", ventral system, monitors vehicles' featural information, encoding information more accurately and robustly. Both systems work together contributing to the driver's situation awareness of traffic. Benefits and limitations of using the driving simulation are also discussed. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

Consistency between subjectively and objectively measured hazard perception skills among young male drivers.

PubMed

Ābele, Līva; Haustein, Sonja; Møller, Mette; Martinussen, Laila M

2018-03-01

Young male drivers have lower hazard perception skills (HPS) than older and more experienced drivers and a tendency to overestimate their skills in hazardous situations. Both factors contribute to an over-representation in traffic accidents. Based on a sample of 63 drivers aged 18-24, this study compares the consistency of HPS measured by objective and subjective measures and the link between these measures is the key contribution of the study. Both visible and hidden hazards are included. Objective measures of HPS include responsiveness and eye movements while driving in a driving simulator. Subjective measures of HPS include self-reports derived based on the Hazard Perception Questionnaire (HPQ), Driving Skill Questionnaire (DSQ), and Brief Sensation Seeking Scale (BSSS). Results show that drivers who respond to the hazards on time, as compared to drivers who do not respond, have higher scores on subjective measures of HPS and higher driving skills in the visible but not in the hidden condition. Eye movement analysis confirms the difference and shows that response in time to hazards indicate higher HPS and young drivers are poor at detecting hidden hazards. Drivers with a response in time locate the hazard faster, have more fixations, but dwell less on the hazard. At the same time, those who do not respond have a later first fixation and fewer but longer fixations on the hazard. High sensation seeking drivers respond to visible hazards on time, suggesting that sensation seeking does not affect HPS negatively when the hazard is visible. To enhance the HPS among young drivers, the results of this study suggest that specific hazard perception training is relevant, especially for hazards that require more advanced HPS. Copyright © 2018 Elsevier Ltd. All rights reserved.

Drivers' biased perceptions of speed and safety campaign messages.

PubMed

Walton, D; McKeown, P C

2001-09-01

One hundred and thirteen drivers were surveyed for their perceptions of driving speed to compare self-reported average speed, perceived average-other speed and the actual average speed, in two conditions (50 and 100 kph zones). These contrasts were used to evaluate whether public safety messages concerning speeding effectively reach their target audience. Evidence is presented supporting the hypothesis that drivers who have a biased perception of their own speed relative to others are more likely to ignore advertising campaigns encouraging people not to speed. A method of self-other-actual comparisons detects biased perceptions when the standard method of self-other comparison does not. In particular, drivers exaggerate the perceived speed of others and this fact is masked using traditional methods. The method of manipulation is proposed as a way to evaluate the effect of future advertising campaigns, and a strategy for such campaigns is proposed based on the results of the self-other comparisons.

Classifying Drivers' Cognitive Load Using EEG Signals.

PubMed

Barua, Shaibal; Ahmed, Mobyen Uddin; Begum, Shahina

2017-01-01

A growing traffic safety issue is the effect of cognitive loading activities on traffic safety and driving performance. To monitor drivers' mental state, understanding cognitive load is important since while driving, performing cognitively loading secondary tasks, for example talking on the phone, can affect the performance in the primary task, i.e. driving. Electroencephalography (EEG) is one of the reliable measures of cognitive load that can detect the changes in instantaneous load and effect of cognitively loading secondary task. In this driving simulator study, 1-back task is carried out while the driver performs three different simulated driving scenarios. This paper presents an EEG based approach to classify a drivers' level of cognitive load using Case-Based Reasoning (CBR). The results show that for each individual scenario as well as using data combined from the different scenarios, CBR based system achieved approximately over 70% of classification accuracy.

Incidence of lung cancer among subway drivers in Stockholm.

PubMed

Gustavsson, Per; Bigert, Carolina; Pollán, Marina

2008-07-01

Very high levels of airborne particles have been detected in the subway system in Stockholm. Subway particles are more toxic to DNA in cultured human lung cells than particles from ambient air. This cohort comprised all men in Stockholm County who were gainfully employed in 1970. They were followed for cancer incidence until 1989. Lung cancer cases were identified from the national cancer register. Subway drivers were identified from the census in 1970. The reference cohort comprised all transport and communication workers in Stockholm. There were nine cases of lung cancer among the subway drivers, giving a SIR of 0.82 (95% confidence interval 0.38-1.56). The lung cancer incidence was not increased among the subway drivers. The study gives some evidence against the hypothesis that subway particles would be more potent in inducing lung cancer than particles in ambient air. (c) 2008 Wiley-Liss, Inc.

Detection of driver engagement in secondary tasks from observed naturalistic driving behavior.

PubMed

Ye, Mengqiu; Osman, Osama A; Ishak, Sherif; Hashemi, Bita

2017-09-01

Distracted driving has long been acknowledged as one of the leading causes of death or injury in roadway crashes. The focus of past research has been mainly on the impact of different causes of distraction on driving behavior. However, only a few studies attempted to address how some driving behavior attributes could be linked to the cause of distraction. In essence, this study takes advantage of the rich SHRP 2 Naturalistic Driving Study (NDS) database to develop a model for detecting the likelihood of a driver's involvement in secondary tasks from distinctive attributes of driving behavior. Five performance attributes, namely speed, longitudinal acceleration, lateral acceleration, yaw rate, and throttle position were used to describe the driving behavior. A model was developed for each of three selected secondary tasks: calling, texting, and passenger interaction. The models were developed using a supervised feed-forward Artificial Neural Network (ANN) architecture to account for the effect of inherent nonlinearity in the relationships between driving behavior and secondary tasks. The results show that the developed ANN models were able to detect the drivers' involvement in calling, texting, and passenger interaction with an overall accuracy of 99.5%, 98.1%, and 99.8%, respectively. These results show that the selected driving performance attributes were effective in detecting the associated secondary tasks with driving behavior. The results are very promising and the developed models could potentially be applied in crash investigations to resolve legal disputes in traffic accidents. Copyright © 2017 Elsevier Ltd. All rights reserved.

A multicentre study of vigabarin for drug-resistant epilepsy

PubMed Central

Browne, T. R.; Mattson, R. H.; Penry, J. K.; Smith, D. B.; Treiman, D. M.; Wilder, B. J.; Ben-Menachem, E.; Miketta, R. M.; Sherry, K. M.; Szabo, G. K.

1989-01-01

1 Vigabatrin (GVG) was given in a single-blind fashion to 89 patients with complex partial seizures (CPS) refractory to conventional drugs. 2 The median number of CPS per month decreased from 11.0 to 5.0 after addition of GVG, and 51% of patients had a 50% or greater decrease in CPS frequency (P < 0.001). 3 Side effects (principally drowsiness, ataxia, headache) occurred mainly during the initiation of therapy and decreased during therapy. After 12 weeks on GVG side effects significantly interfered with functioning in only 13% of patients, and the efficacy: toxicity ratio warranted continued administration in 74% of patients. 4 Co-administration of GVG resulted in a mean decrease of 20% in phenytoin serum concentration (P < 0.001). 5 Sixty-six patients having a favourable response to GVG during the single-blind study have been followed for 6-54 (median 33) months on GVG. Only 17 patients have dropped out of long-term follow-up due to break through seizures and/or side effects. No serious systemic or neurological toxicity has been detected. PMID:2667606

Characterization of "Yaa Chud" Medicine on the Thailand-Myanmar border: selecting for drug-resistant malaria and threatening public health.

PubMed

Newton, Paul N; Hampton, Christina Y; Alter-Hall, Krystyn; Teerwarakulpana, Thanongsak; Prakongpan, Sompol; Ruangveerayuth, Ronnatrai; White, Nicholas J; Day, Nicholas P J; Tudino, Mabel B; Mancuso, Natalia; Fernández, Facundo M

2008-11-01

Multidrug-resistant Plasmodium falciparum malaria is a severe public health problem on the Thailand-Myanmar border. Many villagers buy packets of 4-5 mixed medicines ("yaa chud") from shops without medical assessment as their first-line malaria treatment. In 2000-2001 a local researcher purchased 50 yaa chud from 44 shops around Mae Sot, Thailand and Myawaddy, Myanmar (Burma), for his wife who was said to be pregnant with fever and drowsiness. The tablets/capsules were provisionally identified by appearance and active ingredients determined in a subset by using mass and atomic spectrometry. The most frequently detected active ingredients were acetaminophen (22%), chlorpheniramine (13.4%), chloroquine (12.6%), tetracycline/doxycycline (11.4%), and quinine (5.1%). Only seven bags contained potentially curative medicine for malaria. A total of 82% of the bags contained medicines contraindicated in pregnancy. Inappropriate, ineffective antimalarial drugs on the Thailand-Myanmar border are likely to increase malaria morbidity, mortality and health costs and engender the emergence and spread of antimalarial drug resistance.

Globo H expression is associated with driver mutations and PD-L1 expressions in stage I non-small cell lung cancer.

PubMed

Yang, Ching-Yao; Lin, Mong-Wei; Chang, Yih-Leong; Wu, Chen-Tu

2017-12-12

Globo H is a tumor-associated carbohydrate antigen exclusively expressed in cancer cells rather than normal tissue. Globo H has been found on many cancers of epithelial origins, and become an attractive target for cancer vaccine. We aimed to study the expression of Globo H in non-small cell lung cancer (NSCLC) patients, and correlated its expression with common driver mutations, clinical outcomes, and status of immune checkpoint, programmed death-ligand 1 (PD-L1). The study enrolled 228 patients with surgically resected stage I NSCLC, including 139 patients with adenocarcinoma (ADC) and 89 patients with squamous cell carcinoma (SqCC). Using immunohistochemistry, tumors with moderate to strong membranous staining in ⩾ 1% tumor cells per section were scored as positive Globo H expression. Driver mutations including EGFR, KRAS, BRAF were detected by direct sequencing, while ALK, PI3KCA, FGFR1 and PD-L1 expression was detected by immunohistochemical (IHC) staining. Positive Globo H expression was detected in 88 of the 228 (38.6%) patients. These included 51 of 139 (36.7%) patients with ADC and 37 of 89 (41.6%) patients with SqCC. Positive Globo H expression was significantly associated with EGFR mutation and PD-L1 expression in the ADC group, and PI3KCA overexpression in the SqCC group. The survival analysis showed that Globo H expression was not an independent prognostic factor in stage I NSCLC. Globo H expression was correlated with specific driver mutations in ADC and SqCC NSCLC tumors, as well as PD-L1 status. Immunotherapy targeting Globo H may have potential application in lung cancer treatment.

Discovering mutated driver genes through a robust and sparse co-regularized matrix factorization framework with prior information from mRNA expression patterns and interaction network.

PubMed

Xi, Jianing; Wang, Minghui; Li, Ao

2018-06-05

Discovery of mutated driver genes is one of the primary objective for studying tumorigenesis. To discover some relatively low frequently mutated driver genes from somatic mutation data, many existing methods incorporate interaction network as prior information. However, the prior information of mRNA expression patterns are not exploited by these existing network-based methods, which is also proven to be highly informative of cancer progressions. To incorporate prior information from both interaction network and mRNA expressions, we propose a robust and sparse co-regularized nonnegative matrix factorization to discover driver genes from mutation data. Furthermore, our framework also conducts Frobenius norm regularization to overcome overfitting issue. Sparsity-inducing penalty is employed to obtain sparse scores in gene representations, of which the top scored genes are selected as driver candidates. Evaluation experiments by known benchmarking genes indicate that the performance of our method benefits from the two type of prior information. Our method also outperforms the existing network-based methods, and detect some driver genes that are not predicted by the competing methods. In summary, our proposed method can improve the performance of driver gene discovery by effectively incorporating prior information from interaction network and mRNA expression patterns into a robust and sparse co-regularized matrix factorization framework.

Factors associated with civilian drivers involved in crashes with emergency vehicles.

PubMed

Drucker, Christopher; Gerberich, Susan G; Manser, Michael P; Alexander, Bruce H; Church, Timothy R; Ryan, Andrew D; Becic, Ensar

2013-06-01

Motor vehicle crashes involving civilian and emergency vehicles (EVs) have been a known problem that contributes to fatal and nonfatal injuries; however, characteristics associated with civilian drivers have not been examined adequately. This study used data from The National Highway Traffic Safety Administration's Fatality Analysis Reporting System and the National Automotive Sampling System General Estimates System to identify driver, roadway, environmental, and crash factors, and consequences for civilian drivers involved in fatal and nonfatal crashes with in-use and in-transport EVs. In general, drivers involved in emergency-civilian crashes (ECCs) were more often driving: straight through intersections (vs. same direction) of four-points or more (vs. not at intersection); where traffic signals were present (vs. no traffic control device); and at night (vs. midday). For nonfatal ECCs, drivers were more often driving: distracted (vs. not distracted); with vision obstructed by external objects (vs. no obstruction); on dark but lighted roads (vs. daylight); and in opposite directions (vs. same directions) of the EVs. Consequences included increased risk of injury (vs. no injury) and receiving traffic violations (vs. no violation). Fatal ECCs were associated with driving on urban roads (vs. rural), although these types of crashes were less likely to occur on dark roads (vs. daylight). The findings of this study suggest drivers may have difficulties in visually detecting EVs in different environments. Copyright © 2013 Elsevier Ltd. All rights reserved.

Estimation of automobile-driver describing function from highway tests using the double steering wheel

NASA Technical Reports Server (NTRS)

Delp, P.; Crossman, E. R. F. W.; Szostak, H.

1972-01-01

The automobile-driver describing function for lateral position control was estimated for three subjects from frequency response analysis of straight road test results. The measurement procedure employed an instrumented full size sedan with known steering response characteristics, and equipped with a lateral lane position measuring device based on video detection of white stripe lane markings. Forcing functions were inserted through a servo driven double steering wheel coupling the driver to the steering system proper. Random appearing, Gaussian, and transient time functions were used. The quasi-linear models fitted to the random appearing input frequency response characterized the driver as compensating for lateral position error in a proportional, derivative, and integral manner. Similar parameters were fitted to the Gabor transformed frequency response of the driver to transient functions. A fourth term corresponding to response to lateral acceleration was determined by matching the time response histories of the model to the experimental results. The time histories show evidence of pulse-like nonlinear behavior during extended response to step transients which appear as high frequency remnant power.

Atrial fibrillation driver mechanisms: Insight from the isolated human heart.

PubMed

Csepe, Thomas A; Hansen, Brian J; Fedorov, Vadim V

2017-01-01

Although there have been great technological advances in the treatment of atrial fibrillation (AF), current therapies remain limited due to a narrow understanding of AF mechanisms in the human heart. This review will highlight our recent studies on explanted human hearts where we developed and employed a novel functional-structural mapping approach by integrating high-resolution simultaneous endo-epicardial and panoramic optical mapping with 3D gadolinium-enhanced MRI to define the spatiotemporal characteristics of AF drivers and their structural substrates. The results allow us to postulate that the primary mechanism of AF maintenance in human hearts is a limited number of localized intramural microanatomic reentrant AF drivers anchored to heart-specific 3D fibrotically insulated myobundle tracks, which may remain hidden to clinical single-surface electrode mapping. We suggest that ex vivo human heart studies, by using an integrated 3D functional and structural mapping approach, will help to reveal defining features of AF drivers as well as validate and improve clinical approaches to detect and target these AF drivers in patients with cardiac diseases. Copyright © 2016 Elsevier Inc. All rights reserved.

Impacts of Fog Characteristics, Forward Illumination, and Warning Beacon Intensity Distribution on Roadway Hazard Visibility

PubMed Central

2016-01-01

Warning beacons are critical for the safety of transportation, construction, and utility workers. These devices need to produce sufficient luminous intensity to be visible without creating glare to drivers. Published standards for the photometric performance of warning beacons do not address their performance in conditions of reduced visibility such as fog. Under such conditions light emitted in directions other than toward approaching drivers can create scattered light that makes workers and other hazards less visible. Simulations of visibility of hazards under varying conditions of fog density, forward vehicle lighting, warning beacon luminous intensity, and intensity distribution were performed to assess their impacts on visual performance by drivers. Each of these factors can influence the ability of drivers to detect and identify workers and hazards along the roadway in work zones. Based on the results, it would be reasonable to specify maximum limits on the luminous intensity of warning beacons in directions that are unlikely to be seen by drivers along the roadway, limits which are not included in published performance specifications. PMID:27314058

Optical/digital identification/verification system based on digital watermarking technology

NASA Astrophysics Data System (ADS)

Herrigel, Alexander; Voloshynovskiy, Sviatoslav V.; Hrytskiv, Zenon D.

2000-06-01

This paper presents a new approach for the secure integrity verification of driver licenses, passports or other analogue identification documents. The system embeds (detects) the reference number of the identification document with the DCT watermark technology in (from) the owner photo of the identification document holder. During verification the reference number is extracted and compared with the reference number printed in the identification document. The approach combines optical and digital image processing techniques. The detection system must be able to scan an analogue driver license or passport, convert the image of this document into a digital representation and then apply the watermark verification algorithm to check the payload of the embedded watermark. If the payload of the watermark is identical with the printed visual reference number of the issuer, the verification was successful and the passport or driver license has not been modified. This approach constitutes a new class of application for the watermark technology, which was originally targeted for the copyright protection of digital multimedia data. The presented approach substantially increases the security of the analogue identification documents applied in many European countries.

Design of a steering stabilizer based on CAN bus

NASA Astrophysics Data System (ADS)

Zhan, Zhaomin; Yan, Yibin

2018-04-01

This design realizes a posture correction device of griping steering wheel based on CAN bus, which is embedded in the steering wheel of vehicles. The system aims to detect the drivers' abnormal griping postures and provides drivers with classification alerts, by combining the recorded griping postures data and the vehicle speed data that are obtained via the CAN bus. The warning information are automatically stored and retained in the device for 12 months. To enhance the alerting effect, the count of this warning message for both the latest month and the last 12 months are displayed on the dashboard panel. In addition to prevent itself from being blocked and self-detect any faults in advance, the appliance also provide a self-test function, which will communicate with the integrated instrument system in vehicle and do simulation test right after the vehicle power on. This appliance can help to urge and ensure drivers to operate the steering wheel correctly, effectively, and timely; prevent some typical incorrect behaviors which commonly happen along with the change of griping postures, such as the using cellphone, and ultimately, reduce the incidence of traffic accidents.

Prediction of Driver’s Intention of Lane Change by Augmenting Sensor Information Using Machine Learning Techniques

PubMed Central

Kim, Il-Hwan; Bong, Jae-Hwan; Park, Jooyoung; Park, Shinsuk

2017-01-01

Driver assistance systems have become a major safety feature of modern passenger vehicles. The advanced driver assistance system (ADAS) is one of the active safety systems to improve the vehicle control performance and, thus, the safety of the driver and the passengers. To use the ADAS for lane change control, rapid and correct detection of the driver’s intention is essential. This study proposes a novel preprocessing algorithm for the ADAS to improve the accuracy in classifying the driver’s intention for lane change by augmenting basic measurements from conventional on-board sensors. The information on the vehicle states and the road surface condition is augmented by using an artificial neural network (ANN) models, and the augmented information is fed to a support vector machine (SVM) to detect the driver’s intention with high accuracy. The feasibility of the developed algorithm was tested through driving simulator experiments. The results show that the classification accuracy for the driver’s intention can be improved by providing an SVM model with sufficient driving information augmented by using ANN models of vehicle dynamics. PMID:28604582

Late detection of hazards in traffic: A matter of response bias?

PubMed

Egea-Caparrós, Damián-Amaro; García-Sevilla, Julia; Pedraja, María-José; Romero-Medina, Agustín; Marco-Cramer, María; Pineda-Egea, Laura

2016-09-01

In this study, results from two different hazard perception tests are presented: the first one is a classic hazard-perception test in which participants must respond - while watching real traffic video scenes - by pressing the space bar in a keyboard when they think there is a collision risk between the camera car and the vehicle ahead. In the second task we use fragments of the same scenes but in this case they are adapted to a signal detection task - a 'yes'/'no' task. Here, participants - most of them, University students - must respond, when the fragment of the video scene ends, whether they think the collision risk had started yet or not. While in the first task we have a latency measure (the time necessary for the driver to respond to a hazard), in the second task we obtain two separate measures of sensitivity and criterion. Sensitivity is the driver's ability to discriminate in a proper way the presence vs. absence of the signal (hazard) while the criterion is the response bias a driver sets to consider that there is a hazard or not. His/her criterion could be more conservative - the participant demands many cues to respond that the signal is present, neutral or even liberal - the participant will respond that the signal is present with very few cues. The aim of the study is to find out if our latency measure is associated with a different sensitivity and/or criterion. The results of the present study show that drivers who had greater latencies and drivers who had very low latencies yield a very similar sensitivity mean value. Nevertheless, there was a significant difference between these two groups of drivers in criterion: those drivers who had greater latencies in the first task were also more conservative in the second task. That is, the latter responded less frequently that there was danger in the sequences. We interpret that greater latencies in our first hazard perception test could be due to a stricter or more conservative criterion, rather than a low sensitivity to perceptual information for collision risk. Drivers with a more conservative criterion need more evidences of danger, thus taking longer to respond. Copyright © 2016 Elsevier Ltd. All rights reserved.

Underwater Simultaneous EMI and Magnetometer System (USEMS)

DTIC Science & Technology

2011-02-01

advantages over other marine metal detectors . The first is that, because the sensors are affixed via a rigid boom instead of towed with a cable...Island free of metallic clutter, emplaced a test plot with 14 pipes ranging from 1.5 to 4 inches in diameter, measured the locations of items in it with... metallic contamination. 2.3 REGULATORY DRIVERS The primary driver is the continued need to develop tools to detect underwater MEC. The documented use

Comparison of the effects of two legal blood alcohol limits: the presence of alcohol in traffic accidents according to category of driver in Izmir, Turkey.

PubMed

Karakus, Akan; İdiz, Nuri; Dalgiç, Mustafa; Uluçay, Tarik; Sincar, Yasemin

2015-01-01

Under existing Turkish road traffic law, there are 2 different blood alcohol concentration (BAC) limits allowed for drivers in 2013: zero blood alcohol and ≤0.50 g/L. All public transport, taxi, commercial, and official vehicle drivers must maintain a zero blood alcohol concentration while driving. Private vehicle drivers must maintain a BAC of 0.50 g/L or lower. The aim of the recent study was to evaluate the effect of these 2 legal blood alcohol limits on nonfatal traffic accidents that occurred due to the driver being under the influence of alcohol. This retrospective study was performed to evaluate the blood alcohol concentration of 224 drivers in nonfatal road accidents between June 2010 and July 2011 using headspace gas chromatography at the Izmir Forensic Medicine Group Presidency, Turkey. All cases evaluated by the toxicology department were entered into a database. We used descriptive statistics, χ(2) test, and independent sampling test to analyze the data. The total number of drivers involved in nonfatal traffic accidents was 224; 191 were private vehicle drivers and 33 were public transport, taxi, commercial, and official vehicle drivers. In the present study, alcohol was detected in the blood of about 27.2% (n = 61) of the 224 drivers. Sixty (31.4%) private vehicle drivers involved in nonfatal traffic accidents tested positive for alcohol. BAC values were also above the legal limit (0.50 g/L) in 27.7% (n = 53) of private vehicle drivers. However, the BAC was above the legal limit in only 3% (n = 1) of public transport, commercial, and official vehicle drivers involved in nonfatal traffic accidents. These results showed that private vehicle drivers subject to a BAC limit of ≤0.50 g/L were significantly associated with an increased risk of nonfatal accident involvement than drivers subject to a zero BAC limit (odds ratio [OR] = 12.29, 95% confidence interval [CI], 1.64-92.22; Fisher's exact test, P <.001). Mean BAC in private vehicle drivers subject to a 0.50 g/L level (52.60 mg/dl ± 94.84) was significantly higher than that of drivers subject to a zero alcohol level (10.76 mg/dl ± 61.80; t = 2.44, P <.001). In light of our results, lowering the BAC limit for private vehicle drivers may reduce the level of driving under the influence of alcohol. A change in the law will decrease the rates of alcohol-related road accidents in Turkey.

Global change and terrestrial plant community dynamics

DOE PAGES

Franklin, Janet; Serra-Diaz, Josep M.; Syphard, Alexandra D.; ...

2016-02-29

Anthropogenic drivers of global change include rising atmospheric concentrations of carbon dioxide and other greenhouse gasses and resulting changes in the climate, as well as nitrogen deposition, biotic invasions, altered disturbance regimes, and land-use change. Predicting the effects of global change on terrestrial plant communities is crucial because of the ecosystem services vegetation provides, from climate regulation to forest products. In this article, we present a framework for detecting vegetation changes and attributing them to global change drivers that incorporates multiple lines of evidence from spatially extensive monitoring networks, distributed experiments, remotely sensed data, and historical records. Based on amore » literature review, we summarize observed changes and then describe modeling tools that can forecast the impacts of multiple drivers on plant communities in an era of rapid change. Observed responses to changes in temperature, water, nutrients, land use, and disturbance show strong sensitivity of ecosystem productivity and plant population dynamics to water balance and long-lasting effects of disturbance on plant community dynamics. Persistent effects of land-use change and human-altered fire regimes on vegetation can overshadow or interact with climate change impacts. Models forecasting plant community responses to global change incorporate shifting ecological niches, population dynamics, species interactions, spatially explicit disturbance, ecosystem processes, and plant functional responses. Lastly, monitoring, experiments, and models evaluating multiple change drivers are needed to detect and predict vegetation changes in response to 21st century global change.« less

Global change and terrestrial plant community dynamics

PubMed Central

Franklin, Janet; Serra-Diaz, Josep M.; Syphard, Alexandra D.; Regan, Helen M.

2016-01-01

Anthropogenic drivers of global change include rising atmospheric concentrations of carbon dioxide and other greenhouse gasses and resulting changes in the climate, as well as nitrogen deposition, biotic invasions, altered disturbance regimes, and land-use change. Predicting the effects of global change on terrestrial plant communities is crucial because of the ecosystem services vegetation provides, from climate regulation to forest products. In this paper, we present a framework for detecting vegetation changes and attributing them to global change drivers that incorporates multiple lines of evidence from spatially extensive monitoring networks, distributed experiments, remotely sensed data, and historical records. Based on a literature review, we summarize observed changes and then describe modeling tools that can forecast the impacts of multiple drivers on plant communities in an era of rapid change. Observed responses to changes in temperature, water, nutrients, land use, and disturbance show strong sensitivity of ecosystem productivity and plant population dynamics to water balance and long-lasting effects of disturbance on plant community dynamics. Persistent effects of land-use change and human-altered fire regimes on vegetation can overshadow or interact with climate change impacts. Models forecasting plant community responses to global change incorporate shifting ecological niches, population dynamics, species interactions, spatially explicit disturbance, ecosystem processes, and plant functional responses. Monitoring, experiments, and models evaluating multiple change drivers are needed to detect and predict vegetation changes in response to 21st century global change. PMID:26929338

Predicting Visual Distraction Using Driving Performance Data

PubMed Central

Kircher, Katja; Ahlstrom, Christer

2010-01-01

Behavioral variables are often used as performance indicators (PIs) of visual or internal distraction induced by secondary tasks. The objective of this study is to investigate whether visual distraction can be predicted by driving performance PIs in a naturalistic setting. Visual distraction is here defined by a gaze based real-time distraction detection algorithm called AttenD. Seven drivers used an instrumented vehicle for one month each in a small scale field operational test. For each of the visual distraction events detected by AttenD, seven PIs such as steering wheel reversal rate and throttle hold were calculated. Corresponding data were also calculated for time periods during which the drivers were classified as attentive. For each PI, means between distracted and attentive states were calculated using t-tests for different time-window sizes (2 – 40 s), and the window width with the smallest resulting p-value was selected as optimal. Based on the optimized PIs, logistic regression was used to predict whether the drivers were attentive or distracted. The logistic regression resulted in predictions which were 76 % correct (sensitivity = 77 % and specificity = 76 %). The conclusion is that there is a relationship between behavioral variables and visual distraction, but the relationship is not strong enough to accurately predict visual driver distraction. Instead, behavioral PIs are probably best suited as complementary to eye tracking based algorithms in order to make them more accurate and robust. PMID:21050615

DOE Office of Scientific and Technical Information (OSTI.GOV)

Franklin, Janet; Serra-Diaz, Josep M.; Syphard, Alexandra D.

Anthropogenic drivers of global change include rising atmospheric concentrations of carbon dioxide and other greenhouse gasses and resulting changes in the climate, as well as nitrogen deposition, biotic invasions, altered disturbance regimes, and land-use change. Predicting the effects of global change on terrestrial plant communities is crucial because of the ecosystem services vegetation provides, from climate regulation to forest products. In this article, we present a framework for detecting vegetation changes and attributing them to global change drivers that incorporates multiple lines of evidence from spatially extensive monitoring networks, distributed experiments, remotely sensed data, and historical records. Based on amore » literature review, we summarize observed changes and then describe modeling tools that can forecast the impacts of multiple drivers on plant communities in an era of rapid change. Observed responses to changes in temperature, water, nutrients, land use, and disturbance show strong sensitivity of ecosystem productivity and plant population dynamics to water balance and long-lasting effects of disturbance on plant community dynamics. Persistent effects of land-use change and human-altered fire regimes on vegetation can overshadow or interact with climate change impacts. Models forecasting plant community responses to global change incorporate shifting ecological niches, population dynamics, species interactions, spatially explicit disturbance, ecosystem processes, and plant functional responses. Lastly, monitoring, experiments, and models evaluating multiple change drivers are needed to detect and predict vegetation changes in response to 21st century global change.« less

Quantifying ecological thresholds from response surfaces

Treesearch

Heather E. Lintz; Bruce McCune; Andrew N. Gray; Katherine A. McCulloh

2011-01-01

Ecological thresholds are abrupt changes of ecological state. While an ecological threshold is a widely accepted concept, most empirical methods detect them in time or across geographic space. Although useful, these approaches do not quantify the direct drivers of threshold response. Causal understanding of thresholds detected empirically requires their investigation...

Lane change warning threshold based on driver perception characteristics.

PubMed

Wang, Chang; Sun, Qinyu; Fu, Rui; Li, Zhen; Zhang, Qiong

2018-08-01

Lane Change Warning system (LCW) is exploited to alleviate driver workload and improve the safety performance of lane changes. Depending on the secure threshold, the lane change warning system could transmit caution to drivers. Although the system possesses substantial benefits, it may perturb the conventional operating of the driver and affect driver judgment if the warning threshold does not conform to the driver perception of safety. Therefore, it is essential to establish an appropriate warning threshold to enhance the accuracy rate and acceptability of the lane change warning system. This research aims to identify the threshold that conforms to the driver perception of the ability to safely change lanes with a rear vehicle fast approaching. We propose a theoretical warning model of lane change based on a safe minimum distance and deceleration of the rear vehicle. For the purpose of acquiring the different safety levels of lane changes, 30 licensed drivers are recruited and we obtain the extreme moments represented by driver perception characteristics from a Front Extremity Test and a Rear Extremity Test implemented on the freeway. The required deceleration of the rear vehicle corresponding to the extreme time is calculated according to the proposed model. In light of discrepancies in the deceleration in these extremity experiments, we determine two levels of a hierarchical warning system. The purpose of the primary warning is to remind drivers of the existence of potentially dangerous vehicles and the second warning is used to warn the driver to stop changing lanes immediately. We use the signal detection theory to analyze the data. Ultimately, we confirm that the first deceleration threshold is 1.5 m/s 2 and the second deceleration threshold is 2.7 m/s 2 . The findings provide the basis for the algorithm design of LCW and enhance the acceptability of the intelligent system. Copyright © 2018 Elsevier Ltd. All rights reserved.

Mileage, car ownership, experience of punishment avoidance, and the risky driving of young drivers.

PubMed

Scott-Parker, B; Watson, B; King, M J; Hyde, M K

2011-12-01

Young drivers are at greatest risk of injury or death from a car crash in the first 6 months of independent driving. In Queensland, the graduated driver licensing (GDL) program was extensively modified in July 2007 in order to reduce this risk. Increased mileage and car ownership have been found to play a role in risky driving, offenses, and crashes; however, GDL programs typically do not consider these variables. In addition, young novice drivers' experiences of punishment avoidance have not previously been examined. This article explores the mileage (duration and distance), car ownership, and punishment avoidance behaviors of young newly licensed intermediate (provisional) drivers and their relationship to risky driving, crashes, and offenses. Drivers (n = 1032) aged 17 to 19 years recruited from across Queensland for longitudinal research completed survey 1 exploring prelicense and learner experiences and sociodemographic characteristics. survey 2 explored the same variables with a subset of these drivers (n = 341) after they had completed their first 6 months of independent driving. Most young drivers in survey 2 reported owning a vehicle and paying attention to police presence. Drivers who had their own cars reported significantly greater mileage and more risky driving. Novices who drove more kilometers, spent more hours each week driving, or avoided actual and anticipated police presence were more likely to report risky driving. These drivers were also more likely to report being detected by police for a driving-related offense. The media, parents, friends, and other drivers play a pivotal role in informing novices of on-road police enforcement operations. GDL programs should incorporate education for the parent and novice driver regarding the increased risks associated with greater driving, particularly when the novice driver owns a vehicle. Parents should be encouraged to delay exclusive access to a vehicle. Parents should also consider whether their young novices will deliberately avoid police if they are aware of their location. This may reinforce not only the risky behavior but also young novices' beliefs that their parents condone this behavior.

Developing an EEG-based on-line closed-loop lapse detection and mitigation system

PubMed Central

Wang, Yu-Te; Huang, Kuan-Chih; Wei, Chun-Shu; Huang, Teng-Yi; Ko, Li-Wei; Lin, Chin-Teng; Cheng, Chung-Kuan; Jung, Tzyy-Ping

2014-01-01

In America, 60% of adults reported that they have driven a motor vehicle while feeling drowsy, and at least 15–20% of fatal car accidents are fatigue-related. This study translates previous laboratory-oriented neurophysiological research to design, develop, and test an On-line Closed-loop Lapse Detection and Mitigation (OCLDM) System featuring a mobile wireless dry-sensor EEG headgear and a cell-phone based real-time EEG processing platform. Eleven subjects participated in an event-related lane-keeping task, in which they were instructed to manipulate a randomly deviated, fixed-speed cruising car on a 4-lane highway. This was simulated in a 1st person view with an 8-screen and 8-projector immersive virtual-reality environment. When the subjects experienced lapses or failed to respond to events during the experiment, auditory warning was delivered to rectify the performance decrements. However, the arousing auditory signals were not always effective. The EEG spectra exhibited statistically significant differences between effective and ineffective arousing signals, suggesting that EEG spectra could be used as a countermeasure of the efficacy of arousing signals. In this on-line pilot study, the proposed OCLDM System was able to continuously detect EEG signatures of fatigue, deliver arousing warning to subjects suffering momentary cognitive lapses, and assess the efficacy of the warning in near real-time to rectify cognitive lapses. The on-line testing results of the OCLDM System validated the efficacy of the arousing signals in improving subjects' response times to the subsequent lane-departure events. This study may lead to a practical on-line lapse detection and mitigation system in real-world environments. PMID:25352773

Development of a Targeted Next-Generation Sequencing Assay to Detect Diagnostically Relevant Mutations of JAK2, CALR, and MPL in Myeloproliferative Neoplasms.

PubMed

Frawley, Thomas; O'Brien, Cathal P; Conneally, Eibhlin; Vandenberghe, Elisabeth; Percy, Melanie; Langabeer, Stephen E; Haslam, Karl

2018-02-01

The classical Philadelphia chromosome-negative myeloproliferative neoplasms (MPNs), consisting of polycythemia vera, essential thrombocythemia, and primary myelofibrosis, are a heterogeneous group of neoplasms that harbor driver mutations in the JAK2, CALR, and MPL genes. The detection of mutations in these genes has been incorporated into the recent World Health Organization (WHO) diagnostic criteria for MPN. Given a pressing clinical need to screen for mutations in these genes in a routine diagnostic setting, a targeted next-generation sequencing (NGS) assay for the detection of MPN-associated mutations located in JAK2 exon 14, JAK2 exon 12, CALR exon 9, and MPL exon 10 was developed to provide a single platform alternative to reflexive, stepwise diagnostic algorithms. Polymerase chain reaction (PCR) primers were designed to target mutation hotspots in JAK2 exon 14, JAK2 exon 12, MPL exon 10, and CALR exon 9. Multiplexed PCR conditions were optimized by using qualitative PCR followed by NGS. Diagnostic genomic DNA from 35 MPN patients, known to harbor driver mutations in one of the target genes, was used to validate the assay. One hundred percent concordance was observed between the previously-identified mutations and those detected by NGS, with no false positives, nor any known mutations missed (specificity = 100%, CI = 0.96, sensitivity = 100%, CI = 0.89). Improved resolution of mutation sequences was also revealed by NGS analysis. Detection of diagnostically relevant driver mutations of MPN is enhanced by employing a targeted multiplex NGS approach. This assay presents a robust solution to classical MPN mutation screening, providing an alternative to time-consuming sequential analyses.

Preventing road injuries in children by applying feedback devices.

PubMed

Spiegel, Rainer; Farahmand, Parvis; Da Silva, Fábio Anciães; Claassen, Jens; Kalla, Roger

2012-01-01

The objective of this article is to determine how to prevent road injuries in schoolchildren by reducing the prevalence of speeding. On a busy road in the neighborhood of a preschool and two secondary schools in Oberhaching (greater Munich, Germany), a board was mounted next to the road (visible to the drivers as well as the pedestrians). The board consisted of a picture of a smiling child. Underneath the picture, an LED display read "Thank you!" in green blinking letters when the speed limit was adhered to and "Slowly!" in red blinking letters when speeding was detected. The main outcome assessment was the number of drivers adhering to the speed limit in the experimental condition (i.e., facing the device) compared to the number in the control condition (on the same road within the same time period but traveling in the opposite direction; i.e., drivers not facing the device). In the control condition 27.6 percent (230) of drivers adhered to the speed limit compared to 41.1 percent (427) of drivers in the experimental condition, χ(2) = 36.1, P < .0001. Only 12 drivers exceeded the speed limit by more than 20 km per hour in the experimental condition, whereas 34 drivers did so in the control condition, χ(2) = 9.6, P < .01. The display is associated with a significantly lower percentage of speeding drivers but does not seem to be sufficient, because the majority of drivers still did not observe the speed limit in the presence of the display. Additional factors on how speed reduction can be achieved will be discussed in the light of future applications and possible modifications of the device.

The effects of momentary visual disruption on hazard anticipation and awareness in driving.

PubMed

Borowsky, Avinoam; Horrey, William J; Liang, Yulan; Garabet, Angela; Simmons, Lucinda; Fisher, Donald L

2015-01-01

Driver distraction is known to increase crash risk, especially when a driver glances inside the vehicle for especially long periods of time. Though it is clear that such glances increase the risk for the driver when looking inside the vehicle, it is less clear how these glances disrupt the ongoing processing of information outside the vehicle once the driver's eyes return to the road. The present study was aimed at exploring the effect of in-vehicle glances on the top-down processes that guide the detection and monitoring of hazards on the forward roadway. Using a driving simulator, 12 participants were monitored with an eye-tracking system while they navigated various hazardous scenarios. Six participants were momentarily interrupted by a visual secondary task (simulating a glance inside the vehicle) prior to the occurrence of a potential hazard and 6 were not. Eye movement analyses showed that interrupted drivers often failed to continue scanning for a potential hazard when their forward view reappeared, especially when the potential threat could not easily be localized. Additionally, drivers' self-appraisal of workload and performance of the driving task indicated that, contrary to what one might expect, drivers in the interruption condition reported workload levels lower than and performance equal to drivers in the no interruption condition. Drivers who are momentarily disrupted even for a brief duration are at risk of missing important information when they return their gaze to the forward roadway. In addition, because they are not aware of missing this information they are likely to continue engaging in in-vehicle tasks even though they are demonstrably unsafe. The implications for safety, calibration, and targeted remediation are discussed.

Multi-vehicle detection with identity awareness using cascade Adaboost and Adaptive Kalman filter for driver assistant system

PubMed Central

Wang, Baofeng; Qi, Zhiquan; Chen, Sizhong; Liu, Zhaodu; Ma, Guocheng

2017-01-01

Vision-based vehicle detection is an important issue for advanced driver assistance systems. In this paper, we presented an improved multi-vehicle detection and tracking method using cascade Adaboost and Adaptive Kalman filter(AKF) with target identity awareness. A cascade Adaboost classifier using Haar-like features was built for vehicle detection, followed by a more comprehensive verification process which could refine the vehicle hypothesis in terms of both location and dimension. In vehicle tracking, each vehicle was tracked with independent identity by an Adaptive Kalman filter in collaboration with a data association approach. The AKF adaptively adjusted the measurement and process noise covariance through on-line stochastic modelling to compensate the dynamics changes. The data association correctly assigned different detections with tracks using global nearest neighbour(GNN) algorithm while considering the local validation. During tracking, a temporal context based track management was proposed to decide whether to initiate, maintain or terminate the tracks of different objects, thus suppressing the sparse false alarms and compensating the temporary detection failures. Finally, the proposed method was tested on various challenging real roads, and the experimental results showed that the vehicle detection performance was greatly improved with higher accuracy and robustness. PMID:28296902

Characteristics of On-Road Driving by Persons with Central Vision Loss: Learning to Drive with a Bioptic Telescope

PubMed Central

Wood, Joanne M.; Elgin, Jennifer; McGwin, Gerald; Owsley, Cynthia

2016-01-01

There is limited research on the driving performance and safety of bioptic drivers and even less regarding the driving skills that are most challenging for those learning to drive with bioptic telescopes. This research consisted of case studies of five trainee bioptic drivers whose driving skills were compared with those of a group of licensed bioptic drivers (n=23) while they drove along city, suburban, and controlled-access highways in an instrumented dual-brake vehicle. A certified driver rehabilitation specialist was positioned in the front passenger seat to monitor safety and two backseat evaluators independently rated driving using a standardized scoring system. Other aspects of performance were assessed through vehicle instrumentation and video recordings. Results demonstrate that while sign recognition, lane keeping, steering steadiness, gap judgments and speed choices were significantly worse in trainees, some driving behaviors and skills, including pedestrian detection and traffic light recognition were not significantly different to those of the licensed drivers. These data provide useful insights into the skill challenges encountered by a small sample of trainee bioptic drivers which, while not generalizable because of the small sample size, provide valuable insights beyond that of previous studies and can be used as a basis to guide training strategies. PMID:26480232

Characteristics of on-road driving by persons with central vision loss: Learning to drive with a bioptic telescope.

PubMed

Wood, Joanne M; Elgin, Jennifer; McGwin, Gerald; Owsley, Cynthia

2016-01-01

There is limited research on the driving performance and safety of bioptic drivers and even less regarding the driving skills that are most challenging for those learning to drive with bioptic telescopes. This research consisted of case studies of five trainee bioptic drivers whose driving skills were compared with those of a group of licensed bioptic drivers (n = 23) while they drove along city, suburban, and controlled-access highways in an instrumented dual-brake vehicle. A certified driver rehabilitation specialist was positioned in the front passenger seat to monitor safety and two backseat evaluators independently rated driving using a standardized scoring system. Other aspects of performance were assessed through vehicle instrumentation and video recordings. Results demonstrate that while sign recognition, lane keeping, steering steadiness, gap judgments, and speed choices were significantly worse in trainees, some driving behaviors and skills, including pedestrian detection and traffic light recognition were not significantly different from those of the licensed drivers. These data provide useful insights into the skill challenges encountered by a small sample of trainee bioptic drivers which, while not generalizable because of the small sample size, provide valuable insights beyond that of previous studies and can be used as a basis to guide training strategies.

State Medical Marijuana Laws and the Prevalence of Opioids Detected Among Fatally Injured Drivers

PubMed Central

Santaella-Tenorio, Julian; Mauro, Christine; Wrobel, Julia; Cerdà, Magdalena; Keyes, Katherine M.; Hasin, Deborah; Martins, Silvia S.; Li, Guohua

2016-01-01

Objectives. To assess the association between medical marijuana laws (MMLs) and the odds of a positive opioid test, an indicator for prior use. Methods. We analyzed 1999–2013 Fatality Analysis Reporting System (FARS) data from 18 states that tested for alcohol and other drugs in at least 80% of drivers who died within 1 hour of crashing (n = 68 394). Within-state and between-state comparisons assessed opioid positivity among drivers crashing in states with an operational MML (i.e., allowances for home cultivation or active dispensaries) versus drivers crashing in states before a future MML was operational. Results. State-specific estimates indicated a reduction in opioid positivity for most states after implementation of an operational MML, although none of these estimates were significant. When we combined states, we observed no significant overall association (odds ratio [OR] = 0.79; 95% confidence interval [CI] = 0.61, 1.03). However, age-stratified analyses indicated a significant reduction in opioid positivity for drivers aged 21 to 40 years (OR = 0.50; 95% CI = 0.37, 0.67; interaction P < .001). Conclusions. Operational MMLs are associated with reductions in opioid positivity among 21- to 40-year-old fatally injured drivers and may reduce opioid use and overdose. PMID:27631755

Cancer heterogeneity: converting a limitation into a source of biologic information.

PubMed

Rübben, Albert; Araujo, Arturo

2017-09-08

Analysis of spatial and temporal genetic heterogeneity in human cancers has revealed that somatic cancer evolution in most cancers is not a simple linear process composed of a few sequential steps of mutation acquisitions and clonal expansions. Parallel evolution has been observed in many early human cancers resulting in genetic heterogeneity as well as multilineage progression. Moreover, aneuploidy as well as structural chromosomal aberrations seems to be acquired in a non-linear, punctuated mode where most aberrations occur at early stages of somatic cancer evolution. At later stages, the cancer genomes seem to get stabilized and acquire only few additional rearrangements. While parallel evolution suggests positive selection of driver mutations at early stages of somatic cancer evolution, stabilization of structural aberrations at later stages suggests that negative selection takes effect when cancer cells progressively lose their tolerance towards additional mutation acquisition. Mixing of genetically heterogeneous subclones in cancer samples reduces sensitivity of mutation detection. Moreover, driver mutations present only in a fraction of cancer cells are more likely to be mistaken for passenger mutations. Therefore, genetic heterogeneity may be considered a limitation negatively affecting detection sensitivity of driver mutations. On the other hand, identification of subclones and subclone lineages in human cancers may lead to a more profound understanding of the selective forces which shape somatic cancer evolution in human cancers. Identification of parallel evolution by analyzing spatial heterogeneity may hint to driver mutations which might represent additional therapeutic targets besides driver mutations present in a monoclonal state. Likewise, stabilization of cancer genomes which can be identified by analyzing temporal genetic heterogeneity might hint to genes and pathways which have become essential for survival of cancer cell lineages at later stages of cancer evolution. These genes and pathways might also constitute patient specific therapeutic targets.

Comparison of algorithms for the detection of cancer-drivers at sub-gene resolution

PubMed Central

Porta-Pardo, Eduard; Kamburov, Atanas; Tamborero, David; Pons, Tirso; Grases, Daniela; Valencia, Alfonso; Lopez-Bigas, Nuria; Getz, Gad; Godzik, Adam

2018-01-01

Understanding genetic events that lead to cancer initiation and progression remains one of the biggest challenges in cancer biology. Traditionally most algorithms for cancer driver identification look for genes that have more mutations than expected from the average background mutation rate. However, there is now a wide variety of methods that look for non-random distribution of mutations within proteins as a signal they have a driving role in cancer. Here we classify and review the progress of such sub-gene resolution algorithms, compare their findings on four distinct cancer datasets from The Cancer Genome Atlas and discuss how predictions from these algorithms can be interpreted in the emerging paradigms that challenge the simple dichotomy between driver and passenger genes. PMID:28714987

Sex Chromosome Drive

PubMed Central

Helleu, Quentin; Gérard, Pierre R.; Montchamp-Moreau, Catherine

2015-01-01

Sex chromosome drivers are selfish elements that subvert Mendel's first law of segregation and therefore are overrepresented among the products of meiosis. The sex-biased progeny produced then fuels an extended genetic conflict between the driver and the rest of the genome. Many examples of sex chromosome drive are known, but the occurrence of this phenomenon is probably largely underestimated because of the difficulty to detect it. Remarkably, nearly all sex chromosome drivers are found in two clades, Rodentia and Diptera. Although very little is known about the molecular and cellular mechanisms of drive, epigenetic processes such as chromatin regulation could be involved in many instances. Yet, its evolutionary consequences are far-reaching, from the evolution of mating systems and sex determination to the emergence of new species. PMID:25524548

A Study on Attention Guidance to Driver by Subliminal Visual Information

NASA Astrophysics Data System (ADS)

Takahashi, Hiroshi; Honda, Hirohiko

This paper presents a new warning method for increasing drivers' sensitivity for recognizing hazardous factors in the driving environment. The method is based on a subliminal effect. The results of many experiments performed by three dimensional head-mounted display shows that the response time for detecting a flashing mark tended to decrease when a subliminal mark was shown in advance. Priming effects are observed in subliminal visual information. This paper also proposes a scenario for implementing this method in real vehicles.

S3: School Zone Safety System Based on Wireless Sensor Network

PubMed Central

Yoo, Seong-eun; Chong, Poh Kit; Kim, Daeyoung

2009-01-01

School zones are areas near schools that have lower speed limits and where illegally parked vehicles pose a threat to school children by obstructing them from the view of drivers. However, these laws are regularly flouted. Thus, we propose a novel wireless sensor network application called School zone Safety System (S3) to help regulate the speed limit and to prevent illegal parking in school zones. S3 detects illegally parked vehicles, and warns the driver and records the license plate number. To reduce the traveling speed of vehicles in a school zone, S3 measures the speed of vehicles and displays the speed to the driver via an LED display, and also captures the image of the speeding vehicle with a speed camera. We developed a state machine based vehicle detection algorithm for S3. From extensive experiments in our testbeds and data from a real school zone, it is shown that the system can detect all kinds of vehicles, and has an accuracy of over 95% for speed measurement. We modeled the battery life time of a sensor node and validated the model with a downscaled measurement; we estimate the battery life time to be over 2 years. We have deployed S3 in 15 school zones in 2007, and we have demonstrated the robustness of S3 by operating them for over 1 year. PMID:22454567

Assessing driving forces of land use and land cover change by a mixed-method approach in north-eastern Ghana, West Africa.

PubMed

Kleemann, Janina; Baysal, Gülendam; Bulley, Henry N N; Fürst, Christine

2017-07-01

Land use and land cover change (LULCC) is the result of complex human-environmental interactions. The high interdependencies in social-ecological systems make it difficult to identify the main drivers. However, knowledge of key drivers of LULCC, including indirect (underlying) drivers which cannot be easily determined by spatial or economic analyses, is essential for land use planning and especially important in developing countries. We used a mixed-method approach in order to detect drivers of LULCC in the Upper East Region of northern Ghana by different qualitative and quantitative methods which were compared in a confidence level analysis. Viewpoints from experts help to answer why the land use is changing, since many triggering effects, especially non-spatial and indirect drivers of LULCC, are not measurable by other methodological approaches. Geo-statistical or economic analyses add to validate the relevance of the expert-based results. First, we conducted in-depth interviews and developed a list of 34 direct and indirect drivers of LULCC. Subsequently, a group of experts was asked in a questionnaire to select the most important drivers by using a Likert scale. This information was complemented by remote sensing analysis. Finally, the driver analysis was compared to information from literature. Based on these analyses there is a very high confidence that population growth, especially in rural areas, is a major driver of LULCC. Further, current farming practice, bush fires, livestock, the road network and climate variability were the main direct drivers while the financial capital of farmers and customary norms regarding land tenure were listed as important indirect drivers with high confidence. Many of these driving forces, such as labour shortage and migration, are furthermore interdependent. Governmental laws, credits, the service by extension officers, conservational agriculture and foreign agricultural medium-scale investments are currently not driving land use changes. We conclude that the mixed-method approach improves the confidence of findings and the selection of most important drivers for modelling LULCC, especially in developing countries. Copyright © 2017 Elsevier Ltd. All rights reserved.

Road Anomalies Detection System Evaluation.

PubMed

Silva, Nuno; Shah, Vaibhav; Soares, João; Rodrigues, Helena

2018-06-21

Anomalies on road pavement cause discomfort to drivers and passengers, and may cause mechanical failure or even accidents. Governments spend millions of Euros every year on road maintenance, often causing traffic jams and congestion on urban roads on a daily basis. This paper analyses the difference between the deployment of a road anomalies detection and identification system in a “conditioned” and a real world setup, where the system performed worse compared to the “conditioned” setup. It also presents a system performance analysis based on the analysis of the training data sets; on the analysis of the attributes complexity, through the application of PCA techniques; and on the analysis of the attributes in the context of each anomaly type, using acceleration standard deviation attributes to observe how different anomalies classes are distributed in the Cartesian coordinates system. Overall, in this paper, we describe the main insights on road anomalies detection challenges to support the design and deployment of a new iteration of our system towards the deployment of a road anomaly detection service to provide information about roads condition to drivers and government entities.

Association of Metabolic Syndrome and Albuminuria with Cardiovascular Risk in Occupational Drivers

PubMed Central

Chen, Szu-Chia; Chang, Jer-Ming; Lin, Ming-Yen; Hou, Meng-Ling; Tsai, Jer-Chia; Hwang, Shang-Jyh; Chen, Hung-Chun

2013-01-01

Background and Aim Metabolic syndrome (MetS) and albuminuria increase cardiovascular risk. However, in occupational drivers, the clinical significance of albuminuria and its association with MetS remain unclear. We investigated the prevalence of MetS, albuminuria and cardiovascular risk, and its associated risk factors in occupational drivers; Methods 441 occupational drivers and 432 age- and sex-stratified matched counterpart controls were enrolled. MetS was defined using Adult Treatment Panel III for Asians. Albuminuria was defined as urine albumin-to-creatinine ratio ≥ 30 mg/g. Cardiovascular disease risk was evaluated by Framingham Risk Score (FRS); Results A significantly higher prevalence of MetS (43.1% vs. 25.5%, p < 0.001), albuminuria (12.0% vs. 5.6%, p = 0.001) and high FRS risk ≥ 10% of 10-year risk (46.9% vs. 35.2%, p < 0.001) was found in occupational drivers compared with their counterpart controls. Multiple logistic regression analysis showed that old age, a history of diabetes, gout and betel nut chewing, less exercise and albuminuria (odds ratio [OR], 2.75; p = 0.01) were risk factors for MetS, while a history of renal disease, diabetes and hypertension, and MetS (OR, 2.28; p = 0.01) were risk factors for albuminuria in occupational drivers; Conclusions Our study demonstrated that MetS and albuminuria were public health problems in occupational drivers. An education program for promoting healthy lifestyle and a regular occupational health visit for early detection and interventions should be established. PMID:24201129

A brief peripheral motion contrast threshold test predicts older drivers' hazardous behaviors in simulated driving.

PubMed

Henderson, Steven; Woods-Fry, Heather; Collin, Charles A; Gagnon, Sylvain; Voloaca, Misha; Grant, John; Rosenthal, Ted; Allen, Wade

2015-05-01

Our research group has previously demonstrated that the peripheral motion contrast threshold (PMCT) test predicts older drivers' self-report accident risk, as well as simulated driving performance. However, the PMCT is too lengthy to be a part of a battery of tests to assess fitness to drive. Therefore, we have developed a new version of this test, which takes under two minutes to administer. We assessed the motion contrast thresholds of 24 younger drivers (19-32) and 25 older drivers (65-83) with both the PMCT-10min and the PMCT-2min test and investigated if thresholds were associated with measures of simulated driving performance. Younger participants had significantly lower motion contrast thresholds than older participants and there were no significant correlations between younger participants' thresholds and any measures of driving performance. The PMCT-10min and the PMCT-2min thresholds of older drivers' predicted simulated crash risk, as well as the minimum distance of approach to all hazards. This suggests that our tests of motion processing can help predict the risk of collision or near collision in older drivers. Thresholds were also correlated with the total lane deviation time, suggesting a deficiency in processing of peripheral flow and delayed detection of adjacent cars. The PMCT-2min is an improved version of a previously validated test, and it has the potential to help assess older drivers' fitness to drive. Copyright © 2015 Elsevier Ltd. All rights reserved.

Studying the response of drivers against different collision warning systems: a review

NASA Astrophysics Data System (ADS)

Muzammel, M.; Yusoff, M. Zuki; Malik, A. Saeed; Mohamad Saad, M. Naufal; Meriaudeau, F.

2017-03-01

The number of vehicle accidents is rapidly increasing and causing significant economic losses in many countries. According to the World Health Organization, road accidents will become the fifth major cause of death by the year 2030. To minimize these accidents different types of collision warning systems have been proposed for motor vehicle drivers. These systems can early detect and warn the drivers about the potential danger, up to a certain accuracy. Many researchers study the effectiveness of these systems by using different methods, including Electroencephalography (EEG). From the literature review, it has been observed that, these systems increase the drivers' response and can help to minimize the accidents that may occur due to drivers unconsciousness. For these collision warning systems, tactile early warnings are found more effective as compared to the auditory and visual early warnings. This review also highlights the areas, where further research can be performed to fully analyze the collision warning system. For example, some contradictions are found among researchers, about these systems' performance for drivers within different age groups. Similarly, most of the EEG studies focus on the front collision warning systems and only give beep sound to alert the drivers. Therefore, EEG study can be performed for the rear end collision warning systems, against proper auditory warning messages which indicate the types of hazards. This EEG study will help to design more friendly collision warning system and may save many lives.

Myocardial infarction in Swedish subway drivers.

PubMed

Bigert, Carolina; Klerdal, Kristina; Hammar, Niklas; Gustavsson, Per

2007-08-01

Particulate matter in urban air is associated with the risk of myocardial infarction in the general population. Very high levels of airborne particles have been detected in the subway system of Stockholm, as well as in several other large cities. This situation has caused concern for negative health effects among subway staff. The aim of this study was to investigate whether there is an increased incidence of myocardial infarction among subway drivers. Data from a population-based case-control study of men aged 40-69 in Stockholm County in 1976-1996 were used. The study included all first events of myocardial infarction in registers of hospital discharges and deaths. The controls were selected randomly from the general population. National censuses were used for information on occupation. Altogether, 22 311 cases and 131 496 controls were included. Among these, 54 cases and 250 controls had worked as subway drivers. The relative risk of myocardial infarction among subway drivers was not increased. It was 0.92 [95% confidence interval (95% CI) 0.68-1.25] when the subway drivers were compared with other manual workers and 1.06 (95% CI 0.78-1.43) when the subway drivers were compared with all other gainfully employed men. Subgroup analyses indicated no influence on the risk of myocardial infarction from the duration of employment, latency time, or time since employment stopped. Subway drivers in Stockholm do not have a higher incidence of myocardial infarction than other employed persons.

Reliability of solid-state lighting electrical drivers subjected to WHTOL accelerated aging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lall, Pradeep; Sakalauku, Peter; Davis, Lynn

An investigation of a solid-state lighting (SSL) luminaire with the focus on the electronic driver which has been exposed to a standard wet hot temperature operating life (WHTOL) of 85% RH and 85°C in order to assess reliability of prolonged exposer to a harsh environment has been conducted. SSL luminaires are beginning introduced as head lamps in some of today's luxury automobiles and may also be fulfilling a variety of important outdoor applications such as overhead street lamps, traffic signals and landscape lighting. SSL luminaires in these environments are almost certain to encounter excessive moisture from humidity and high temperaturesmore » for a persistent period of time. The lack of accelerated test methods for LEDs to assess long-term reliability prior to introduction into the marketplace, a need for SSL physics based PHM modeling indicators for assessment and prediction of LED life, as well as the U.S. Department of Energy's R&D roadmap to replace todays lighting with SSL luminaires makes it important to increase the understanding of the reliability of SSL devices, specifically, in harsh environment applications. In this work, a set of SSL electrical drivers were investigated to determine failure mechanisms that occur during prolonged harsh environment applications. Each driver consists of four aluminum electrolytic capacitors (AECs) of three different types and was considered the weakest component inside the SSL electrical driver. The reliability of the electrical driver was assessed by monitoring the change in capacitance and the change in equivalent series resistance for each AEC, as well as monitoring the luminous flux of the SSL luminaire or the output of the electrical driver. The luminous flux of a pristine SSL electrical driver was also monitored in order to detect minute changes in the electrical drivers output and to aid in the investigation of the SSL luminaires reliability. The failure mechanisms of the electrical drivers have been determined and are presented in this paper.« less

A parametric duration model of the reaction times of drivers distracted by mobile phone conversations.

PubMed

Haque, Md Mazharul; Washington, Simon

2014-01-01

The use of mobile phones while driving is more prevalent among young drivers-a less experienced cohort with elevated crash risk. The objective of this study was to examine and better understand the reaction times of young drivers to a traffic event originating in their peripheral vision whilst engaged in a mobile phone conversation. The CARRS-Q advanced driving simulator was used to test a sample of young drivers on various simulated driving tasks, including an event that originated within the driver's peripheral vision, whereby a pedestrian enters a zebra crossing from a sidewalk. Thirty-two licensed drivers drove the simulator in three phone conditions: baseline (no phone conversation), hands-free and handheld. In addition to driving the simulator each participant completed questionnaires related to driver demographics, driving history, usage of mobile phones while driving, and general mobile phone usage history. The participants were 21-26 years old and split evenly by gender. Drivers' reaction times to a pedestrian in the zebra crossing were modelled using a parametric accelerated failure time (AFT) duration model with a Weibull distribution. Also tested where two different model specifications to account for the structured heterogeneity arising from the repeated measures experimental design. The Weibull AFT model with gamma heterogeneity was found to be the best fitting model and identified four significant variables influencing the reaction times, including phone condition, driver's age, license type (provisional license holder or not), and self-reported frequency of usage of handheld phones while driving. The reaction times of drivers were more than 40% longer in the distracted condition compared to baseline (not distracted). Moreover, the impairment of reaction times due to mobile phone conversations was almost double for provisional compared to open license holders. A reduction in the ability to detect traffic events in the periphery whilst distracted presents a significant and measurable safety concern that will undoubtedly persist unless mitigated. Copyright © 2013 Elsevier Ltd. All rights reserved.

The role of visual attention in predicting driving impairment in older adults.

PubMed

Hoffman, Lesa; McDowd, Joan M; Atchley, Paul; Dubinsky, Richard

2005-12-01

This study evaluated the role of visual attention (as measured by the DriverScan change detection task and the Useful Field of View Test [UFOV]) in the prediction of driving impairment in 155 adults between the ages of 63 and 87. In contrast to previous research, participants were not oversampled for visual impairment or history of automobile accidents. Although a history of automobile accidents within the past 3 years could not be predicted using any variable, driving performance in a low-fidelity simulator could be significantly predicted by performance in the change detection task and by the divided and selection attention subtests of the UFOV in structural equation models. The sensitivity and specificity of each measure in identifying at-risk drivers were also evaluated with receiver operating characteristic curves.

Human Factors Research Under Ground-Based and Space Conditions. Part 2

NASA Technical Reports Server (NTRS)

1997-01-01

In this session, Session WP2, the discussion focuses on the following topics: Training Astronauts Using Three-Dimensional Visualizations of the International Space Station; Measurement and Validation of Bidirectional Reflectance of Shuttle and Space Station Materials for Computerized Lighting Models; Effects of Environmental Color on Mood and Performance of Astronauts in ISS; Psychophysical Measures of Motion and Orientation, Implications for Human Interface Design; and the Sopite Syndrome Revisited, Drowsiness and Mood Changes in Student Aviators.

Operational Risk Management of Fatigue Effects II

DTIC Science & Technology

2008-08-01

to their low point in the pre-dawn hours. Additionally, the state of wakefulness, itself, unavoidably induces the state of sleepiness. If sleep...malaise 5b. Reduced aerobic capacity 5c. Drowsiness 5d. Sleep debt and need for recovery sleep 5e. Falling asleep on the job 5f. Dizziness 5g ...rhythm in metabolic rate and body temperature. This rhythm reaches its low point at about 04:00 in a person without jet lag or shift lag. 8

GHB: Forensic examination of a dangerous recreational drug by FTIR spectroscopy

NASA Astrophysics Data System (ADS)

Kindig, J. P.; Ellis, L. E.; Brueggemeyer, T. W.; Satzger, R. D.

1998-06-01

Gamma-hydroxybutyric acid (GHB) is an illegal drug that has been abused for its intoxicating effects. However, GHB can also produce harmful physiological effects ranging from mild (nausea, drowsiness) to severe (coma, death). Because GHB is often produced by clandestine manufacture, its concentration, purity, and final form can be variable. Therefore, the analysis of suspected GHB samples using FTIR spectroscopy requires a variety of sample preparations and accessories, based on the sample matrix.

Profound bradycardia associated with NIV removal.

PubMed

Echevarria, C; Bourke, S C; Gibson, G J

2012-01-01

A patient with lower-limb onset ALS presented with a one-month history of vasovagal episodes and a one-week history of cough productive of green sputum and lethargy. She was drowsy and in acute on chronic type-two respiratory failure. She responded to non-invasive ventilation, however she suffered recurrent episodes of profound bradycardia on removal of the mask, which gradually resolved over ten days. We have reviewed the literature and offer a potential explanation for these events.

Safety of Acupuncture Practice in Japan: Patient Reactions, Therapist Negligence and Error Reduction Strategies

PubMed Central

Tsukayama, Hiroshi

2008-01-01

Evidence-based approach on the safety of acupuncture had been lagging behind both in the West and the East, but reliable data based on some prospective surveys were published after the late 1990s. In the present article, we, focusing on ‘Japanese acupuncture’, review relevant case reports and prospective surveys on adverse events in Japan, assess the safety of acupuncture practice in this country, and suggest a strategy for reducing the therapists’ error. Based on the prospective surveys, it seems reasonable to suppose that serious adverse events are rare in standard practice by adequately trained acupuncturists, regardless of countries or modes of practice. Almost all of adverse reactions commonly seen in acupuncture practice—such as fatigue, drowsiness, aggravation, minor bleeding, pain on insertion and subcutaneous hemorrhage—are mild and transient, although we should be cautious of secondary injury following drowsiness and needle fainting. After demonstrating that acupuncture is inherently safe, we have been focusing on how to reduce the risk of negligence in Japan, as well as educating acupuncturists more about safe depth of insertion and infection control. Incident reporting and feedback system is a useful strategy for reducing therapist errors such as forgotten needles. For the benefit of acupuncture patients in Japan, it is important to establish mandatory postgraduate clinical training and continued education system. PMID:18955234

Mode of anesthesia and postoperative symptoms following abdominal hysterectomy in a fast-track setting.

PubMed

Wodlin, Ninnie Borendal; Nilsson, Lena; Arestedt, Kristofer; Kjølhede, Preben

2011-04-01

To determine whether postoperative symptoms differ between women who undergo abdominal benign hysterectomy in a fast-track model under general anesthesia or spinal anesthesia with intrathecal morphine. Secondary analysis from a randomized, open, multicenter study. Five hospitals in south-east Sweden. One-hundred and eighty women scheduled for benign hysterectomy were randomized; 162 completed the study; 82 were allocated to spinal and 80 to general anesthesia. The Swedish Postoperative Symptoms Questionnaire, completed daily for 1 week and thereafter once a week until 5 weeks postoperatively. Occurrence, intensity and duration of postoperative symptoms. Women who had hysterectomy under spinal anesthesia with intrathecal morphine experienced significantly less discomfort postoperatively compared with those who had the operation under general anesthesia. Spinal anesthesia reduced the need for opioids postoperatively. The most common symptoms were pain, nausea and vomiting, itching, drowsiness and fatigue. Abdominal pain, drowsiness and fatigue occurred significantly less often and with lower intensity among the spinal anesthesia group. Although postoperative nausea and vomiting was reported equally in the two groups, vomiting episodes were reported significantly more often during the first day after surgery in the spinal anesthesia group. Spinal anesthesia was associated with a higher prevalence of postoperative itching. Spinal anesthesia with intrathecal morphine carries advantages regarding postoperative symptoms and recovery following fast-track abdominal hysterectomy. © 2011 The Authors Acta Obstetricia et Gynecologica Scandinavica© 2011 Nordic Federation of Societies of Obstetrics and Gynecology.

SLEEP COMPLAINTS IN COMMUNITY-LIVING OLDER PERSONS: A MULTIFACTORIAL GERIATRIC SYNDROME

PubMed Central

Vaz Fragoso, Carlos A.; Gill, Thomas M.

2009-01-01

Among older persons, sleep complaints in the form of insomnia and daytime drowsiness are highly prevalent and associated with adverse outcomes. The underlying mechanisms are linked to age-related declines in physiology, i.e., normal aging, and age-related increases in disease prevalence, i.e., usual aging. In this monograph, we describe how normal aging leads to less restorative sleep, characterized by reductions in homeostatic and circadian sleep, and to phase advancement of the sleep-wake cycle, characterized by older persons being more alert in the early morning but drowsier in the early evening. We also describe how usual aging leads to sleep complaints through reductions in health status, loss of physical function, and primary sleep disorders. Psychosocial influences are likewise described and their relevance to sleep complaints is discussed. We subsequently incorporate these aging-related changes into a conceptual model that describes sleep complaints as a consequence of multiple and interdependent predisposing, precipitating, and perpetuating factors, akin to a geriatric syndrome. We conclude our discussion by applying our conceptual model to the sleep-related care of an older person with insomnia and daytime drowsiness, and suggest that the diagnostic assessment consider, in addition to primary sleep disorders, multiple domains including medical, physical, cognitive, psychological, and social issues with the intent of developing an overall therapeutic plan and establishing long-term follow-up. PMID:17916123

Driver face tracking using semantics-based feature of eyes on single FPGA

NASA Astrophysics Data System (ADS)

Yu, Ying-Hao; Chen, Ji-An; Ting, Yi-Siang; Kwok, Ngaiming

2017-06-01

Tracking driver's face is one of the essentialities for driving safety control. This kind of system is usually designed with complicated algorithms to recognize driver's face by means of powerful computers. The design problem is not only about detecting rate but also from parts damages under rigorous environments by vibration, heat, and humidity. A feasible strategy to counteract these damages is to integrate entire system into a single chip in order to achieve minimum installation dimension, weight, power consumption, and exposure to air. Meanwhile, an extraordinary methodology is also indispensable to overcome the dilemma of low-computing capability and real-time performance on a low-end chip. In this paper, a novel driver face tracking system is proposed by employing semantics-based vague image representation (SVIR) for minimum hardware resource usages on a FPGA, and the real-time performance is also guaranteed at the same time. Our experimental results have indicated that the proposed face tracking system is viable and promising for the smart car design in the future.

The co-occurrence of driver mutations in chronic myeloproliferative neoplasms.

PubMed

Boddu, Prajwal; Chihara, Dai; Masarova, Lucia; Pemmaraju, Naveen; Patel, Keyur P; Verstovsek, Srdan

2018-06-27

Myeloproliferative neoplasms (MPNs) are clonal disorders characterized by proliferation of one or more elements of the myeloid lineage. Key genetic aberrations include the BCR-ABL1 gene rearrangement in Philadelphia chromosome-positive chronic myelogenous leukemia (CML) and JAK2/MPL/CALR aberrations in Philadelphia chromosome-negative MPNs. While thought to be mutually exclusive, occasional isolated reports of coexistence of BCR-ABL1 and JAK2, and JAK2 with MPL or CALR aberrations have been described. Given the paucity of data, clinical characteristics and outcome of patients harboring concurrent Philadelphia-positive and Philadelphia-negative mutations or dual Philadelphia-negative driver mutations have not been systematically evaluated, and their clinical relevance is largely unknown. It is difficult to determine the true relevance of co-existing driver mutations on outcomes given the rarity of its occurrence. In this case series, we describe those patients who had dual driver mutations detected at any point during the course of their disease and characterized their clinical and laboratory features, bone marrow pathology, and overall disease course.

Contrasting models of driver behaviour in emergencies using retrospective verbalisations and network analysis.

PubMed

Banks, Victoria A; Stanton, Neville A

2015-01-01

Automated assistance in driving emergencies aims to improve the safety of our roads by avoiding or mitigating the effects of accidents. However, the behavioural implications of such systems remain unknown. This paper introduces the driver decision-making in emergencies (DDMiEs) framework to investigate how the level and type of automation may affect driver decision-making and subsequent responses to critical braking events using network analysis to interrogate retrospective verbalisations. Four DDMiE models were constructed to represent different levels of automation within the driving task and its effects on driver decision-making. Findings suggest that whilst automation does not alter the decision-making pathway (e.g. the processes between hazard detection and response remain similar), it does appear to significantly weaken the links between information-processing nodes. This reflects an unintended yet emergent property within the task network that could mean that we may not be improving safety in the way we expect. This paper contrasts models of driver decision-making in emergencies at varying levels of automation using the Southampton University Driving Simulator. Network analysis of retrospective verbalisations indicates that increasing the level of automation in driving emergencies weakens the link between information-processing nodes essential for effective decision-making.

Enhancing older driver safety: A driving survey and evaluation of the CarFit program.

PubMed

Gaines, Jean M; Burke, Kasey L; Marx, Katherine A; Wagner, Mary; Parrish, John M

2011-10-01

To evaluate CarFit, an educational program designed to promote optimal alignment of driver with vehicle. A driving activity survey was sent to 727 randomly selected participants living in retirement communities. Drivers (n=195) were assigned randomly to CarFit intervention (n=83, M age=78.1) or Comparison (n=112, M age=79.6) groups. After 6months, participants completed a post-test of driving activity and CarFit recommendations. Nonconsenting drivers were older and participated in fewer driving activities. CarFit participation was moderate (71%) with 86% of the participants receiving recommendations. 60% followed the recommendations at the 6-month re-evaluation). The CarFit (67.6%) and Comparison (59.3%) groups reported at least one type of self-regulation of driving activity at baseline. There was no significant change in the driving behaviors at the six-month follow-up. CarFit was able to detect addressable opportunities that may contribute to the safety of older drivers. CarFit recommendations may need stronger reinforcement in order to be enacted by a participant. Copyright © 2011 National Safety Council and Elsevier Ltd. All rights reserved.

Environment Modeling Using Runtime Values for JPF-Android

NASA Technical Reports Server (NTRS)

van der Merwe, Heila; Tkachuk, Oksana; Nel, Seal; van der Merwe, Brink; Visser, Willem

2015-01-01

Software applications are developed to be executed in a specific environment. This environment includes external native libraries to add functionality to the application and drivers to fire the application execution. For testing and verification, the environment of an application is simplified abstracted using models or stubs. Empty stubs, returning default values, are simple to generate automatically, but they do not perform well when the application expects specific return values. Symbolic execution is used to find input parameters for drivers and return values for library stubs, but it struggles to detect the values of complex objects. In this work-in-progress paper, we explore an approach to generate drivers and stubs based on values collected during runtime instead of using default values. Entry-points and methods that need to be modeled are instrumented to log their parameters and return values. The instrumented applications are then executed using a driver and instrumented libraries. The values collected during runtime are used to generate driver and stub values on- the-fly that improve coverage during verification by enabling the execution of code that previously crashed or was missed. We are implementing this approach to improve the environment model of JPF-Android, our model checking and analysis tool for Android applications.

Development of high precision digital driver of acoustic-optical frequency shifter for ROG

NASA Astrophysics Data System (ADS)

Zhang, Rong; Kong, Mei; Xu, Yameng

2016-10-01

We develop a high precision digital driver of the acoustic-optical frequency shifter (AOFS) based on the parallel direct digital synthesizer (DDS) technology. We use an atomic clock as the phase-locked loop (PLL) reference clock, and the PLL is realized by a dual digital phase-locked loop. A DDS sampling clock up to 320 MHz with a frequency stability as low as 10-12 Hz is obtained. By constructing the RF signal measurement system, it is measured that the frequency output range of the AOFS-driver is 52-58 MHz, the center frequency of the band-pass filter is 55 MHz, the ripple in the band is less than 1 dB@3MHz, the single channel output power is up to 0.3 W, the frequency stability is 1 ppb (1 hour duration), and the frequency-shift precision is 0.1 Hz. The obtained frequency stability has two orders of improvement compared to that of the analog AOFS-drivers. For the designed binary frequency shift keying (2-FSK) and binary phase shift keying (2-PSK) modulation system, the demodulating frequency of the input TTL synchronous level signal is up to 10 kHz. The designed digital-bus coding/decoding system is compatible with many conventional digital bus protocols. It can interface with the ROG signal detecting software through the integrated drive electronics (IDE) and exchange data with the two DDS frequency-shift channels through the signal detecting software.

Evaluation of Driver Visibility from Mobile LIDAR Data and Weather Conditions

NASA Astrophysics Data System (ADS)

González-Jorge, H.; Díaz-Vilariño, L.; Lorenzo, H.; Arias, P.

2016-06-01

Visibility of drivers is crucial to ensure road safety. Visibility is influenced by two main factors, the geometry of the road and the weather present therein. The present work depicts an approach for automatic visibility evaluation using mobile LiDAR data and climate information provided from weather stations located in the neighbourhood of the road. The methodology is based on a ray-tracing algorithm to detect occlusions from point clouds with the purpose of identifying the visibility area from each driver position. The resulting data are normalized with the climate information to provide a polyline with an accurate area of visibility. Visibility ranges from 25 m (heavy fog) to more than 10,000 m (clean atmosphere). Values over 250 m are not taken into account for road safety purposes, since this value corresponds to the maximum braking distance of a vehicle. Two case studies are evaluated an urban road in the city of Vigo (Spain) and an inter-urban road between the city of Ourense and the village of Castro Caldelas (Spain). In both cases, data from the Galician Weather Agency (Meteogalicia) are used. The algorithm shows promising results allowing the detection of particularly dangerous areas from the viewpoint of driver visibility. The mountain road between Ourense and Castro Caldelas, with great presence of slopes and sharp curves, shows special interest for this type of application. In this case, poor visibility can especially contribute to the run over of pedestrians or cyclists traveling on the road shoulders.

An Orientation Sensor-Based Head Tracking System for Driver Behaviour Monitoring

PubMed Central

Görne, Lorenz; Yuen, Iek-Man; Cao, Dongpu; Sullman, Mark; Auger, Daniel; Lv, Chen; Wang, Huaji; Matthias, Rebecca; Skrypchuk, Lee; Mouzakitis, Alexandros

2017-01-01

Although at present legislation does not allow drivers in a Level 3 autonomous vehicle to engage in a secondary task, there may become a time when it does. Monitoring the behaviour of drivers engaging in various non-driving activities (NDAs) is crucial to decide how well the driver will be able to take over control of the vehicle. One limitation of the commonly used face-based head tracking system, using cameras, is that sufficient features of the face must be visible, which limits the detectable angle of head movement and thereby measurable NDAs, unless multiple cameras are used. This paper proposes a novel orientation sensor based head tracking system that includes twin devices, one of which measures the movement of the vehicle while the other measures the absolute movement of the head. Measurement error in the shaking and nodding axes were less than 0.4°, while error in the rolling axis was less than 2°. Comparison with a camera-based system, through in-house tests and on-road tests, showed that the main advantage of the proposed system is the ability to detect angles larger than 20° in the shaking and nodding axes. Finally, a case study demonstrated that the measurement of the shaking and nodding angles, produced from the proposed system, can effectively characterise the drivers’ behaviour while engaged in the NDAs of chatting to a passenger and playing on a smartphone. PMID:29165331

Human-factors engineering for smart transport: design support for car drivers and train traffic controllers.

PubMed

Lenior, Dick; Janssen, Wiel; Neerincx, Mark; Schreibers, Kirsten

2006-07-01

The theme Smart Transport can be described as adequate human-system symbiosis to realize effective, efficient and human-friendly transport of goods and information. This paper addresses how to attune automation to human (cognitive) capacities (e.g. to take care of information uncertainty, operator trust and mutual man-machine adaptations). An introduction to smart transport is presented, including examples of best practice for engineering human factors in the vehicle ergonomics and train traffic control domain. The examples are representative of an ongoing trend in automation and they show how the human role changes from controller to supervisor. Section 2 focuses on the car driver and systems that support, or sometimes even take over, critical parts of the driving task. Due to the diversity of driver ability, driving context and dependence between driver and context factors, there is a need for personalised, adaptive and integrated support. Systematic research is needed to establish sound systems. Section 3 focuses on the train dispatcher support systems that predict train movements, detect potential conflicts and show the dispatcher the possibilities available to solve the detected problems. Via thorough analysis of both the process to be controlled and the dispatcher's tasks and cognitive needs, support functions were developed as part of an already very complex supervision and control system. The two examples, although from a different field, both show the need for further development in cognitive modelling as well as for the value of sound ergonomics task analysis in design practice.

VarWalker: Personalized Mutation Network Analysis of Putative Cancer Genes from Next-Generation Sequencing Data

PubMed Central

Jia, Peilin; Zhao, Zhongming

2014-01-01

A major challenge in interpreting the large volume of mutation data identified by next-generation sequencing (NGS) is to distinguish driver mutations from neutral passenger mutations to facilitate the identification of targetable genes and new drugs. Current approaches are primarily based on mutation frequencies of single-genes, which lack the power to detect infrequently mutated driver genes and ignore functional interconnection and regulation among cancer genes. We propose a novel mutation network method, VarWalker, to prioritize driver genes in large scale cancer mutation data. VarWalker fits generalized additive models for each sample based on sample-specific mutation profiles and builds on the joint frequency of both mutation genes and their close interactors. These interactors are selected and optimized using the Random Walk with Restart algorithm in a protein-protein interaction network. We applied the method in >300 tumor genomes in two large-scale NGS benchmark datasets: 183 lung adenocarcinoma samples and 121 melanoma samples. In each cancer, we derived a consensus mutation subnetwork containing significantly enriched consensus cancer genes and cancer-related functional pathways. These cancer-specific mutation networks were then validated using independent datasets for each cancer. Importantly, VarWalker prioritizes well-known, infrequently mutated genes, which are shown to interact with highly recurrently mutated genes yet have been ignored by conventional single-gene-based approaches. Utilizing VarWalker, we demonstrated that network-assisted approaches can be effectively adapted to facilitate the detection of cancer driver genes in NGS data. PMID:24516372

VarWalker: personalized mutation network analysis of putative cancer genes from next-generation sequencing data.

PubMed

Jia, Peilin; Zhao, Zhongming

2014-02-01

A major challenge in interpreting the large volume of mutation data identified by next-generation sequencing (NGS) is to distinguish driver mutations from neutral passenger mutations to facilitate the identification of targetable genes and new drugs. Current approaches are primarily based on mutation frequencies of single-genes, which lack the power to detect infrequently mutated driver genes and ignore functional interconnection and regulation among cancer genes. We propose a novel mutation network method, VarWalker, to prioritize driver genes in large scale cancer mutation data. VarWalker fits generalized additive models for each sample based on sample-specific mutation profiles and builds on the joint frequency of both mutation genes and their close interactors. These interactors are selected and optimized using the Random Walk with Restart algorithm in a protein-protein interaction network. We applied the method in >300 tumor genomes in two large-scale NGS benchmark datasets: 183 lung adenocarcinoma samples and 121 melanoma samples. In each cancer, we derived a consensus mutation subnetwork containing significantly enriched consensus cancer genes and cancer-related functional pathways. These cancer-specific mutation networks were then validated using independent datasets for each cancer. Importantly, VarWalker prioritizes well-known, infrequently mutated genes, which are shown to interact with highly recurrently mutated genes yet have been ignored by conventional single-gene-based approaches. Utilizing VarWalker, we demonstrated that network-assisted approaches can be effectively adapted to facilitate the detection of cancer driver genes in NGS data.

A Manual Control Test for the Detection and Deterrence of Impaired Drivers

NASA Technical Reports Server (NTRS)

Stein, A. C.; Allen, R. W.; Jex, H. R.

1984-01-01

A brief manual control test and a decision strategy were developed, laboratory tested, and field validated which provide a means for detecting human operator impairment from alcohol or other drugs. The test requires the operator to stabilize progressively unstable controlled element dynamics. Control theory and experimental data verify that the human operator's control ability on this task is constrained by basic cybernetic characteristics, and that task performance is reliably affected by impairment effects on these characteristics. Assessment of human operator control ability is determined by a statistically based decision strategy. The operator is allowed several chances to exceed a preset pass criterion. Procedures are described for setting the pass criterion based on individual ability and a desired unimpaired failure rate. These procedures were field tested with apparatus installed in automobiles that were designed to discourage drunk drivers from operating their vehicles. This test program demonstrated that the control task and detection strategy could be applied in a practical setting to screen human operators for impairment in their basic cybernetic skills.

Sex chromosome drive.

PubMed

Helleu, Quentin; Gérard, Pierre R; Montchamp-Moreau, Catherine

2014-12-18

Sex chromosome drivers are selfish elements that subvert Mendel's first law of segregation and therefore are overrepresented among the products of meiosis. The sex-biased progeny produced then fuels an extended genetic conflict between the driver and the rest of the genome. Many examples of sex chromosome drive are known, but the occurrence of this phenomenon is probably largely underestimated because of the difficulty to detect it. Remarkably, nearly all sex chromosome drivers are found in two clades, Rodentia and Diptera. Although very little is known about the molecular and cellular mechanisms of drive, epigenetic processes such as chromatin regulation could be involved in many instances. Yet, its evolutionary consequences are far-reaching, from the evolution of mating systems and sex determination to the emergence of new species. Copyright © 2015 Cold Spring Harbor Laboratory Press; all rights reserved.

Method and apparatus for communicating computer data from one point to another over a communications medium

DOEpatents

Arneson, Michael R [Chippewa Falls, WI; Bowman, Terrance L [Sumner, WA; Cornett, Frank N [Chippewa Falls, WI; DeRyckere, John F [Eau Claire, WI; Hillert, Brian T [Chippewa Falls, WI; Jenkins, Philip N [Eau Claire, WI; Ma, Nan [Chippewa Falls, WI; Placek, Joseph M [Chippewa Falls, WI; Ruesch, Rodney [Eau Claire, WI; Thorson, Gregory M [Altoona, WI

2007-07-24

The present invention is directed toward a communications channel comprising a link level protocol, a driver, a receiver, and a canceller/equalizer. The link level protocol provides logic for DC-free signal encoding and recovery as well as supporting many features including CRC error detection and message resend to accommodate infrequent bit errors across the medium. The canceller/equalizer provides equalization for destabilized data signals and also provides simultaneous bi-directional data transfer. The receiver provides bit deskewing by removing synchronization error, or skewing, between data signals. The driver provides impedance controlling by monitoring the characteristics of the communications medium, like voltage or temperature, and providing a matching output impedance in the signal driver so that fewer distortions occur while the data travels across the communications medium.

Baseline Face Detection, Head Pose Estimation, and Coarse Direction Detection for Facial Data in the SHRP2 Naturalistic Driving Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paone, Jeffrey R; Bolme, David S; Ferrell, Regina Kay

Keeping a driver focused on the road is one of the most critical steps in insuring the safe operation of a vehicle. The Strategic Highway Research Program 2 (SHRP2) has over 3,100 recorded videos of volunteer drivers during a period of 2 years. This extensive naturalistic driving study (NDS) contains over one million hours of video and associated data that could aid safety researchers in understanding where the driver s attention is focused. Manual analysis of this data is infeasible, therefore efforts are underway to develop automated feature extraction algorithms to process and characterize the data. The real-world nature, volume,more » and acquisition conditions are unmatched in the transportation community, but there are also challenges because the data has relatively low resolution, high compression rates, and differing illumination conditions. A smaller dataset, the head pose validation study, is available which used the same recording equipment as SHRP2 but is more easily accessible with less privacy constraints. In this work we report initial head pose accuracy using commercial and open source face pose estimation algorithms on the head pose validation data set.« less

Comparison of Different Features and Classifiers for Driver Fatigue Detection Based on a Single EEG Channel

PubMed Central

2017-01-01

Driver fatigue has become an important factor to traffic accidents worldwide, and effective detection of driver fatigue has major significance for public health. The purpose method employs entropy measures for feature extraction from a single electroencephalogram (EEG) channel. Four types of entropies measures, sample entropy (SE), fuzzy entropy (FE), approximate entropy (AE), and spectral entropy (PE), were deployed for the analysis of original EEG signal and compared by ten state-of-the-art classifiers. Results indicate that optimal performance of single channel is achieved using a combination of channel CP4, feature FE, and classifier Random Forest (RF). The highest accuracy can be up to 96.6%, which has been able to meet the needs of real applications. The best combination of channel + features + classifier is subject-specific. In this work, the accuracy of FE as the feature is far greater than the Acc of other features. The accuracy using classifier RF is the best, while that of classifier SVM with linear kernel is the worst. The impact of channel selection on the Acc is larger. The performance of various channels is very different. PMID:28255330

Comparison of Different Features and Classifiers for Driver Fatigue Detection Based on a Single EEG Channel.

PubMed

Hu, Jianfeng

2017-01-01

Driver fatigue has become an important factor to traffic accidents worldwide, and effective detection of driver fatigue has major significance for public health. The purpose method employs entropy measures for feature extraction from a single electroencephalogram (EEG) channel. Four types of entropies measures, sample entropy (SE), fuzzy entropy (FE), approximate entropy (AE), and spectral entropy (PE), were deployed for the analysis of original EEG signal and compared by ten state-of-the-art classifiers. Results indicate that optimal performance of single channel is achieved using a combination of channel CP4, feature FE, and classifier Random Forest (RF). The highest accuracy can be up to 96.6%, which has been able to meet the needs of real applications. The best combination of channel + features + classifier is subject-specific. In this work, the accuracy of FE as the feature is far greater than the Acc of other features. The accuracy using classifier RF is the best, while that of classifier SVM with linear kernel is the worst. The impact of channel selection on the Acc is larger. The performance of various channels is very different.

Mutation analysis of 13 driver genes of colorectal cancer-related pathways in Taiwanese patients

PubMed Central

Chang, Yuli Christine; Chang, Jan-Gowth; Liu, Ta-Chih; Lin, Chien-Yu; Yang, Shu-Fen; Ho, Cheng-Mao; Chen, William Tzu-Liang; Chang, Ya-Sian

2016-01-01

AIM: To investigate the driver gene mutations associated with colorectal cancer (CRC) in the Taiwanese population. METHODS: In this study, 103 patients with CRC were evaluated. The samples consisted of 66 men and 37 women with a median age of 59 years and an age range of 26-86 years. We used high-resolution melting analysis (HRM) and direct DNA sequencing to characterize the mutations in 13 driver genes of CRC-related pathways. The HRM assays were conducted using the LightCycler® 480 Instrument provided with the software LightCycler® 480 Gene Scanning Software Version 1.5. We also compared the clinicopathological data of CRC patients with the driver gene mutation status. RESULTS: Of the 103 patients evaluated, 73.79% had mutations in one of the 13 driver genes. We discovered 18 novel mutations in APC, MLH1, MSH2, PMS2, SMAD4 and TP53 that have not been previously reported. Additionally, we found 16 de novo mutations in APC, BMPR1A, MLH1, MSH2, MSH6, MUTYH and PMS2 in cancerous tissues previously reported in the dbSNP database; however, these mutations could not be detected in peripheral blood cells. The APC mutation correlates with lymph node metastasis (34.69% vs 12.96%, P = 0.009) and cancer stage (34.78% vs 14.04%, P = 0.013). No association was observed between other driver gene mutations and clinicopathological features. Furthermore, having two or more driver gene mutations correlates with the degree of lymph node metastasis (42.86% vs 24.07%, P = 0.043). CONCLUSION: Our findings confirm the importance of 13 CRC-related pathway driver genes in the development of CRC in Taiwanese patients. PMID:26900293

Mutation analysis of 13 driver genes of colorectal cancer-related pathways in Taiwanese patients.

PubMed

Chang, Yuli Christine; Chang, Jan-Gowth; Liu, Ta-Chih; Lin, Chien-Yu; Yang, Shu-Fen; Ho, Cheng-Mao; Chen, William Tzu-Liang; Chang, Ya-Sian

2016-02-21

To investigate the driver gene mutations associated with colorectal cancer (CRC) in the Taiwanese population. In this study, 103 patients with CRC were evaluated. The samples consisted of 66 men and 37 women with a median age of 59 years and an age range of 26-86 years. We used high-resolution melting analysis (HRM) and direct DNA sequencing to characterize the mutations in 13 driver genes of CRC-related pathways. The HRM assays were conducted using the LightCycler® 480 Instrument provided with the software LightCycler® 480 Gene Scanning Software Version 1.5. We also compared the clinicopathological data of CRC patients with the driver gene mutation status. Of the 103 patients evaluated, 73.79% had mutations in one of the 13 driver genes. We discovered 18 novel mutations in APC, MLH1, MSH2, PMS2, SMAD4 and TP53 that have not been previously reported. Additionally, we found 16 de novo mutations in APC, BMPR1A, MLH1, MSH2, MSH6, MUTYH and PMS2 in cancerous tissues previously reported in the dbSNP database; however, these mutations could not be detected in peripheral blood cells. The APC mutation correlates with lymph node metastasis (34.69% vs 12.96%, P = 0.009) and cancer stage (34.78% vs 14.04%, P = 0.013). No association was observed between other driver gene mutations and clinicopathological features. Furthermore, having two or more driver gene mutations correlates with the degree of lymph node metastasis (42.86% vs 24.07%, P = 0.043). Our findings confirm the importance of 13 CRC-related pathway driver genes in the development of CRC in Taiwanese patients.

Influence of age, speed and duration of monotonous driving task in traffic on the driver's useful visual field.

PubMed

Rogé, Joceline; Pébayle, Thierry; Lambilliotte, Elina; Spitzenstetter, Florence; Giselbrecht, Danièle; Muzet, Alain

2004-10-01

Recent research has shown that the useful visual field deteriorates in simulated car driving when the latter can induce a decrease in the level of activation. The first aim of this study was to verify if the same phenomenon occurs when driving is performed in a simulated road traffic situation. The second aim was to discover if this field also deteriorates as a function of the driver's age and of the vehicle's speed. Nine young drivers (from 22 to 34 years) and nine older drivers (from 46 to 59 years) followed a vehicle in road traffic during two two-hour sessions. The car-following task involved driving at 90 km.h(-1) (speed limit on road in France) in one session and at 130 km.h(-1) (speed limit on motorway in France) in the other session. While following the vehicle, the driver had to detect the changes in colour of a luminous signal located in the central part of his/her visual field and a visual signal that appeared at different eccentricities on the rear lights of the vehicles in the traffic. The analysis of the data indicates that the useful visual field deteriorates with the prolongation of the monotonous simulated driving task, with the driver's age and with the vehicle's speed. The results are discussed in terms of general interference and tunnel vision.

Hardcore drinking drivers and other contributors to the alcohol-impaired driving problem: need for a comprehensive approach.

PubMed

Williams, Allan F; McCartt, Anne T; Ferguson, Susan A

2007-03-01

Understanding the hardcore drinking driver concept in the context of the alcohol-impaired driving problem. Review of the relevant literature. As progress against alcohol-impaired driving slowed in the early 1990s, public and political attention turned to "hardcore" drinking drivers, and they have been a priority for the past 15 years. Though intuitive, the hardcore concept has been difficult to conceptualize. Its definition of hard-to-change chronic heavy drinking drivers focuses on a group that is not easily identifiable and ignores many who account for a large portion of alcohol-impaired driving crashes. These include drivers who drink heavily on occasion and drivers who drink at more moderate levels that elevate crash risk. Emphasis on the hardcore has focused attention on the small proportion of drinking drivers who have been detected and arrested, whereas the vast majority of drinking drivers go undetected. Some countermeasures aimed at the hardcore group have been effective in reducing recidivism, but attention and resources also need to be given to general deterrent initiatives (e.g., 0.08 g/dL, sobriety checkpoints, administrative license suspension). There has been no reduction in the overall alcohol-impaired driving problem since the mid-1990s. Reductions in the alcohol-impaired driving problem require that attention be focused on all relevant target groups. Some benefits could accrue by recognizing that countermeasures developed for hardcore drinking drivers, such as alcohol ignition interlocks and vehicle or plate impoundment, might also be effective with more numerous first-time offenders. However, such strategies are likely to be most effective against recidivism (specific deterrence). Greater gains could be achieved through general deterrent efforts (increasing the real and perceived risk of arrest and punishment to all drinking drivers), along with application of public health measures designed to reduce overall consumption. Additional ways need to be found to separate drinking and driving, either through cultural changes in drinking and/or driving behavior or, in the future, with the use of technology that can make vehicles inoperable by drivers with illegal blood alcohol concentrations.

Multiple pedestrian detection using IR LED stereo camera

NASA Astrophysics Data System (ADS)

Ling, Bo; Zeifman, Michael I.; Gibson, David R. P.

2007-09-01

As part of the U.S. Department of Transportations Intelligent Vehicle Initiative (IVI) program, the Federal Highway Administration (FHWA) is conducting R&D in vehicle safety and driver information systems. There is an increasing number of applications where pedestrian monitoring is of high importance. Visionbased pedestrian detection in outdoor scenes is still an open challenge. People dress in very different colors that sometimes blend with the background, wear hats or carry bags, and stand, walk and change directions unpredictably. The background is various, containing buildings, moving or parked cars, bicycles, street signs, signals, etc. Furthermore, existing pedestrian detection systems perform only during daytime, making it impossible to detect pedestrians at night. Under FHWA funding, we are developing a multi-pedestrian detection system using IR LED stereo camera. This system, without using any templates, detects the pedestrians through statistical pattern recognition utilizing 3D features extracted from the disparity map. A new IR LED stereo camera is being developed, which can help detect pedestrians during daytime and night time. Using the image differencing and denoising, we have also developed new methods to estimate the disparity map of pedestrians in near real time. Our system will have a hardware interface with the traffic controller through wireless communication. Once pedestrians are detected, traffic signals at the street intersections will change phases to alert the drivers of approaching vehicles. The initial test results using images collected at a street intersection show that our system can detect pedestrians in near real time.

Review of Technology to Prevent Alcohol-Impaired Crashes (TOPIC)

DOT National Transportation Integrated Search

2007-07-01

This report summarizes the results of an evaluation of vehicular technology alternatives to detect driver blood alcohol concentration and alcohol- : impaired driving. Taking an international perspective, this report references relevant literature, in...

Vehicle Clearance: Literature Review

DOT National Transportation Integrated Search

2015-10-05

This project will investigate and test truck-mounted LIDAR and optical sensors to determine their feasibility for detecting hazardous bridge/tunnel heights for warning the driver of an overheight truck. This document, which describes the problem and ...

Vehicle clearance : literature review.

DOT National Transportation Integrated Search

2015-10-05

This project will investigate and test truck-mounted LIDAR and optical sensors to determine their feasibility for detecting hazardous bridge/tunnel heights for warning the driver of an overheight truck. This document, which describes the problem and ...

The ironies of vehicle feedback in car design.

PubMed

Walker, Guy H; Stanton, Neville A; Young, Mark S

2006-02-10

Car drivers show an acute sensitivity towards vehicle feedback, with most normal drivers able to detect 'the difference in vehicle feel of a medium-size saloon car with and without a fairly heavy passenger in the rear seat' (Joy and Hartley 1953-54). The irony is that this level of sensitivity stands in contrast to the significant changes in vehicle 'feel' accompanying modern trends in automotive design, such as drive-by-wire and increased automation. The aim of this paper is to move the debate from the anecdotal to the scientific level. This is achieved by using the Brunel University driving simulator to replicate some of these trends and changes by presenting (or removing) different forms of non-visual vehicle feedback, and measuring resultant driver situational awareness (SA) using a probe-recall method. The findings confirm that vehicle feedback plays a key role in coupling the driver to the dynamics of their environment (Moray 2004), with the role of auditory feedback particularly prominent. As a contrast, drivers in the study also rated their self-perceived levels of SA and a concerning dissociation occurred between the two sets of results. Despite the large changes in vehicle feedback presented in the simulator, and the measured changes in SA, drivers appeared to have little self-awareness of these changes. Most worryingly, drivers demonstrated little awareness of diminished SA. The issues surrounding vehicle feedback are therefore similar to the classic problems and ironies studied in aviation and automation, and highlight the role that ergonomics can also play within the domain of contemporary vehicle design.

Use of illicit drugs by truck drivers arriving at Paranaguá port terminal, Brazil.

PubMed

Peixe, Tiago Severo; de Almeida, Rafael Menck; Girotto, Edmarlon; de Andrade, Selma Maffei; Mesas, Arthur Eumann

2014-01-01

The purpose of this study was to estimate the prevalence of recent use of illicit drugs among truck drivers who had parked their vehicles at the terminal port in Paranaguá City at Paraná State, southern Brazil. This cross-sectional study was part of a larger research project conducted among drivers at a regional Brazilian port. Data on professional characteristics, involvement in road traffic injuries, sleep, and use of alcohol and illicit drugs were collected using a questionnaire. Urine samples were collected and analyzed for amphetamines, cocaine, and cannabis using gas chromatography with mass spectrometric detection. Sixty-two drivers were included in the study. Toxicological analyses showed that 8.1 percent (95% confidence interval [CI], 2.7-17.8%) of the urine samples were positive for drugs (4.8% for cocaine, 1.6% for amphetamine, and 1.6% for both); 8.1 percent reported drug use during the preceding 30 days in the questionnaire and only one tested positive for the drug in the urine sample. No sample was positive for cannabinoids. In total, at least 14.5 percent (95% CI, 6.9-25.8%) had used illicit drugs during the preceding 30 days based on self-reports and urine testing. Drivers who reported involvement in traffic injuries the year before more often tested positive for drugs in biological samples (P <.05). This research provides preliminary evidence that the use of illicit stimulants was common among professional truck drivers transporting grain loads. Thus, actions are needed to reduce drug use among truck drivers in order to prevent drug-related road traffic injuries.

Fatal passenger vehicle crashes 1999 to 2004 with drivers under age 15: the impact in Texas and other southern and southwestern states.

PubMed

Frisch, Larry

2007-03-01

Texas has more fatal crashes involving unlicensed drivers under age 15 than does any other US state. Numbers and rates of such crashes are also above the national mean in many southern and Southwest states. Data on fatal passenger vehicle crashes from 1999 through 2004 were obtained from the online Fatality Analysis Reporting System (FARS). During the study period, there were 51 fatal passenger vehicle crashes in Texas in which drivers were under age 15. These crashes accounted for 12.3% of the US total. Nine southern states, including Texas, together accounted for 44% of all fatal crashes involving drivers under 15. Unlicensed crash rates per million inhabitants were higher in Texas than in other states with comparable populations but were much lower than those in other southern, southwest, and north central states. While Texas has recently improved its compliance with proposed graduated licensing models, state law explicitly prohibits police from stopping drivers based solely on age-related probable cause. This restriction may be a major barrier to effective detection and interdiction of under-age unlicensed driving. Because of the relatively high number of fatal crashes involving drivers under age 15 occurring in Texas, preventive efforts targeted to this state could modestly reduce the national burden of deaths due to very young unlicensed drivers. Expanding these efforts to other southern and southwest states could further reduce numbers and rates of such crashes. Expanded use of graduated licensing and increased public awareness are likely to prove effective tools in this public health effort.

Examining drivers' eye glance patterns during distracted driving: Insights from scanning randomness and glance transition matrix.

PubMed

Wang, Yuan; Bao, Shan; Du, Wenjun; Ye, Zhirui; Sayer, James R

2017-12-01

Visual attention to the driving environment is of great importance for road safety. Eye glance behavior has been used as an indicator of distracted driving. This study examined and quantified drivers' glance patterns and features during distracted driving. Data from an existing naturalistic driving study were used. Entropy rate was calculated and used to assess the randomness associated with drivers' scanning patterns. A glance-transition proportion matrix was defined to quantity visual search patterns transitioning among four main eye glance locations while driving (i.e., forward on-road, phone, mirrors and others). All measurements were calculated within a 5s time window under both cell phone and non-cell phone use conditions. Results of the glance data analyses showed different patterns between distracted and non-distracted driving, featured by a higher entropy rate value and highly biased attention transferring between forward and phone locations during distracted driving. Drivers in general had higher number of glance transitions, and their on-road glance duration was significantly shorter during distracted driving when compared to non-distracted driving. Results suggest that drivers have a higher scanning randomness/disorder level and shift their main attention from surrounding areas towards phone area when engaging in visual-manual tasks. Drivers' visual search patterns during visual-manual distraction with a high scanning randomness and a high proportion of eye glance transitions towards the location of the phone provide insight into driver distraction detection. This will help to inform the design of in-vehicle human-machine interface/systems. Copyright © 2017. Published by Elsevier Ltd.

Drivers of the primate thalamus

PubMed Central

Rovó, Zita; Ulbert, István; Acsády, László

2012-01-01

The activity of thalamocortical neurons is largely determined by giant excitatory terminals, called drivers. These afferents may arise from neocortex or from subcortical centers; however their exact distribution, segregation or putative absence in given thalamic nuclei are unknown. To unravel the nucleus-specific composition of drivers, we mapped the entire macaque thalamus utilizing vesicular glutamate transporters 1 and 2 to label cortical and subcortical afferents, respectively. Large thalamic territories were innervated exclusively either by giant vGLUT2- or vGLUT1-positive boutons. Co-distribution of drivers with different origin was not abundant. In several thalamic regions, no giant terminals of any type could be detected at light microscopic level. Electron microscopic observation of these territories revealed either the complete absence of large multisynaptic excitatory terminals (basal ganglia-recipient nuclei) or the presence of both vGLUT1- and vGLUT2-positive terminals, which were significantly smaller than their giant counterparts (intralaminar nuclei, medial pulvinar). In the basal ganglia-recipient thalamus, giant inhibitory terminals replaced the excitatory driver inputs. The pulvinar and the mediodorsal nucleus displayed subnuclear heterogeneity in their driver assemblies. These results show that distinct thalamic territories can be under pure subcortical or cortical control; however there is significant variability in the composition of major excitatory inputs in several thalamic regions. Since thalamic information transfer depends on the origin and complexity of the excitatory inputs, this suggests that the computations performed by individual thalamic regions display considerable variability. Finally, the map of driver distribution may help to resolve the morphological basis of human diseases involving different parts of the thalamus. PMID:23223308

The influence of thermal biology on road mortality risk in snakes.

PubMed

Mccardle, Logan D; Fontenot, Clifford L

2016-02-01

Road mortality is a significant threat to terrestrial vertebrates in many areas, and the novel thermal environment of black-topped roads may represent ecological traps for some species and demographic groups. We investigated the relationship between ambient temperature and on-road detection in a snake assemblage in southeastern Louisiana by comparing observations of live snakes on a black-topped road, across measurements of air temperature and road temperature on survey days. Analyses indicated on-road detection of snakes was significantly influenced by ambient temperature conditions for five snake species. Additionally, road temperatures, and the difference between air and road temperatures, were strong drivers of on-road snake detections. Permutation analysis methods revealed that significant temperature related group (species or sex) structure exists in occurrences of snakes on the roadway, and that road temperature was the strongest driver of species differences. We also compared how air and road temperatures affected occurrence on the road between sexes in the colubrid snakes Nerodia fasciata, Nerodia cyclopion, Thamnophis proximus, and Pantherophis obsoletus. Males and females of the viviparous species N. fasciata, N. cyclopion, and T. proximus diverged significantly in temperature preferences, with females found under warmer conditions, while males and females of the oviparous species P. obsoletus did not. Road temperature was also the strongest driver of differences between sexes. Our results indicate that black-topped roads are an ecological trap that is heavily influenced by sex, reproductive condition, and species specific thermoregulatory requirements, particularly for viviparous species. Copyright © 2015 Elsevier Ltd. All rights reserved.

Comparing car drivers' and motorcyclists' opinions about junction crashes.

PubMed

Robbins, Chloe J; Allen, Harriet A; Chapman, Peter

2018-08-01

Motorcyclists are involved in a disproportionate number of crashes given the distance they travel, with a high proportion of these crashes occurring at junctions. Despite car drivers being solely responsible for many road crashes involving a motorcycle, previous research has mostly focussed on understanding motorcyclists' attitudes towards their own safety. We compared car drivers' (n = 102) and motorcyclists' (n = 579) opinions about junction crashes using a web-based questionnaire. Motorcyclists and car drivers were recruited in similar ways so that responses could be directly compared, accessing respondents through driver/rider forums and on social media. Car drivers' and motorcyclists' opinions were compared in relation to who they believe to be blameworthy in situations which varied in specificity, ranging from what road user they believe is most likely to cause a motorcyclist to have a road crash, to what road user is at fault in four specific scenarios involving a car and motorcycle at a junction. Two of these scenarios represented typical 'Right of way' (ROW) crashes with a motorcycle approaching from the left and right, and two scenarios involved a motorcycle overtaking another vehicle at the junction, known as 'Motorcycle Manoeuvrability Accidents' (MMA). Qualitative responses were analysed using LIWC software to detect objective differences in car drivers' and motorcyclists' language. Car drivers' and motorcyclists' opinions about the blameworthiness of accidents changed depending on how specific the situation was that was being presented. When respondents were asked about the cause of motorcycle crashes in a general abstract sense, car drivers' and motorcyclists' responses significantly differed, with motorcyclists more likely to blame car drivers, demonstrating an in-group bias. However, this in-group favouritism was reduced when asked about specific scenarios, especially in MMA situations which involve motorcyclists manoeuvring their motorcycles around cars at a junction. In the four specific scenarios, car drivers were more likely to blame the car driver, and motorcyclists were more likely to blame the motorcyclist. In the typical ROW scenarios, the responses given by both road users, as analysed by the LIWC, show that the law is taken into account, as well as a large emphasis on the lack of observation given around junctions, especially from car drivers. It is concluded that the perception of blameworthiness in crashes is very much dependent on the details of the crash, with a more specific situation eliciting a fairer evaluation by both car drivers and motorcyclists. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.