Basic Study for New Assistive Technology Based on Brain Activity during Car Driving (original) (raw)
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The Relationship between Human Brain Activity and Movement on Car Driving for New Assistive System
2013
Final purpose in this research is to contribute to developing of assistive robot and apparatus. Recently, there is a pressing need to develop a new system which assists and acts for car driving and wheelchair for the elderly as the population grows older. In terms of developing a new system, it is thought that it is important to examine behaviors as well as spatial recognition. Therefore, experiments have been performed for an examination of human spatial perceptions, especially right and left recognition, during car driving using NIRS. In previous research, it has been documented that there were significant differences at dorsolateral prefrontal cortex at left hemisphere during virtual driving task and actual driving. In this paper, brain activity during car driving was measured and detailed analysis was performed by segmentalizing brain activity during car driving on the basis of subjects' motion. So, we report the relationship between brain activity and movement concerned with perception during driving in this paper.
2011 IEEE International Conference on Robotics and Biomimetics, 2011
Final purpose in this research is to contribute to developing of assistive robot and apparatus. Recently, there is a pressing need to develop a new system which assists and acts for car driving and wheelchair for the elderly as the population grows older. In terms of developing a new system, it is thought that it is important to examine behaviors as well as spatial recognition. Therefore, experiments have been performed for an examination of human spatial perceptions, especially right and left recognition, during car driving using NIRS. In previous research, it has been documented that there were significant differences at dorsolateral prefrontal cortex at left hemisphere during virtual driving task and actual driving. In this paper, brain activity during car driving was measured and detailed analysis was performed by segmental brain activity during car driving on the basis of subjects' motion. So, we report the relationship between brain activity and movement concerned with perception during driving in this paper. Keywords-brain information processing during driving task; spatial cognitive task;determining direction; NIRS. I.
Basic Study for Human Spatial Cognition Based on Brain Activity During Car Driving
The purpose in this research is to contribute to developing of assistive robot and related-apparatus. Recently, there is a pressing need to develop a new system which assists and acts for car driving and wheelchair for the elderly as the population grows older. In terms of developing a new system, it is thought that it is important to examine behaviors as well as spatial recognition. Therefore, experiments have been performed for an examination of human spatial perceptions, especially right and left recognition, during car driving using NIRS. In previous research, it has been documented that there were significant differences at dorsolateral prefrontal cortex at left hemisphere during virtual driving task and actual driving. In this paper, brain activity during car driving was measured and detailed analysis was performed by segmentalizing brain activity during car driving on the basis of subjects' motion. So, we report the relationship between brain activity and movement concerned with perception during driving in this paper.
Basic Study of Analysis of Human Brain Activities during Car Driving
Lecture Notes in Computer Science, 2011
Recently, as the worldwide population grows older, it is thought that various assistive systems have soared. It is necessary to discuss functions of humans, spatial perception, decision-making, and determining direction, for developing assistive systems. The final goal of our research is to contribute to developing of welfare robots with functions that are responsive like human. We measured brain activities during virtual car driving using NIRS. As a result of these experiments, there were significant differences at outside frontal cortex in left brain. This go-round, we measured brain activity during actual car driving. In general roads, experiments were performed by taking f-NIRS in the car, and measuring the brain activity when car driven by subjects was went through a number of intersections and road signs. In addition, there was significant difference in common regions. We report a significant association between car driving and brain activity.
BRAIN CONTROLLED CAR FOR DISABLED USING ARTIFICIAL INTELLIGENCE
USING ARTIFICIAL INTELLIGENCE Presented By JAYAKRISHNAN ILLAKIYAN 1. ABSTRACT This paper considers the development of a brain driven car, which would be of great help to the physically disabled people. Since these cars will rely only on what the individual is thinking they will hence not require any physical movement on the part of the individual. The car integrates signals from a variety of sensors like video, weather monitor, anti-collision etc. it also has an automatic navigation system in case of emergency. The car works on the asynchronous mechanism of artificial intelligence. It's a great advance of technology which will make the disabled, abled. In the 40s and 50s, a number of researchers explored the connection between neurology, information theory, and cybernetics. Some of them built machines that used electronic networks to exhibit rudimentary intelligence, such as W. Grey Walter's turtles and the Johns Hopkins Beast. Many of these researchers gathered for meetings of the Teleological Society at Princeton and the Ratio Club in England.
Measurement of Driver ’ s Brain Activity within Truck Driving Simulator Laboratory
Individual human behavior makes a significant impact to the road and traffic safety. The necessity of minimizing the human factor influence is rather obvious. A detailed study of different aspects of human-machine interaction shall make it possible to determine reasons of faulty human behavior and develop methods for its prevention. Complex approach for problem solution is suggested. A truck simulator laboratory described in this article shall suggest wide range of possibilities for the relevant research. Observation of various aspects of faulty driver behavior using different methods, namely combination of brain activity observations (EEG) together with data obtained from readings of other tools such as ocular movements, heartbeat, mimics, muscular activity, gestures, driving behavior and vehicle behavior is to be run for data collection and its further analysis. A set of pilot experiments has been relevant research of both electroencephalographic (EEG) and near infra-red (NIRS) signals analysis of drivers, exposed to influence of various kinds of attention load on adaptive driving simulator is presented. The results are expected to be a basis for recommendation for further deeper and wide scale analyses of various load influences on driver brain.
An Overview of Controlling Vehicle Direction Using Brain Rhythms
2016
In recent years, lot many research activities have taken place in the field of EEG based BCI. Recent experiments have shown that this application finds good potential for disabled people where driving becomes an impossible task. This paper discusses potential of BCI application for controlling vehicle direction, its effectiveness and probable issues. This system works on EEG signals on MATLAB platform. This is implemented by signal acquisition, filtering, feature extraction and their classification on the basis of command given.
2016
Driving requires possessing sufficient cognitive, visual and motor skills and drivers must have adequate motor strength, speed and coordination. Perhaps more importantly, cognitive skills including concentration, attention, adequate visual perceptual skills, insight and memory need to be present. The normal ageing process leads to declines in these motor and cognitive skills, and when combined with a cerebral disease, it may significantly impair the person's driving performance. The objective of this paper is the analysis of driving behaviour of drivers with cognitive impairment due to various brain pathologies, in urban areas, using a driving simulator. An experiment with three assessments for healthy and impaired drivers is carried out: a medical/neurological assessment, a neuropsychological assessment and a driving simulator experiment, in which participants drive in urban area in low and high traffic volumes, and thus, the driving performance of the two driver groups can be ...
Computational intelligent brain computer interaction and its applications on driving cognition
IEEE Computational Intelligence Magazine, 2009
Driving is one of the most common attention-demanding tasks in daily life. Driver's fatigue, drowsiness, inattention, and distraction are reported a major causal factor in many traffic accidents. Due to the drivers lost their attention, they had markedly reduced the perception, recognition and vehicle control abilities. In recent years, many computational intelligent technologies were developed for preventing traffic accidents caused by driver's inattention. Driver's drowsiness and distraction related studies had become a major interest research topic in automotive safety engineering. Many researches had investigated the driving cognition in cognitive neuro-engineering, but how to utilize the main findings of driving-related cognitive researches in traditional cognitive neuroscience and integrate with computational intelligence technologies for augmenting driving performance will become a big challenge in the interdisciplinary research area. For this reason, we attempt to integrate the driving cognition for real life application in this study. The implications of the driving cognition in cognitive neuroscience and computational intelligence for daily applications are also demonstrated through two common attention-related driving studies: (1) cognitive-state monitoring of the driver performing the realistic long-term driving tasks in a simulated realistic-driving environment; and (2) to extract the brain dynamic changes of driver's distraction effect during dual-task driving. Experimental results of these studies provide new insights into the understanding of complex brain functions of participants actively performing ordinary tasks in natural body positions and situations within real operational environments.