Abstract:
PROBLEM TO BE SOLVED: To provide a method and algorithm for analyzing eye movement data generated by a head and/or eye movement system and outputting characteristic data.SOLUTION: In the method, the eye movement data is processed using a processor by applying classification rules to the data and thereby identifying visual fixations experienced by the subject. Analysis is also made of gaze-direction information associated with the identified fixations thereby developing data representative of directions in which the subject visually fixated during the period of data collection. The data is segregated, based partially on gaze-direction of fixations, into delimited data sets, each delimited data set representing an area/object-of-subject-interest existing during the period of data collection. At least one of the delimited data sets represents a region of typical eyes-forward driving based on a high-density pattern assessed from the collected gaze-direction data. Characteristics of a driver of Percent Road Center (PRC) are calculated based on data representing relative quantification of eyes-forward driving maintained by the driver during a predetermined period.
Abstract:
PROBLEM TO BE SOLVED: To provide a system and a method for monitoring physiological behaviors of a driver in which safety is increased by assisting the driver in situations where drowsiness is caused, attention is decreased and/or high-place work is imposed. SOLUTION: The system and the method for monitoring the physiological behaviors of the driver includes: a step for measuring physiological variables of the driver; a step for assessing a driver's behavioral parameter on the basis of at least measured physiological variable; and a step for informing the driver of the assessed driver's behavioral parameter. The step for measuring the physiological variables can include steps for: measuring a driver's eye movement; measuring a driver's eye-gaze direction; measuring a driver's eye-closure amount; measuring a driver's blinking movement; measuring a driver's head movement; measuring a driver's head position; measuring a driver's head orientation; measuring driver's movable facial features; and measuring a driver's facial temperature image. COPYRIGHT: (C)2011,JPO&INPIT
Abstract:
PROBLEM TO BE SOLVED: To provide a method for presenting comparison measures in assessing driver activity and/or driver condition. SOLUTION: This method includes collecting a stream of gaze-direction data based on a sensed characteristic of a driver, ascertaining a region representative of typical eyes-forward driving based on a high-density pattern determined from the collected gaze-direction data; and utilizing the collected gaze-direction data, in comparison to the ascertained representative region of typical eyes-forward driving, to identify and assess the severity of at least one of the following driver impairment characteristics based on the comparison: (1) cognitive driver distraction, (2) visual driver distraction, and (3) high driver work load. COPYRIGHT: (C)2010,JPO&INPIT
Abstract:
A method of analyzing data based on the physiological orientation of a driver is provided. Data is descriptive of a driver's gaze-direction is processing and criteria defining a location of driver interest is determined. Based on the determined criteria, gaze-direction instances are classified as either on-location or off-location. The classified instances can then be used for further analysis, generally relating to times of elevated driver workload and not driver drowsiness. The classified instances are transformed into one of two binary values (e.g., 1 and 0) representative of whether the respective classified instance is on or off location. The uses of a binary value makes processing and analysis of the data faster and more efficient. Furthermore, classification of at least some of the off-location gaze direction instances can be inferred from the failure to meet the determined criteria for being classified as an on-location driver gaze direction instance.
Abstract:
A method and system for recognizing and/or detecting workload of a person, especially of a driver of a vehicle, by detecting and evaluating head movements of the person is disclosed.
Abstract:
The present invention discloses a method for automated analysis of eye movement data, said method comprising the step of: processing data descriptive of eye movements observed in a subject using a computer-based processor by applying classification rules to the data and thereby identifying at least visual fixations experienced by the subject; and analyzing gaze-direction information associated with the identified fixations thereby developing data representative of directions in which the subject visually fixated during the period of data collection; segregating the developed data, based at least partially on fixation gaze-direction, into delimited data sets, each delimited data set representing an area/object-of-subject-interest existing during the period of data collection and at least one of said delimited data sets representing a region of typical eyes-forward driving based on a high-density pattern assessed from said gaze-direction information; and calculating a percentage road center (PRC) driver characteristic from the developed data representing a relative quantification of driver maintained, eyes-forward driving during a prescribed period of time.
Abstract:
A method and system for recognizing and/or detecting workload of a person, especially of a driver of a vehicle, by detecting and evaluating head movements of the person is disclosed.