Media Logic
In: Journalism quarterly: JQ ; devoted to research in journalism and mass communication, Band 57, Heft 3
ISSN: 0196-3031, 0022-5533
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In: Journalism quarterly: JQ ; devoted to research in journalism and mass communication, Band 57, Heft 3
ISSN: 0196-3031, 0022-5533
In: Journalism quarterly, Band 47, Heft 3, S. 439-449
In: Human factors: the journal of the Human Factors Society, Band 21, Heft 6, S. 635-645
ISSN: 1547-8181
Quasi-static and dynamic pull tests were conducted to measure the maximum forces that adults can voluntarily exert in holding a 7.9 kg infant dummy (age 6 months) in their laps. The results indicate that the forces that lap and shoulder belted adults can exert in holding an infant dummy in their laps are far less than the inertial force that would be exerted by a 7.9 kg infant decelerated at more than 30 Gs. Thus in a motor vehicle frontal barrier crash at 50 km/hr, an infant even when held tightly by a restrained adult would almost certainly strike the dash or windshield. Similarly in airplanes, in crash or turbulence situations, the lap-held infant is likely to hit nearby hard structures. The results clearly demonstrate that it is not safe for infants to be transported in adults' laps in automobiles or airplanes even in the relatively rare instances when they are held tightly and the adults are restrained.
In: Journal of vocational behavior, Band 14, Heft 2, S. 181-189
ISSN: 1095-9084
In: Journal of vocational behavior, Band 12, Heft 2, S. 140-144
ISSN: 1095-9084
In: Human factors: the journal of the Human Factors Society, Band 44, Heft 4, S. 557-568
ISSN: 1547-8181
A new model for predicting automobile driving posture is presented. The model, based on data from a study of 68 men and women in 18 vehicle package and seat conditions, is designed for use in posturing the human figure models that are increasingly used for vehicle interior design. The model uses a series of independent regression models, coupled with data-guided inverse kinematics, to fit a whole-body linkage. An important characteristic of the new model is that it places greatest importance on prediction accuracy for the body locations that are most important for vehicle interior design: eye location and hip location. The model predictions were compared with the driving postures of 120 men and women in five vehicles. Errors in mean eye location predictions in the vehicles were typically less than 10 mm. Prediction errors were largely independent of anthropometric variables and vehicle layout. Although the average posture of a group of people can be predicted accurately, individuals' postures cannot be predicted precisely because of interindividual posture variance that is unrelated to key anthropometric variables. The posture prediction models developed in this research can be applied to posturing computer-rendered human models to improve the accuracy of ergonomic assessments of vehicle interiors.
In: Human factors: the journal of the Human Factors Society, Band 42, Heft 4, S. 541-552
ISSN: 1547-8181
The effects of vehicle package, seat, and anthropometric variables on posture were studied in a laboratory vehicle mockup. Participants (68 men and women) selected their preferred driving postures in 18 combinations of seat height, fore-aft steering wheel position, and seat cushion angle. Two seats differing in stiffness and seat back contour were used in testing. Driving postures were recorded using a sonic digitizer to measure the 3D locations of body landmarks. All test variables had significant independent effects on driving posture. Drivers were found to adapt to changes in the vehicle geometry primarily by changes in limb posture, whereas torso posture remained relatively constant. Stature accounts for most of the anthropometrically related variability in driving posture, and gender differences appear to be explained by body size variation. Large intersubject differences in torso posture, which are fairly stable across different seat and package conditions, are not closely related to standard anthropometric measures. The findings can be used to predict the effects of changes in vehicle and seat design on driving postures for populations with a wide range of anthropometric characteristics.