Detection Response Task Research Articles

Comparing the Demands of Destination Entry using Google Glass and the Samsung Galaxy S4

A driving simulation study assessed the impact of vocally entering an alpha numeric destination into Google Glass relative to voice and touch-entry methods using a handheld Samsung Galaxy S4 smartphone. Driving performance (standard deviation of lateral lane position and longitudinal velocity) and reaction to a light detection response task (DRT) were recorded for a gender-balanced sample of 24 young adult drivers. Task completion time and subjective workload ratings were also measured. Using Google Glass for destination entry had a statistically higher miss rate than using the Samsung Galaxy S4 voice interface, the Google Glass method took less time to complete, and the two methods were given comparable workload ratings by participants. In agreement with previous work, both voice interfaces performed significantly better than touch entry; this was seen in workload ratings, task duration, lateral lane control, and DRT metrics. Finally, irrespective of device or modality, destination entry significantly decreased responsiveness to events in the forward scene (as measured by the DRT reaction time) as compared to the baseline driving.

Development of the Enhanced Peripheral Detection Task: A Surrogate Test for Driver Distraction

Up to now, there is no standard methodology that addresses how driver distraction is affected by perceptual demand and working memory demand - aside from visual allocation. In 2009, the Peripheral Detection Task (PDT) became a NHTSA recommended measure for driver distraction [1]. Then the PDT task was renamed as the Detection Response Task (DRT) because the International Standards Organization (ISO) has identified this task as a potential method for assessing selective attention in detection of visual, auditory, tactile and haptic events while driving. The is also under consideration for adoption as an ISO standard surrogate test for driver performance for new telematics designs. The State University (WSU) driver imaging group [2, 3] improved the PDT and created the Enhanced Peripheral Detection Task I (EPDT-I) [4]. The EPDT-I is composed of a simple visual event detection task and a video of a real-world driving scene. It is simple, easy to learn and run, and convenient for use in the lab, road, or brain imaging environments [5]. With the success of EPDT-I, the WSU driver imaging group further developed the Enhanced Peripheral Detection Task-II (EPDT-II; also called Wayne State Enhanced DRT or Wayne State EDRT) by adding a number of features to engage participants more with the primary driving task and to assess attentional processes in greater detail. This research also compared performance in the EPDT-II at our lab, EEG, and neuroimaging environments to the open road for validation purposes [6]. In conclusion, the State EDRT provides a sensitive and up-to-date surrogate test for measuring driver distraction in the lab and on the road. Keywords: Driver distraction; Language: en

Detection and recognition masking-level differences for the individual CID W-1 spondaic words.

The detection and recognition masking-level differences for the 36 individual CID W-1 spondaic words (Technisonic Studios) were established on 36 listeners with normal hearing. The masking for two conditions, SoNo and S pi No, was accomplished with 70-dB-SPL speech-spectrum noise. The word lists were administered in 2-dB decrements with the 36 words presented at each signal-to-noise ratio, which ranged from 9 dB to -19 dB for SoNo and from 3 dB to -25 dB for S pi No. The detection and recognition thresholds determined for each spondaic word under both masking conditions are presented. Additionally, the slopes of the psychometric functions for each word under both conditions are given. The mean masking-level difference (SoNo-S pi No) for the detection-response task was 9.4 dB (SD = .7 dB). The mean masking-level difference for the recognition task was 7.2 dB (SD = 1.4 dB). The recognition masking-level differences for the individual spondaic words ranged from 4.4 dB (stairway) to 10.0 dB (oatmeal). A list of 10 words that had the largest masking-level differences for recognition is suggested to enhance the clinical utility of the masking-level difference for speech.