AUDITORY REACTION TIME MEASUREMENT WITH OBSERVER-BASED PSYCHOPHYSICAL PROCEDURE

Reaction is defined as a behavioral response to a stimulus. The stimulus can be auditory or visual. Reaction time (RT) is determined as the time between the onset of the stimulus and response. According to this definition, the auditory RT is the time between the auditory stimulus and the response. Simple reaction time has been the subject of comparison of many different groups with both auditory and visual stimuli. When the simple auditory and visual RT in normal hearing individuals are compared, it has been observed that the auditory RT is faster than visual reaction. Auditory RT in womens's was observed slower than men. In many different studies, average values are 180-200 ms for visual RT and 140-160 ms for auditory RT with normal hearing and sighted individuals. Keywords: Reaction Time, Cochlear Implant, Hearing loss

Hearing Reaction Time Measurement Concentration Level Tool Integrated Android Smartphone

Performance in a job is very important because it will have an impact on the assessment and productivity of an employee, one of the indicators for evaluating high performance is related to concentration, execution speed and high productivity of the employee. Concentration is needed in working to prevent fatal accidents. In this study, it is possible to monitor measurement results via a smartphone, namely by using the Bluetooth HC-05 sensor as an integration to a smartphone. With 8 pushbutton, Arduino UNO microncontroller, Bluetooth HC-05, 16x2 LCD, and Buzzer. This tool works alternately when the push button Start is pressed, the power from the power supply will provide an electric current to the microncontroller, and continue to be connected to the Bluetooth HC-05, then by providing pushbuttons pressing input. Each pressing instruction on the pushbutton provides a different sound output, consisting of sound output, High, Mid, and Low. And continue on the LCD, and can display the results of the input that has been processed by the microcontroller. The output results are in the form of the amount of time displayed on the LCD, the sound from the buzzer, and from a series of work tools and the output results can be monitored via android smartphone. The results of this study are the accuracy of the tool in each variable low 99%, mid 90%, high 92%. The average tool ranges from 2.44. The error is low 7,4%, mid 7,4%, high 7,6%.

Development of Standards for Production of an Exit Sign Lighting to Minimize Human Reaction Time - Part I: The Minimum Effective Dimensions

Based on National Fire Safety Codes 303 in Korea, the size of an exit sign lighting to be installed is determined according to space use. Accordingly, a small exit sign lighting can be installed in a large area, which causes problems in the visual recognition of the exit sign lighting by occupants and increases the time required for evacuation. Therefore, in this study, human reaction time measurement experimental tests were conducted in a virtual reality environment to analyze the minimum effective dimension of an exit sign lighting. It was found that the minimum effective dimension of emergency exit sign lighting should be set to a length of 255 mm or more on one side of a 1:1 square display surface.

A-244 Examining the Effects of Computer Operating Configuration on Automated Neuropsychological Assessment Metrics V 4.0 (ANAM4) Reaction Time: A Repeated Measures Approach with Clinical and Research Implications

Objective Computerized cognitive tests are vulnerable to measurement error due to hardware and software configurations of the administration computer. Though automatic score corrections are often provided to account for this, they may mask subtle individual variations in test performance. We investigated the group and individual impact of correcting for measurement error while accounting for possible order effects using data from a larger study of computer platform effects on reaction time measurement. Methods ANAM4 TBI Military’s Simple Reaction Time (SRT) subtest was administered repeatedly on three different computer platforms. We compare two of those platforms: Platform 1, a Dell D630 configured for ANAM4 TBI Military administration; Platform 3, a Dell E6540 with default settings. A mechanical arm with a preset RT was first used to capture measurement error on each platform. SRT was then administered to healthy US Army soldiers in a randomly selected administration order, such that platform 1 was first and platform 3 was third for n = 58 and platform 3 was first and platform 1 second for n = 53. Results Platform 3 was on average 43.06 ms slower than Platform 1. Group analyses suggested applying a 43.06 ms correction to Platform 3 scores resulted in scores similar to Platform 1. However, it appears there were subtle practice and fatigue effects for some individuals that were possibly masked by the score correction. Conclusion Correcting for error due to computer configurations is important in RT measurement, though there may be subtle individual statistical and clinical implications that are lost at a group analysis level.

Work Performance Measurement of Data Entry Employees in E-Commerce Industry Based on Mental Workload Value

This reseach aimed to measure the mental workload of data entry processing tasks in the e-commerce industry based on mental workload value. It was to determine the factors influencing mental workload mainly induced by the data entry process. The experiments without work instruction and with two types of work instruction were conducted to diagnose the mental workload. The measurement of the initial mental workload condition of data entry employees was conducted in the laboratory. Then, the Electroencephalogram (EEG) measurement using sensors from Emotiv was performed every 30 minutes, and the data of EEG measurements (focus, engagement, and stress) were collected using the laptop. Meanwhile, pulse measurement (heart rate) was measured before and after the work. Raw National Aeronautics and Space Administration Task Load Index (NASA-TLX) and reaction time measurement were conducted after the work. Through these experiments, the researchers identify that mental effort and fatigue are the significant determinants of mental workload value in the data entry process of the e-commerce industry. In respect of the results of work performance analysis, it is recommended that the placement of work instruction should be near the employee. Then, the task demand (minimum completion target) should be adjusted according to each employee’s capacity.