The effects of static multiple sources of noise on the visual search component of human inspection

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International Journal of Industrial Ergonomics 34 (2004) 195–207

*Correspondin

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0169-8141/$ - see

doi:10.1016/j.ergo

The effects of static multiple sources of noise on the visualsearch component of human inspection

William Taylora, Brian Melloya, Pallavi Dharwadaa,*,Anand Gramopadhyea, Joe Tolerb

aDepartment of Industrial Engineering, Clemson University, Clemson SC-29634, USAbDepartment of Experimental Statistics, Clemson University, Clemson SC-29634, USA

Received 7 January 2004; received in revised form 12 April 2004; accepted 13 April 2004

Abstract

Visual inspection is a commonly used inspection method, but effects of noise on visual inspection have not been

studied extensively. The objective of this study was to investigate the effects of noise on visual search performance. The

effects of continuous, intermittent, and random noise conditions emitted from single and multiple sources on the

accuracy of an inspector to perform easy and difficult inspection tasks was examined. When compared to the

continuous noise treatment, random and intermittent noise patterns were shown to have negative effects on the easy

search task accuracy. Additionally, the results indicate that single source noise enhances search performance of difficult

tasks. A larger study would likely detect noxious effects of multiple noise sources on difficult search task performance.

Relevance to industry

A thorough understanding of inspection is important for continued quality, reliability and safety in manufacturing,

maintenance, security and other industries. The results of this study can be applied to inspection tasks conducted in

workplace conditions that are similar to those employed in the current study.

r 2004 Elsevier B.V. All rights reserved.

Keywords: Visual search; Noise; Inspection

1. Introduction

As consumers have demanded higher-qualitygoods and litigation related to product liabilityhave increased (Micalizzi and Goldberg, 1989) theimportance of inspection in industry has been

g author.

s: [email protected] (P. Dharwada).

front matter r 2004 Elsevier B.V. All rights reserve

n.2004.04.002

substantiated in recent years. Because of itseconomic importance (Harris and Chaney, 1969),inspection helps to maintain or improve qualityand is prevalent in many types of industry. Eventhough consumers demand defect-free products,the inspection process is not 100% reliable (Druryand Sinclair, 1983). Proper procedures for inspec-tion tasks in industry are drawn from the results ofinspection research.

d.

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W. Taylor et al. / International Journal of Industrial Ergonomics 34 (2004) 195–207196

Visual inspection is one of the most commontypes of inspection, and it is characterized byseveral factors: looking for several targets at once,the search being done in haste, and inaccuracywith the search (Schoonard et al., 1973). Muchresearch has been performed on visual inspectionto understand its many details in order to assistinspectors. There are some important concernsregarding many of these studies. A majority ofthese studies do not take into account the actualenvironments that the inspections take place(Schoonard et al., 1973). That is, importantinfluential factors from the surrounding environ-ment that can affect inspector performance areoverlooked in these studies. An example is themagnitude and sources of ambient noise while aninspection task is being performed (Megaw, 1979).The effects of noise on industrial inspection

have not been studied extensively. Instead, resultsfrom studies that mainly involve vigilance taskshave been extended to predict the results of noiseon inspection. Vigilance tasks have been aprevalent part of the research in psychology forover 50 years, and the association betweenvigilance and inspection models has been exploredfor about as long (Mackworth, 1957; Baker, 1964;Craig, 1983). Measurement, monitoring and scan-ning have all been used in many vigilance tasksthroughout the years. The relationship betweenvigilance and inspection tasks can be perceivedbecause the inspection task itself is characterizedby three main categories; measurement, monitor-ing, and scanning (Harris and Chaney, 1969).Smith (1969) found that inspection tasks aresimilar to vigilance tasks such as monitoring aradar or sonar display. Indeed, due to the commoncharacteristics of these tasks, many investigatorshave extended conclusions about inspection per-formance in noisy environments based on experi-ments with vigilance tasks. For example, it hasbeen shown that loud noise increases the tendencyof an individual to use extreme judgment in thedecision-making process. An individual perform-ing a vigilance task would state that a signal iseither definitely present or definitely not present atthe expense of intermediate categories such aspossibly present or possibly not present (Broad-bent and Gregory, 1965). In a sense, noise

increases the individual’s confidence, which leadsto either more false alarms (saying that a target isnonconforming when it is actually conforming) ormore hits (saying that a product is conformingwhen it is actually nonconforming). Other vigi-lance studies have shown that performance atnoise levels of 80 dBA results in more errors ofomission (Jones et al., 1979). These are but a fewof numerous such cases in the literature. Yetdespite the similarities of inspection and vigilancetasks, the differences that exist between them areof unknown consequence. Hence, the extent towhich the results from vigilance studies may beapplied to inspection tasks is unclear.There are, however, a smaller number of studies

that have specifically investigated the effects ofnoise on performance in an inspection task. Ehlers(1972) evaluated the effects of noise on a circuitboard inspection task with varying levels of noiseand reported a decrease in inspector accuracy at90 dBA. Another study was performed to deter-mine the effects of continuous, periodic, andrandom noise on an industrial inspection task(Fornwalt, 1970). Results of this study showedhigher errors for continuous and random noisethan for periodic noise, but there was no effect ofthe different noise levels on errors. A decrease inerrors was reported by Broadbent and Little(1960) when noise levels in a factory weredecreased from 98 to 90 dB. These studies supportthe hypothesis that noise affects inspection per-formance, but the scope of the information islimited. The appendix shows a review of literatureon studies of the effects of noise which demon-strate that noise has had positive, negative, ornegligible effects on human performance.Noise can have various effects on performance,

but the effects are dependant on the task and theconditions present during inspection (Broadbent,1971). Noise in industry may be generated frommany sources and locations and occur at unknowntimes, but this important aspect of noise oninspection performance has been neglected inprevious research. Most studies have relied on asingle source (headphones or a single loudspeaker)to administer the noise treatments to the subjects.However, a study by Becker et al. (1995) showedthat noise administered with a Doppler-like effect

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W. Taylor et al. / International Journal of Industrial Ergonomics 34 (2004) 195–207 197

(moving airplane) had a degrading effect onperformance. These results suggest that exposureto multiple noise sources may be detrimental toinspection performance. The effects of differentintermittencies of noise randomly emitted fromsources in more than one location have not beencompared to the effects of different noise patternsadministered from a single source.Research on noise localization would provide

valuable information about the effect of noise onhuman performance in an inspection task. Broad-bent (1979) conjectured that uncertain localizationof noise sources invokes a sense of curiosity orinsecurity in human subjects. How does thecuriosity of attempting to identify ‘where’ a noisecame from cause a decrement in performance? Ithas been proposed that the auditory systempossesses mechanisms that identify both ‘‘what’’and ‘‘where’’ (Romanski, 1999). The additionalprocessing resources needed for the auditorysystem to identify both ‘‘what’’ and ‘‘where’’ whenexposed to multiple sources of noise perhaps causeinspection performance to suffer. This assumptionis based on a resource view of attention theory(Lintern and Wickens, 1987). That is, as taskdemands become greater, more processing re-sources are needed in order to maintain perfor-mance levels.An experiment was conducted in which subjects

were exposed to random, intermittent, and con-tinuous noise from single and multiple sourceswhile performing a simulated visual search task.The focus of this study was to investigate theeffects of noise on the visual search aspect of theinspection process. Visual search is the first step ofthe inspection process in which an inspector mustlocate a defect or target item and is the prominentcomponent in aircraft inspections and othersimilar inspection processes (Melloy et al., 2000).

Fig. 1. Layout of speaker positioning.

2. Methodology

2.1. Subjects

Fifteen subjects ranging from 21 to 28 years ofage were randomly selected from a population ofgraduate and undergraduate students in the

Industrial Engineering Program at Clemson Uni-versity. Students were used as subjects in thisexperiment as Gallwey and Drury (1986) haveshown that minimal differences exist betweeninspectors and student subjects on simulated tasks.A questionnaire was used to document that thesubjects had 20/20 vision and no hearing impair-ments.

2.2. Equipment

The equipment used for the experiment includeda 2000 Gateway personal computer with Windows2000 operating system and an Intel Pentium threeprocessor. The monitor provided a viewing area of17 in at a resolution of 800� 600 pixels. Thesubjects observed the screen from an approximatedistance of 20 in and used a mouse to make allresponses. The subjects were not allowed to use themouse as a scanning tool.

2.3. Noise stimulus

The noise stimulus was created by repeatedlytapping a hammer on a piece of aluminum andrecorded using an Olympus digital recorder.Intermittent noise (IN), continuous noise (CN),and random noise (RN) patterns were createdusing Goldwave noise editing software. The noisetreatments were administered to the subjects usingLenoxx Sound Model 109 Compact Disc Playerspositioned 7 ft from the subject (as shown inFig. 1). Three speakers were used for the multiplesource (MS) noise treatments, while only the rearspeaker was used for the single source (SS) noise

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Fig. 2. Sample cumulative inspection time distribution.


treatments. For the MS noise treatments, noisewas emitted from each of the speakers but atdifferent times. The noise intensity for MS and SStreatments was controlled at 8072 dBA using anExtech Model 407735 digital sound level meter.The no-noise (NN) treatment was administeredwith ambient room noise of 4072 dBA.

2.4. Inspection task

An inspection task was simulated using a visualsearch program constructed in Visual Basic 5.0. Aseries of screens were presented with eight ASCIIbackground characters (W, M, N, A, B, R, K, andZ) randomly generated for each noise treatment.Among the background characters there was an‘‘X’’ target (easy search), a ‘‘V’’ target (difficultsearch), or no. The ‘‘X’’ and ‘‘V’’ targetsrepresented defects. The ‘‘V’’ character has beenshown to be difficult to detect in a visual searchtask (Megaw and Richardson, 1978). Past litera-ture has shown that searching for multiple faultsis as accurate as searching for single faults(Matthews, 1986).

2.5. Experimental design

The experiment was performed using an 8� 8diagram-balanced Latin Square Design with sub-ject and time as blocking factors. The twotreatment factors, noise source and noise pattern,were examined in this study. The noise sourcefactor consisted of two levels: SS (one speaker) andMS (three speakers). The noise pattern factorconsisted of three levels: IN, CN, and RNpatterns. The six combinations of noise sourceand noise pattern plus two NN treatmentsprovided the eight treatments used in this study.Each of the eight subjects completed eight trials,one for each of the treatments. Each trial consistedof 50 screens: 20 with an ‘‘X’’ defect (easy search),20 with a ‘‘V’’ defect (difficult search), and 10 withno defect.

2.6. Subject calibration

Since a baseline accuracy of 80–90% for theeasy search was desired, each subject was cali-

brated before participating in the experiment. Theprocess consisted of determining a pacing time foreach subject to ensure that each subject’s ‘‘X’’accuracy was within the prescribed range. Themethod for calibrating pacing time was similar tothe approach used by Garret et al. (2001). Eachsubject performed an un-paced trial consisting of50 screens (20 with an ‘‘X’’ defect, 20 with a ‘‘V’’defect, and 10 with no defect). The 15% back-ground density used for each screen was deter-mined from a pilot study. The results from eachsubject were used to prepare a cumulative inspec-tion time distribution curve (Fig. 2). The meaninspection time was used to find the correspondingpercentage on the curve. The cumulative percen-tage for the mean inspection time of a subject wasdivided into four quartiles, and the correspondinginspection time was determined for each quartile(IT1, IT2, and IT3). Subjects were re-tested usingtheir specific value for IT2 as the pacing time. If asubject performed in the 80–95% range for ‘‘X’’accuracy, IT2 was used for the experiment.However, subjects performing above or belowthe prescribed range were tested again using eitherIT1 or IT3 values. The calibration was performedto reduce variability among subjects.

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2.7. Procedure

The study was conducted over a 3-day periodwith day 1 used for training and calibration.The subjects were given an explanation of thestudy, a consent form to sign, and a questionn-aire for obtaining demographic information.The subjects were permitted to familiarizethemselves with the simulator, but no feedbackor feed forward information was provided. Thesubjects were read the experimental protocol andpresented with four trials (two in the morning andtwo in the afternoon) on days 2 and 3. Uponcompletion of the study, the subjects weredebriefed.

3. Results

Inspection accuracies were based on thepercentage of defects detected out of the totalnumber of defects presented. The mean percen-tages of ‘‘X’’ (easy) and ‘‘V’’ (difficult) targetsdetected for each noise treatment are givenin Table 1. The data obtained were checkedfor normality and it was found to be homo-genous. An analysis of variance (ANOVA)was performed for easy and difficult searchtasks using SASs, and there was insufficientevidence of carry-over effects (data not shown).The Linear contrasts were used to examinefactorial effects and perform single degree-of-freedom comparisons.

Table 1

Effects of noise treatments on percent correct detection for easy

and difficult search tasks

Noise treatment Search task (%)

Easy (‘‘X’’) Difficult (‘‘V’’)

No noise 84.1 (13) 31.9 (15)

Intermittent, single source 81.3 (10) 37.5 (13)

Random, single source 83.1 (6) 40.6 (15)

Continuous, single source 86.9 (15) 38.8 (18)

Intermittent, multiple source 85.6 (11) 34.4 (18)

Random, multiple source 80.0 (13) 32.5 (18)

Continuous, multiple source 88.1 (13) 35.0 (14)

3.1. Easy search

There was insufficient evidence of interactionbetween noise type and noise source or a maineffect of noise source for the easy search task(Table 2). However, the inspection accuracy ofsubjects exposed to random or intermittent noisepatterns was lower than for continuous noiseconditions (P ¼ 0:046). No other differences weredetected for the easy search task.

3.2. Difficult search

There was insufficient evidence of interaction ormain effects for noise type and noise source oninspection performance for the difficult search task(Table 2). Search accuracy of the subjects wasgreater when exposed to SS noise than for the NNcondition (P ¼ 0:045), while results for MS noiseand NN conditions were comparable. No otherdifferences were detected for the difficult searchtask.

4. Discussion

The primary research hypothesis of this studywas that multiple sources of noise would nega-tively affect the visual search component of adifficult inspection task. The experimental resultsindicate some effects of noise on inspectionperformance but do not strongly support thehypothesis that multiple sources of noise have adetrimental effect on inspection performance. Asexpected, results for the easy search task (‘‘X’’accuracy) showed little effects due to noise. Thiscan be explained using a resource theory approach(Lintern and Wickens, 1987). An individual has alimited amount of processing resources to allocateamong perceptual and cognitive systems whenperforming an action. As the task becomes moredemanding, the amount of resources required bythe various systems to maintain performanceincreases. When the amount of resources requiredis greater than the amount of resources anindividual has to allocate, performance will suffer.Since the subjects maintained performance for theeasy search task when subjected to either single or

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Table 2

Summary ANOVA table with single degree-of-freedom comparisons for easy and difficult search tasks

Source of variationa df Search task—P-value

Easy (‘‘X’’) Difficult (‘‘V’’)

NN vs. SS 1 0.903 0.045

NN vs. MS 1 0.840 0.547

Source (SS vs. MS) 1 0.717 0.111

Type (2)

RN and IN vs. CN 1 0.046 0.849

RN vs. IN 1 0.507 0.869

Type� source (2)

(RN and IN vs. CN)� source 1 0.898 0.775

(RN vs. IN)� source 1 0.188 0.510

aNN=no noise, SS=single source, MS=multiple source, RN=random noise, IN=intermittent noise, and CN=continuous noise.


multiple noise sources, it can be concluded that theadditional demands from the noise treatments onthe subjects’ limited resource pool were within thepool’s capacity. That is, the processing resourcesneeded to examine incoming stimuli from auditorychannels was not great enough to detract from theprocessing resources being used by the perceptualand cognitive systems for analyzing incomingstimuli from visual channels.For the easy search task, random and inter-

mittent noise treatments had lower accuracies thancontinuous noise treatments. Many studies in thepast have also shown that intermittent noisecaused a decline in performance (Eschenbrenner,1971; Carter and Beh, 1987). The distractiontheory proposed by Broadbent (1957, 1982) offersone explanation for this result. The distractiontheory, like the resource theory, is based on alimited capacity resource system. However, thedistraction theory focuses primarily on resourceswithin the perceptual system. Using this frame-work of resource theory and distraction theory, itis hypothesized that new incoming stimuli fromauditory channels causes ‘‘blinks’’ in processingincoming visual stimuli. The ‘‘blinks’’ occurbecause visual information is lost as new auditorystimuli briefly compete for control of resourcesallocated within the perceptual system (Broadbent,1958). Random or intermittent noise treatmentswould likely cause ‘‘blinks’’ and result in greaterloss of incoming data than continuous noiseconditions. According to Teichner et al. (1963),

continuous noise may be habituated and therebyreduce its effect on incoming visual stimuli.The results of the difficult search task were very

surprising. It was hypothesized that multiplesources of noise would reduce inspectors’ perfor-mance compared to a single noise source; however,this result was not detected (P ¼ 0:111) due to thelimited sample size available for this study (Table2). Averaged over types of noise, ‘‘V’’ accuracywas 39% for SS noise compared to only 34% forMS noise (Table 1).The most interesting result for the difficult

search task was that higher accuracies wereobtained for single source noise treatmentsthan for the no noise treatment (Table 2).Based on resource theory, the combination of amore demanding task and noise treatmentsshould produce lower accuracy than performingthe task without noise. However, the experimentalresults show that performance levels were main-tained or even increased for some noise treatments.This suggests that noise treatments did notaffect the processing resources required by thedifficult search task. Previous studies ofdifficult tasks have reported a linear relationshipbetween performance and resources (Normanand Bobrow, 1975; Wickens, 1992) indicatingthat resource limitations exist for all perfor-mance levels. These results suggest that subjectsperforming a difficult search task will not haveadditional resources available for processing audi-tory noise stimuli. Therefore, the enhanced

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performance that occurred with the single sourcenoise must have been the result of some othermechanism.The arousal theory proposed by Broadbent

(1971) suggests that noise can be an arousal agent.Broadbent’s arousal theory is based on theYerkes–Dodson law of arousal and performance(Yerkes and Dodson, 1908). If arousal levels areplotted against performance, the graph willresemble an inverted ‘‘U’’. As arousal increases,so will performance. Arousal is said to increaseconcentration on some inputs to the detrimentof others (Broadbent, 1971). It has been hypothe-sized that arousal is related to attentional selectiv-ity; and, as the state of arousal increases, thefocus (spotlight) of attention becomes narrower(Matthews et al., 2000). At some point over-arousal occurs which leads to a decline inperformance as the attentional focus becomestoo narrow.A graph of the results for the difficult search

roughly resembles an inverted ‘‘U’’, thus thearousal theory may help explain results for thedifficult search task (Fig. 3). Since subjects wereresource limited, it can be assumed that positiveincreases in performance were the result of shiftingavailable processing resources. It is hypothesizedthat when single source noise stimuli are intro-duced, subjects shift their attention to the visualsearch task and attempt to block out noise. Thatis, resources being used to process incomingauditory stimuli are reallocated to sections of theperceptual and cognitive systems devoted to

Fig. 3. Graph of experimental data for difficult search.

performing the visual search task. The shift ofresources increases the focus of attention on thesearch task and results in enhanced visual searchperformance.However, the additional strain of managing the

‘‘what’’ and ‘‘where’’ properties of multiple-sourcenoise treatments results in over-arousal. Thesubjects try harder to shift attention away fromadditional incoming auditory stimuli and to thevisual search task. Their focus of attentionnarrows to the point of excluding relevant stimuliand performance declines.The results of this study provide additional

information about the effects of noise on humanperformance in visual search tasks. An importantcaveat though is that these results may only berelevant to similar studies or conditions. Broad-bent (1971) stated that there are indeed noiseeffects on performance, but these effects dependon the type of task as well as the type of noise.With this in mind, an important result of this studyis that visual search performance for an easy taskis similar for multiple and single sources of noise atthe 80 dBA level. Results were not as conclusivefor the difficult search task, and additionalinformation would likely indicate deleteriouseffects of multiple noise sources on search perfor-mance.Several recommendations for visual inspection

in industries with noisy working environments canbe made from these results. First, for noise levelsof 80 dBA and below, the results of this studysuggest that there are no detrimental effects ofnoise on accuracy of easy visual search processes.The introduction of noise from more than onesource should not negatively affect inspectors’visual search performance as long as the combinednoise level does not exceed 80 dBA. In fact,moderate levels of single source noise may increaseinspectors’ performance for difficult search tasks.Second, intermittent and random noise patternsemitted from either single or multiple sources inthe workplace may distract inspectors conductingeasy visual search tasks. One final caveat is thattest power for detecting detrimental effects ofmultiple sources of noise on the difficult visualsearch task was compromised due to limitedsample size.

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5. Conclusions

This study investigated the effects of noise onthe visual search component of a visual inspectionprocess. The results from this study suggest thatneither multiple or single sources of noise affectinspector performance on easy or difficult visualsearch tasks at the noise level tested (80 dBA). Infact, the results suggest some performance benefitsfrom a single noise source during a difficult search

Table 3

Researcher (year) Noise stimulus Theory

Cassel and Dallenbach (1918) Hammer and bell noise Distrac

Harmon (1933) 50–65dB office sounds,

65–75dB traffic sounds

Not spe

Broadbent (1952) 70 and 100 dB Distrac

theory

Broussard et al. (1952) 45 and 90 dB tank noise None

Jerison (1954) 110 dB white noise and

relative quiet

None

Broadbent (1954) 70 and 100 dB Distrac

Jerison (1957) Noise and quiet Attentio

Broadbent (1958) High/low freq. at 80, 90,

100 dBA

Distrac

theory

Jerison (1959) 83 and 114 dB Arousa

Teichner et al. (1963) 57, 69, 81, and 93 dB Distrac

habitua

arousal

Corcoran (1962) 90 white dB noise Arousa

Park and Payne (1962) 98 and 108 dB noise Not spe

Wilkinson (1963) 100 dB white noise Arousa

Watkins (1964) 75 dB Not spe

Fornwalt (1970) 7, 80 and 94 dBA cont.

periodic and random noise

Tempor

conditio

Davies and Hockey (1966) 70 and 95 dB noise Arousa

Eldredge and Busch (1967) Speech and white noise at

78 dB

Filter th

Boggs and Simon (1968) 0.5 s bursts of bandsaw

noise, quiet, 92

Filter th

Houston (1968) 78 dB noise Arousa

inhibito

process

Hockey (1970) 70 and 100 dB noise Arousa

selectivi

task. For the easy search task, reduced perfor-mance was detected for the random and inter-mittent noise patterns compared to a continuousnoise condition.

Appendix A. Past studies involving noise

A review of literature on studies of the effects ofnoise on human performance is given in Table 3.

Single or

multiple

source

Effects Task type

tion Single Positive and

negative

n/a

cified Single Positive Reading,

mental vigilance

tion-filter Single Negative Vigilance

Single Negative Tracking, visual

contrast task

Single Negative Vigilance/count

tion Single Negative Vigilance

n shifting Single None Vigilance

tion-filter Single Negative Vigilance

l Single Negative Vigilance

tion,

tion and

Single None Vigilance tasks

l Single Positive Vigilance

cified Single None Cognitive

vigilance

l Single Negative Vigilance

cified Single Positive Visual signal

detection

al

ning

Single Negative Inspection

l Single Positive Vigilance

eory Single Negative Recall

eory Single Negative Response

time/auditory

vigilance

l and

ry

es

Single Positive Scan and

vigilance task

l and

ty

Single Positive and

negative

Vigilance

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Table 3 (continued)

Researcher (year) Noise stimulus Theory Single or

multiple

source

Effects Task type

Warner and Heimstra (1971) Four inter. Noise ratios Arousal–

distraction

Single Negative and

positive

Vigilance

Eschenbrenner (1971) Aperiodic, periodic and

cont. noise at 50, 70, 90 dB

Not specified Single Negative Manual image

motion comp.

C. Stanley Harris (1972) Cont. Inter. Does not agree

with filter theory

Single Negative Serial search

Ehlers (1972) 0, 70, 90 dBA Arousal–

distraction

Single Negative Inspection

S.S. Stevens (1972) 90, and 115 dB None given Single Negative Vigilance type

task

Warner and Heimstra (1972) Low volume continuous

white noise

Not specified Single Positive and

negative

Target search

Hockey (1973) 70 and 100 dBA Arousal Single Negative Vigilance

Basow (1973) 100 dB cont. white noise Arousal Single None Selective,

scanning and

focusing

Poulton and Edwards (1974) 102 dB low-freq. noise Arousal Double Positive Vigilance task

Simpson et al. (1974) 50 and 80 dBA noise None given Single Negative Tracking

Theologus et al. (1974) 85 dB random and

intermittent noise

Stress Single Positive and

no effects

Vigilance and

response tasks

Epp and Konz (1975) Various home appliances

noises 64–95dBA

None given Single Negative Rating

Edsell (1976) 61 and 75 dBA inter. noise

and 51 dBA quiet noise

Arousal Single Negative Serial recall

Wolwill et al. (1976) 80–85dBA white noise Distraction Multiple None Vigilance

Kallman and Issac (1977) 69 dBA and 39–41dBA Arousal Single Positive Response time

Kyriakides and Leventhall

(1977)

70 and 90 dBA None given Single Negative Vigilance

Hamilton et al. (1977) 85 dBA and ambient State selection Single Positive Cognitive

vigilance,

guessing

Bachman (1977) 105 dB — — None —

Loeb and Jones (1978) 75 dBA, 136 dB (SPL), and

105dBA

Against masking Single Negative —

Forster and Grieson (1978) 70 and 92 dBA Arousal Single Negative Recall

Finkelman et al. (1979) 0 and 90 dB white noise

burst

Arousal Single Negative Recall

Holding et al. (1979) 45 and 90 dBA Unspecified Single Positive Cognitive

vigilance

arithmetic task

Clevenson and Leatherwood

(1979)

68–86dBA heli noise Not specified Multiple Negative Listening recall

Arnoult and Voorhees (1980) Helicopter noise Not specified Single Negative Audio visual

task

Smith et al. (1981) 55 and 80–85 dBC Strategy Single Negative Recall

Smith et al. (1981) 80 dBC and quiet Strategy Single None and

negative

Recall tasks

Smith et al. (1981) 55 and 85 dBC Strategy Single None Recall tasks

Gawron (1982) 55, 70, and 85 dBA broad

band white noise

Not specified Multiple 3

sources

emitting same

noise

Positive and

negative

Digit canceling/

vigilance type

task


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Table 3 (continued)

Researcher (year) Noise stimulus Theory Single or

multiple

source

Effects Task type

Milosevic (1983) 70 and 100 dB cont. noise Arousal Single None Vigilance

Smith (1983a,b) 55 and 85 dBC Selection and

strategy

Single Negative and

positive

Recall

Smith (1983a,b) 60 and 85 dBC Strategy Single Positive and

negative

Recall

Lysaght et al. (1984) Broadband noise and glass

and singer noise, office and

speech noise, and quiet

Unspecified Single Positive and

negative

Vigilance

Noonan et al. (1984) Quiet and 70 dB white noise Unspecified Single Positive Vigilance

Noweir (1984) 80–99dBA of various

industrial noise

Unspecified Single Negative Textile work

vigilance-type

task

Smith (1985) 60 and 85 dBC Against masking Single Positive Vigilance

Smith (1985) 60 and 80 dBC Selective attention

and strategy

Single Negative Vigilance

Smith and Miles (1986) 40 and 75 dBA Arousal Single Negative Vigilance

Smith (1985) 60 and 85 dBC Selective attention Single Positive and

negative

Recall tasks

Smith and Stansfield (1986) Aircraft noise Selection — Negative Vigilance

Smith and Miles (1986) 40 and 75 dBA Arousal Single Negative Vigilance

Carter and Beh (1987) 92 dBA intermittent noise Strategy Single Negative Vigilance

Baker and Holding (1987) 55–95dBA Arousal Single Positive and

negative

Arithmetic

Smith and Miles (1986) 40 and 75 dBA Distraction Single Negative Search task

Smith (1988) 55 and 85 dBA Unspecified Single Negative Cognitive

vigilance

Dornic and Laaksonen (1989) Cont. inter. and random Unspecified Single Negative Rating

Levy-Leboyer (1989) 65, 75, and 90 dBA Information

processing

Single Negative Assembly of car

carburetor and

air conditioner

Zhand and Wickens (1990) 44 and 88 dB heli. noise Distraction Single None Vigilance/visual

search

Smith (1991) 50 and 78 dBA Selective attention Single Negative Search

Yoshida (1991) 42–45dBA background,

50–80dBA broadband, and

60–80dBA road noise

Arousal — Positive and

negative

Choice reaction

time and figure

counting task

Baker and Holding (1993) 55 dBA ambient, 90 dB

white, 90 dBA machine

noise, 85 dBA speech, and

85 dBA normal

Unspecified Single Positive and

negative

Cognitive tasks

Becker et al. (1995) 70 and 95 dBA aircraft

noise

Information

processing

Multiple Negative Vigilance task

Kjellburg et al. (1996) Office, lab and industry

noise o85 dBA

Unspecified — Negative Industrial office

and lab work

Hygge and Kenz (2001) 38 and 58 dBA Speed accuracy

tradeoff

hypothesis

Single Positive Memory load

search task

Belojevic et al. (2001) 42 dBA quiet and 88 dBA

traffic noise

Annoyance Single None Arithmetic task

Lavine et al. (2002) 50 dBA noise 90 dBA inter.

and rand. noise

Alertness

(arousal?)

Dual Positive Vigilance


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References

Arnoult, M.D., Voorhees, J.W., 1980. Effects of aircraft noise

on an intelligibility task. Human Factors 22 (2), 183–188.

Bachman, J.C., 1977. The effect of non traumatic audible stress

on learning of two motor skills. Journal of Motor Behavior

9, 243–245.

Baker, C.H., 1964. Industrial Inspection Considered as a

Vigilance Task. Human Factors Inc., Goleta.

Baker, M.A., Holding, D.H., 1987. Towards meaningful

noise research. The Journal of General Psychology 114

(4), 395–410.

Baker, M.A., Holding, D.H., 1993. The effects of noise and

speech on cognitive task performance. The Journal of

General Psychology 120 (3), 339–355.

Basow, S.A., 1973. The effect of white noise on physiological

arousal and attention as a function of manifest anxiety.

Doctoral Dissertation, Brandeis University, Abstracts

International, 386-B.

Becker, A.B., Warm, J.S., Dember, W.N., 1995. Effects of jet

engine noise and performance feedback on perceived

workload in a monitoring task. The International Journal

of Aviation Psychology 5 (1), 49–62.

Belojevic, G., Slepcevic, V., Jakovlevic, B., 2001. Mental

performance in noise: the role of introversion. Journal of

Environmental Psychology 21, 209–213.

Boggs, D.H., Simon, J.R., 1968. Differential effect of noise on

tasks of varying complexity. Journal of Applied Psychology

52 (2), 148–153.

Broadbent, D.E., 1952. Noise, paced performance and

vigilance tasks. British Journal of Psychology XLIV (4),

295–303.

Broadbent, D.E., 1954. Some effects of noise on visual

performance. The Quarterly Journal of Experimental

Psychology 6, 1–5.

Broadbent, D.E., 1957. Effects of noises of high and low

frequency on behavior. Ergonomics 1, 21–29.

Broadbent, D.E., 1958. Perception and Communications.

Pergamon, London.

Broadbent, D.E., 1971. Decision and Stress. Academic Press,

London.

Broadbent, D.E., 1979. Human performance and noise. In:

Harris, C.M. (Ed.), Handbook of Noise Control. McGraw-

Hill, New York, pp. 2066–2085.

Broadbent, D.E., 1982. Task combination and the selective

intake of information. Acta Psychologica 50, 253–290.

Broadbent, D.E., Gregory, M., 1965. Effects of noise and signal

rate upon vigilance analyzed by means of decision theory.

Human Factors 7, 155–162.

Broadbent, D.E., Little, E.A., 1960. Effects of noise reduction

in a work situation. Occupational Psychology 34, 133–140.

Broussard, I.G., Walker, R.Y., Roberts, E.E., 1952. Influence

of noise on the visual contrast threshold. Report USAMRL-

101, Army Medical Research Laboratory, Fort Knox, KY.

Carter, N.L., Beh, H.C., 1987. The effect of intermittent noise

on vigilance performance. Journal of the Acoustical Society

of America 82 (4), 1334–1341.

Cassel, E.E., Dallenbach, K.M., 1918. The effect of auditory

distraction upon the sensory reaction. The American

Journal of Psychology XXIX (2), 129–142.

Clevenson, S.A., Leatherwood, J.D., 1979. Effect of Noise

Spectra and a Listening Task upon Passenger Annoyance in

a Helicopter Interior Noise Environment. NASA Technical

Paper 1590, December 1979.

Corcoran, D.W.J., 1962. Noise and loss of sleep. Quarterly

Journal of Experimental Psychology 14, 178–182.

Craig, A., 1983. Vigilance and inspection. Studia Psychologica

25, 259–270.

Davies, D.R., Hockey, G.R.J., 1966. The effects of noise and

doubling the signal frequency on individual differences in

visual vigilance performance. British Journal of Psychology

57 (3,4), 381–389.

Dornic, S., Laaksonen, T., 1989. Continuous noise, intermittent

noise and annoyance. Perceptual and Motor Skills 68,

11–18.

Drury, C.G., Sinclair, M.A., 1983. Human and machine

performance in an inspection task. Human Factors 25,

391–399.

Edsell, R.D., 1976. Noise and social interaction as simultaneous

stressors. Perceptual and Motor Skills 42, 1123–1129.

Ehlers, H.W., 1972. Effects of Low Frequency Continuous

Noise on an Inspection Task. Army Material Command.

Eldredge, D., Busch, A.C., 1967. Proactive inhibition, recency,

and limited channel capacity under acoustic stress. Percep-

tual and Motor Skills 25, 85–91.

Epp, S., Konz, S., 1975. Home appliance noise: annoyance and

speech interference. Home Economics Research Journal 3

(3), 205–209.

Eschenbrenner, J.A., 1971. Effects of intermittent noise on the

performance of a complex psychomotor task. Human

Factors 13 (1), 59–63.

Finkelman, M., Zeitlin, L.R., Romoff, R.A., Riend, M.,

Brown, L.S., 1979. Conjoint effect of physical stress and

noise stress on information processing performance and

cardiac response. Human Factors 21 (1), 1–6.

Fornwalt, N.E., 1970. Investigation into the effect of inter-

mittent noise of constant periodicity vs. random periodicity

on the performance of an industrial task. Masters Thesis,

Texas Technological College.

Forster, P.M., Grieson, T., 1978. Noise and attentional

selectivity: a reproducible phenomenon. British Journal of


Gallwey, T.J., Drury, C.G., 1986. Task complexity in visual

inspection. Human Factors 28 (5), 595–606.

Garret, S.K., Melloy, B.J., Gramopadhye, A.K., 2001. The

effects of per lot and per item pacing on inspection

performance. International Journal of Industrial Ergo-

nomics 27, 291–302.

Gawron, V.J., 1982. Performance effects of noise intensity.

Psychological set, and task type complexity. Human Factors

24 (2), 225–243.

Hamilton, P., Hockey, B., Rejman, M., 1977. The place of the

concept of activation in human information processing

theory: an integrative approach. In: Dornic, S., (Ed.),

ARTICLE IN PRESS


Attention and Performance, Vol. IV, Erlbaum, Hillsdale,

NY, pp. 463–485.

Harmon, F.L., 1933. The effects of noise upon certain

psychological and physiological processes. Archives of

Psychology 147, 81.

Harris, D.H., Chaney, F.D., 1969. Human Factors in Quality

Assurance. Wiley, New York.

Harris, C.S., 1972. Effects of intermittent and continuous noise

on serial search performance. Perceptual and Motor Skills

35, 627–634.

Hockey, G.R.J., 1970. Effect of loud noise on attentional

selectivity. Quarterly Journal of Experimental Psychology

22, 28–36.

Hockey, R., 1973. Changes in information-selection patterns

in multisource monitoring as a function of induced

arousal shifts. Journal of Experimental Psychology 101

(1), 35–42.

Holding, D.H., Baker, M.A., Loeb, M., 1979. Noise, time of

day, and unpaced arithmetic. Paper presented at the

Psychonomics Society Annual Meeting, Phoenix.

Houston, K.B., 1968. Inhibition and the facilitating effect of

noise on interference tasks. Perceptual and Motor Skills 27,

947–950.

Hygge, S., Knez, I., 2001. Effects of noise, heat, and indoor

lighting on cognitive performance and self-reported affect.

Journal of Environmental Psychology 21, 291–299.

Jerison, H.J., 1954. Paced Performance on a Complex Counting

Task under Noise and Fatigue Conditions. Aero Medical

Library, Wright Patterson AFB.

Jerison, H.J., 1957. Performance on a simple vigilance task in

noise and quiet. Journal of the Acoustical Society of

America 29 (11), 1163–1165.

Jerison, H.J., 1959. Effects of noise on human performance.

Journal of Applied Psychology 45 (2), 96–101.

Jones, D.M., Smith, A.P., Broadbent, D.E., 1979. Effects of

moderate intensity noise on the Bakan vigilance task.

Journal of Applied Psychology 64, 627–634.

Kallman, W.C., Issac, W., 1977. Altering arousal in humans by

varying ambient sensory conditions. Perceptual Motor

Skills 44, 19–22.

Kjellburg, A., Landstrom, U., Tesarz, M., Soderberg, L.,

Akerlund, E., 1996. The effects of nonphysical noise

characteristics, ongoing task and noise sensitivity on

annoyance and distraction due to noise at work. Journal

of Environmental Psychology 16, 123–136.

Kyriakides, K., Leventhal, H.G., 1977. Some effects of

infrasound on task performance. Journal of Sound and

Vibration 50 (3), 369–388.

Lavine, R.A., Sibert, J.L., Gokturk, M., Dickens, B., 2002. Eye

tracking measures and human performance in a vigilance

task. Aviation Space and Environmental Medicine 73 (4),

367–372.

Levy-Leboyer, C., 1989. Noise effects on two individual tasks.

Work and Stress 3 (4), 315–322.

Lintern, G., Wickens, C.D., 1987. Attention theory as a basis

for training research. Aviation Research Laboratory Tech-

nical Report ARL-87-2 / NASA-87-3, University of Illinois.

Loeb, M., Jones, P.D., 1978. Noise exposure, monitoring and

tracking performance as a function of signal bias and task

priority. Ergonomics 21 (4), 265–272.

Lysaght, R.J., Warm, J.S., Dember, W.H., 1984. Effects of

noise and information processing demand on vigilance

performance in men and women. Trends in Ergonomics/

Human Factors I, 27–32.

Mackworth, N.H., 1957. Vigilance. The Advancement of

Science 53, 389–393.

Matthews, M.L., 1986. Visual quality control inspection with

multiple product faults. In: Karwoski, W. (Ed.), Trends in

Ergonomics/Human Factors, Vol. III, North-Holland,

Amsterdam.

Matthews, G., Davies, D.R., Westerman, S.J., Stammers, R.,

2000. Human Performance: Cognition, Stress, and Indivi-

dual Differences. Psychology Press, Hove.

Megaw, E.D., 1979. Factors affecting visual inspection

accuracy. Applied Ergonomics 10 (1), 27–32.

Megaw, E.D., Richardson, J., 1978. Target uncertainty

and visual scanning strategies. Human Factors 21 (2),

303–315.

Melloy, B.J., Harris, J.M., Gramopadhye, A.K., 2000. Predict-

ing the accuracy of visual search performance in the

structural inspection of aircraft. International Journal of

Industrial Ergonomics 26 (2), 277–283.

Micalizzi, J., Goldberg, G., 1989. Knowledge of results in visual

inspection decisions sensitivity or criterion effects. Interna-

tional Journal of Industrial Ergonomics 4, 225–235.

Milosevic, S., 1983. Effects of noise on signal detection.

Ergonomics 26 (10), 939–949.

Noonan, T.K., Ash, D., Loeb, M., Warm, J.S., 1984. Task

complexity, noise, and cognitive vigilance performance.

Trends in Ergonomics/Human Factors I, 33–38.

Norman, D., Bobrow, D., 1975. On data limited and resource

limited processing. Cognitive Psychology 7, 44–60.

Noweir, M.H., 1984. Noise exposure as related to productivity,

disciplinary actions, absenteeism, and accidents among

textile workers. Journal of Safety Research 15, 163–174.

Park, J.F., Payne, M.C., 1962. Effects of noise level and

difficulty of task in performing division. Journal of Applied


Poulton, C.E., Edwards, R.S., 1974. Interactions and range

effects in experiments on pairs of stresses: mild heat and low

frequency noise. Journal of Experimental Psychology 102

(4), 621–628.

Romanski, L.M., et al., 1999. National Neuroscience 2,

1131–1136.

Schoonard, J.W., Gould, J.D., Miller, L.A., 1973. Studies of

visual inspection. Ergonomics 16 (4), 365–379.

Simpson, G.C., Cox, T., Rothschild, D.R., 1974. The effects of

noise stress on blood glucose level and skilled performance.

Ergonomics 17 (4), 481–487.

Smith, A.P., 1983a. The effects of noise and memory load on a

running memory task. British Journal of Psychology 74,

439–445.

Smith, A.P., 1983b. The effects of noise and time on recall of

order information. British Journal of Psychology 74, 83–89.

ARTICLE IN PRESS


Smith, A.P., 1985. Noise, biased probability and serial reaction.

British Journal of Psychology 76, 89–95.

Smith, A.P., 1988. Acute effects of noise exposure: an

experimental investigation of noise and task parameters

on cognitive vigilance tasks. International Archive of

Occupational and Environmental Health 60, 307–310.

Smith, A.P., 1991. Noise and aspects of attention. British

Journal of Psychology 82, 313–324.

Smith, R.L., 1969. Vigilance research: it’s application to

industrial problems. Human Factors 11, 149–156.

Smith, A.P., Miles, C., 1986. Acute effects of meals, noise,

nightwork. British Journal of Psychology 77, 377–387.

Smith, A., Stansfield, S., 1986. Aircraft noise exposure, noise

sensitivity, and everyday errors. Environment and Behavior

18 (2), 214–226.

Smith, A.P., Jones, D.M., Broadbent, D.E., 1981. The effects of

noise on recall of categorized list. British Journal of


Stevens, S.S., 1972. Stability of human performance under

intense noise. Journal of Sound and Vibration 21 (1), 35–56.

Teichner, W.H., Arees, E., Reilly, R., 1963. Noise and human

performance, a psychophysiological approach. Ergonomics

6, 83–97.

Theologus, G.C., Wheaton, G.R., Fleishman, E.A., 1974.

Effects of intermittent, moderate intensity noise stress on

human performance. Journal of Applied Psychology 59 (5),

539–547.

Warner, H.D., Heimstra, N.W., 1971. Effects of intermittent

noise on visual search tasks of varying complexity.

Perceptual Motor Skills 32, 219–226.

Warner, H.D., Heimstra, N.W., 1972. Effects of voice intensity

on visual-target detection performance. Human Factors 14,

181–185.

Watkins, W.H., 1964. Effect of certain noises upon detection of

visual signals. Journal of Experimental Psychology 67, 72–75.

Wickens, C.D., 1992. Engineering Psychology and Human

Performance. Harper Collins, New York.

Wilkinson, R.T., 1963. Interaction of noise with knowledge of

results and deep sleep deprivation. Journal of Experimental


Wolwill, J.F., Nasar, J.L., Dejoy, D.M., Foruzani, H.H., 1976.

Behavioral effects of a noisy environment: task involvement

versus passive exposure. Journal of Applied Psychology 61

(1), 67–74.

Yerkes, R.M., Dodson, J.D., 1908. The relation of strength of

stimulus to rapidity of habit formation. Journal of

Comparative Neurological Psychology 18, 459–482.

Yoshida, T., 1991. Effects of low or moderate noise on

performance. Journal of Sound and Vibration 151 (3),

429–436.

Zhand, K., Wickens, C.D., 1990. Effects of noise and workload

on performance with two object displays vs. a separate

display. Proceedings of the Human Factors Society 34th

Annual Meeting.

Documents

The effects of static multiple sources of noise on the visual search component of human inspection