This article was downloaded by: [Temple University Libraries]On: 18 November 2014, At: 00:08Publisher: Taylor & FrancisInforma Ltd Registered in England and Wales Registered Number:1072954 Registered office: Mortimer House, 37-41 Mortimer Street,London W1T 3JH, UK

ErgonomicsPublication details, including instructions forauthors and subscription information:http://www.tandfonline.com/loi/terg20

Performance of a skilledmotor task in virtual andreal environmentsPaul Arnold a , Martin J. Farrell a , Steve Pettiferb & Adrian J. West ba Department of Psychology, University ofManchester, Oxford Road, Manchester M13 9PL,UKb Advanced Interfaces Group, Department ofComputer Science, University of Manchester,Oxford Road, Manchester M13 9PL, UKPublished online: 09 Nov 2010.

To cite this article: Paul Arnold , Martin J. Farrell , Steve Pettifer & Adrian J.West (2002) Performance of a skilled motor task in virtual and real environments,Ergonomics, 45:5, 348-361, DOI: 10.1080/00140130110120510

To link to this article: http://dx.doi.org/10.1080/00140130110120510

PLEASE SCROLL DOWN FOR ARTICLE

Taylor & Francis makes every effort to ensure the accuracy of allthe information (the “Content”) contained in the publications on ourplatform. However, Taylor & Francis, our agents, and our licensorsmake no representations or warranties whatsoever as to the accuracy,completeness, or suitability for any purpose of the Content. Any opinionsand views expressed in this publication are the opinions and views ofthe authors, and are not the views of or endorsed by Taylor & Francis.The accuracy of the Content should not be relied upon and should beindependently verified with primary sources of information. Taylor andFrancis shall not be liable for any losses, actions, claims, proceedings,demands, costs, expenses, damages, and other liabilities whatsoever

or howsoever caused arising directly or indirectly in connection with, inrelation to or arising out of the use of the Content.

This article may be used for research, teaching, and private studypurposes. Any substantial or systematic reproduction, redistribution,reselling, loan, sub-licensing, systematic supply, or distribution in anyform to anyone is expressly forbidden. Terms & Conditions of accessand use can be found at http://www.tandfonline.com/page/terms-and-conditions

Dow

nloa

ded

by [

Tem

ple

Uni

vers

ity L

ibra

ries

] at

00:

08 1

8 N

ovem

ber

2014

Performance of a skilled motor task in virtual and realenvironments

PAUL ARNOLD{*, MARTIN J. FARRELL{, STEVE PETTIFER{ and ADRIAN J. WEST{

{Department of Psychology, University of Manchester, Oxford Road,Manchester M13 9PL, UK

{Advanced Interfaces Group, Department of Computer Science, University ofManchester, Oxford Road, Manchester M13 9PL, UK

Keywords: Motor skill; Head mounted display (HMD); Real world analogue;Virtual environment.

Three experiments compared the performances of adult participants (three groupsof 10) on a perceptuo-motor task in both real world (RW) and virtualenvironments (VEs). The task involved passing a hoop over a bent wire course,and three versions of the task were used: a 3-D wire course with no background, a¯attened version of the 3-D course (2‰-D course) with no background, and the2‰-D course with added background to provide spatial context. In all threeexperiments the participants had to prevent the hoop from touching the wire asthey moved it. In the ®rst experiment, the VE condition produced about 18 timesmore errors than the RW task. The VE 2‰-D task was found to be as di� cult asthe 3-D, and the 2‰-D with the added background produced more errors thanthe other two experiments. Taken together, the experiments demonstrate thedi� culty of performing ®ne motor tasks in VEs, a phenomenon that has not beengiven due attention in many previous studies of motor control in VEs.

1. IntroductionThere has been a considerable amount of speculation in the popular and scienti®cliterature about the great prospects that will be opened by virtual environments(VEs), and there have been attempts to apply VE technology to a variety ofsituations (e.g. architectural design, museum displays, and medical applications(Munro et al. 1999). Such applications allow the viewer to visualize a 3-D VE and,often, to `navigate’ through it. Some experimental studies have suggested that VEsmay be of some use in allowing people to ®nd their way around new environments(Koh et al. 1999). Such tasks, however, involve only gross whole body movementsand it remains to be seen whether people can interact with a VE in a more ®nelytuned way. This paper investigated a skilled motor task in a VE and a real world(RW) situation.

A good deal of the existing work on the performance of ®ne movements in VEshas concentrated on the potential usefulness of virtual reality (VR) for the training ofsurgical skills (Chaudhry et al. 1999, O’Toole et al. 1999, Prystowsky et al. 1999).

*Author for correspondence. e-mail: arnold@fs4.psy.man.ac.uk

ERGONOMICS, 2002, VOL. 45, NO. 5, 348 ± 361

Ergonomics ISSN 0014-0139 print/ISSN 1366-584 7 online # 2002 Taylor & Francis Ltdhttp://www.tandf.co.uk/journals

DOI: 10.1080/0014013011012051 0

Dow

nloa

ded

by [

Tem

ple

Uni

vers

ity L

ibra

ries

] at

00:

08 1

8 N

ovem

ber

2014

Although, in general, these studies have found that performance on a surgical VEsimulator improves with practice, and that experienced surgeons perform better onthe simulation than inexperienced medical students, it is not possible to concludefrom such results that the VE simulation is eliciting surgically relevant skills. Thesuperior performance of experienced surgeons may be due to better visuo-motorabilities in general or to greater familiarity with the procedural aspects of therelevant surgical task (see Arnold and Farrell 2002, for a review).

Several other studies (Kozak et al. 1993, Werkhoven and Kooi 1995, Werkhovenand Groen 1998) have used VE as a tool for simulating real world motor tasks. Forexample, Werkhoven and Groen (1998) asked participants to grasp and position avirtual object. The time taken to perform this task was, however, considerably longerthan that which would be needed to perform a similar real world task (Jeannerod1984), and performance was not particularly accurate. Another study in whichparticipants had to pick up and position virtual objects was carried out by Kozak etal. (1993). Again, the VR task proved to be considerably more di� cult than the realworld version of the same task.

There are several possible sources of the greater di� culty of ®ne motor tasks inVR. Participants in a VE may be able to navigate by means that do not exist inreality, and this may create an incongruity between visual and proprioceptiveinformation that causes performance to decline (Chance et al. 1998). Virtual objectsare `weightless’, and this may impair performance in the VE task. VR systems alsohave a delay between the execution of a movement and the presentation of visualfeedback to the user. Diminished distance perception may also impair motorperformance in VEs. Both binocular and monocular cues to depth are often di� cultto simulate in VEs (Werkhoven and Kooi 1995, Wann and Mon-Williams 1996).

Given the present state of technology, some di� culties, such as binocularinformation for depth perception, appear to be intractable. Others, however (e.g.mismatch between visual and proprioceptive information, the use of `weightless’virtual objects, and the long lags between the performance of a movement and itsvirtual representation to the user), can be addressed using existing technology, as wedo in the present series of experiments.

The task that was chosen for these experiments was a version of the oldfairground game in which the participant has to move a metal hoop over a length ofbent wire without allowing the hoop to come into contact with the wire course. Asimilar task has recently been used (Rose et al. 2000) to investigate transfer oftraining from VEs to the real world. The present series of experiments are, however,not concerned with transfer of training but with the more basic issue of thecomparative di� culty of the VE and RW tasks, a comparison that was not explicitlyinvestigated by Rose et al. (2000). The present authors sought to exclude several ofthe possible causes of di� culty that may have impaired motor performance inprevious research. First, in this study, participants could only alter their view of thewire course by actually moving their head or body, just as they would in the realworld. Thus, there could be no possible disorienting eVect of `¯ying’ through the VEto a new location. Second, in both RW and VE conditions participants manipulatedidentical metal hoops, and so di� culties could not arise from the strangeness ofmanipulating weightless virtual objects. Finally, the delay between the performanceof a movement and its appearance on the virtual display was reduced to 55 ms. Thepresent authors wanted to discover whether excluding these factors would make VEperformance broadly comparable to that of the RW.

349Motor performance in virtual and real environments

Dow

nloa

ded

by [

Tem

ple

Uni

vers

ity L

ibra

ries

] at

00:

08 1

8 N

ovem

ber

2014

2. Experiment 1: Performance on the 3-D wire task in virtual and real environments2.1. ParticipantsTen ®rst-year student volunteers from the University of Manchester PsychologyDepartment took part in the experiment for course credits. They were aged between18 and 19 years. All participants had normal or corrected vision and those who woreglasses were able to do so when wearing the VR headset.

2.2. ApparatusThe bent wire and hoop real world (RW) apparatus was constructed from sections of7-mm diameter copper tubing soldered together (®gure 1). The dimensions of the

Figure 1. Real world 3-D wire course.

350 P. Arnold et al.

Dow

nloa

ded

by [

Tem

ple

Uni

vers

ity L

ibra

ries

] at

00:

08 1

8 N

ovem

ber

2014

wire course were 1 m61 m625 cm deep. The hoop was square (6 cm66 cm) andwas constructed from steel wire, with a 2.5 cm long insulated handle. A small cubewas taped to the base of the RW hoop to mimic the attachment of the positionsensor attached to the hoop used in the VE version. A lightweight cable connectedboth hoop and wire course to a Pentium III Personal Computer, which was used tosense contact between the two, and emitted an audible `beep’ from a pair of speakersand logged the time of contact.

Participants wore a Virtual Research V8 head mounted display (HMD), which hada resolution of 6406480 pixels, each generated by a triad of RGB LEDs. The imagewas presented on a pair of 1.3-in. diagonal active matrix liquid crystal displays with a608 diagonal ®eld of view. The inter-pupilliary distance ranges were between 52 and74 mm and were adjusted, using controls on the front of the HMD, to suit the wearer.The `eye relief’ (distance to the lens) could be adjusted by the wearer for comfortbetween 10 and 30 mm. The number of frames per second was in the order of 18.

The calibration of the HMD was performed empirically, using markers in thereal world to plot the actual ®eld of view of the HMD and this ®eld was transformedinto a viewing frustum for the virtual world. The empirical values match within 5%those stated by the manufacturers (e.g. 608 diagonal ®eld of view). Tracking wasperformed using Polhemus Fastrack sensors. Tracking errors were around 1 cm forthe range used.

A virtual model of the wire course and the hoop was constructed by a process ofdigitization. A Polhemus electromagnetic position sensor capable of determining theposition and rotation of a sensor in real world 3-D space was used to register theturning points of the real world hoop and to generate an appropriate virtualrepresentation in the computer. The virtual wire course and hoop had, in this ®rstexperiment, no structured background, but appeared against a uniform coloured anduntextured `sky’ and so appeared to be `hanging in space’. There was, however,shading and occlusion of parts of the course by those in front of them to provide depthinformation (as well as that provided by the stereo HMD). A virtual representation ofthe hoop was also visible in the display, but no representation of the participant’shand was rendered. The position of the virtual hoop on the display was calibrated andlinked to the movement of a hand-held real hoop by the participant. This hoop wasidentical to that used in the real world task. Its position was tracked by means ofanother Polhemus electromagnetic position sensor. When the virtual hoop contactedthe virtual wire course, an identical audible `beep’ was emitted from the two computerspeakers, as in the real world task, and the sector of the wire that was touched ¯ashedred for the duration of the contact, so visibly registering a `hit’.

Although in many ways similar to the real world task, the virtual environmentversion aVorded no haptic feedback to the user. That is, in the real world, contactbetween hoop and wire provides feedback not only audibly, but also by theconstraining of the movement of the hoop against the wire course. In the virtualenvironment, once a collision had been detected, the wire hoop was still completelyfree to move through the course. Although potentially this represents a signi®cantdivergence between RW and VE, there is presently no hardware solution to theproblem. Although several devices that exist are capable of generating forms ofhaptic feedback, they either do not provide the scale, resolution, and freedom ofmovement required for use in this experiment or health and safety regulationsprohibit their use. A number of software approaches were considered to resolve theissue of the virtual hoop apparently moving through the virtual wire course.

351Motor performance in virtual and real environments

Dow

nloa

ded

by [

Tem

ple

Uni

vers

ity L

ibra

ries

] at

00:

08 1

8 N

ovem

ber

2014

One possibility is to freeze the hoop’s movement. This is a computationallyinexpensive solution. When a collision is detected, the position of the hoop is frozenat the point in space where the collision occurred, with the only allowable motionbeing that which causes the contact between hoop and wire to be broken. This isclearly unlike the behaviour in the real world, where on collision with the course onlyone direction of movement is restricted. A further problem with this approach is thatan unnatural dislocation between the user’s real and virtual hand occurs, and thevirtual hoop is unable to move again until the two are reunited in the virtual world.

Two potential solutions to this were considered. First, the inclusion of a virtualhand, which would provide a registration cue such that when the position of thehoop (frozen on the wire course) diverges from the virtual hand, the relativepositions can be determined in order to re-unite the two. Second, to `ghost’ thefrozen hoop. This procedure produces a diVerent style of registration cue and soagain the position of the user’s hand with respect to that of the frozen hoop can bedetermined and the two reconciled.

Another possibility is geometric constraining. This solution more faithfullyreproduces the behaviour of a hoop pressed against the wire course, in that onlymotion that would cause the hoop to pass through the course is restricted. Althoughcomputationally more expensive, the limited amount of geometric comparisonrequired for this experiment is realistic given current computing capabilities.However, although this provides a more realistic movement of the hoop against thewire, it does not address the issues of the dislocation of the virtual hand from thevirtual hoop described previously.

Since it is not possible in the real world to mimic the forces and constraints of thevirtual environment, it was decided that neither of the above solutions to the hapticissue were appropriate. Indeed, the unnatural dislocation of virtual/real hand andvirtual hoop introduced a new problem that was not mirrored in the real world (i.e.with the above approaches, not only is it possible to move the hand such that itcauses the hoop to pass through the wire, but in addition it introduces the issue of re-aligning the virtual hand with the virtual hoop before progress can be made). It wasdecided that no attempt to resolve collisions would be included in the software,allowing the ¯awed but `honest’ situation whereby the virtual hoop passes freelythrough the virtual wire, audibly and visibly registering a `hit’ (by turning red) forthe purposes of counting errors.

2.3. DesignA one-way repeated measures design was administered. There was one experimentalfactor: whether participants performed the task in the real or virtual environments.All participants took part in both conditions, half performed the real task ®rst andhalf performed the virtual task ®rst. Participants performed 10 trials in eachcondition.

2.4. ProcedureParticipants were instructed to make as few errors as possible, and to perform thetask in their own time. Participants performed both tasks while standing.

2.5. ResultsAs has been noted earlier, the hoop in the VE is free to move `through’ the wirecourse without resistance. The implication of this is that passing through the wire is

352 P. Arnold et al.

Dow

nloa

ded

by [

Tem

ple

Uni

vers

ity L

ibra

ries

] at

00:

08 1

8 N

ovem

ber

2014

usually followed by a corrective movement, which itself is recorded as an error, i.e.the hoop has to `pass through’ the wire course in order to get on it. The solution thatwas adopted in this experiment and those that follow is simply to halve the numberof recorded errors, which provides a conservative estimate of the number of errors.The number of errors produced in the virtual condition was considerably higher thanthe number of errors in the real world task by a factor of about 18 (table 1). The timetaken to complete the task in each condition was also examined. As there were moreerrors in the VE condition and as participants would therefore have to spend moretime putting the hoop back on the virtual wire course, only the time actually spent onthe wire course was taken as the measure of time taken to distinguish time takenfrom number of errors. The mean time on task for a trial of the virtual task wasalmost twice as great as the time needed to perform a real world trial. There wastherefore no speed-accuracy trade oV between these tasks: performance in the virtualtask was both less accurate and slower than that in the real world task.

Regression analyses were carried out to determine whether any learning occurredfrom trial to trial as participants proceeded though the experimental session.Number of errors in the VE task declined curvilinearly through the session (F(2,7) = 24.38, p = 0.001, r2= 0.874) (®gure 2(a)), whereas there was no signi®cantrelationship in the real world task as participants’ performances were already closeto ceiling from the outset.

(a) (b)

Figure 2. (a) Mean number of errors made in each trial of the virtual environment conditionwith 3-D virtual wire course and no background; (b) mean time on task in each trial ofreal world and VE conditions with 3-D wire course and no background.

Table 1. Mean number of errors for 10 trials and mean time taken for one trial in real worldand virtual environments conditions with 3-D virtual display with no background.

Task No. of errors SD of errors Time taken (s) SD of times

VE task 243 45 98.32 14.71Real task 13 13 34.70 2.41

353Motor performance in virtual and real environments

Dow

nloa

ded

by [

Tem

ple

Uni

vers

ity L

ibra

ries

] at

00:

08 1

8 N

ovem

ber

2014

The time on task in the real world trials did, however, decrease curvilinearly overthe session (F (2,7) = 25.15, p = 0.001, r2 = 0.878), as did the time on task in the VEtrials (F (2,7) = 16.45, p = 0.002, r2= 0.825) (®gure 2(b)).

2.6. DiscussionClearly the VE task was very much more di� cult for the participants to performthan the real world task, both in terms of the number of errors made and in thetime taken to complete each trial. The participants were, however, not simplybehaving in a random way as their learning of the task over the experimentalsession clearly demonstrates: participants made fewer errors and took less time tocomplete each trial as the experiment progressed. In this case, then, there was notrade-oV between speed and accuracy. The learning curves indicate that there wassome information in the VE display that the participants were able to use to guidetheir movements, and that the participants became more pro®cient at using thisinformation the more practice they had, but that the information was so di� cult touse that, even after substantial experience of the task, performances remainedextremely poor.

As mentioned in the Introduction, Kozak et al. (1993) put forward severalreasons why performance in their VE grasping tasks was much poorer comparedto performance of the same task in the real world: participants sometimes changedlocation by ¯ying through the VE, and they had to accommodate the inherenttime lag in the system. In the present experiment, however, the ®rst explanation isruled out as participants in both the real world and VE tasks sometimes had tochange their positions relative to the wire course, but in both conditions thisrepositioning was accomplished by the same method: the participant simplyphysically moved sidewards. The lag present in the system used by Kozak et al.(1993) is not speci®ed in their paper. The lag used in the present experiment,however, was less than that which studies of driving simulators and adaptation toprisms have suggested are necessary to have a serious eVect on performance. It istherefore unlikely that the poor performance of participants in this VE task wascaused by the lag in the VE, although its possible in¯uence cannot be ruled outcompletely.

Another explanation proposed by Kozak et al. (1993) for the di� culty of theirVE task was that there was a lack of tactile feedback so that, when the participants inthe experiment picked up a virtual can, the object itself felt weightless. This factormay indeed have been of some importance in the grasping task studied in their paper,but the present experiment suggests that this cannot be a major reason for thedi� culty of VE as, in the present task, no tactile feedback was necessary in order toperform the task well. Indeed, the better the participant performed the RW task, theless tactile feedback there was. Participants could perform the RW task very welland, so, received very little tactile feedback concerning their performances. It istherefore unlikely that the lack of tactile feedback in the VE task could account forits greater di� culty.

A further possible cause of the participants’ poor performance in the presentexperiment is that they had to move the virtual hoop back and forth in depth.Werkhoven and Groen (1998) found that such movements were more di� cult in aVE than were horizontal or vertical movements in the picture plane. The presentauthors therefore investigated whether reducing the need to move the virtual hoop indepth would reduce the di� culty of performance in the VE.

354 P. Arnold et al.

Dow

nloa

ded

by [

Tem

ple

Uni

vers

ity L

ibra

ries

] at

00:

08 1

8 N

ovem

ber

2014

3. Experiment 2: Performance on the `2‰-D’ wire task in virtual and realenvironments

To reduce the need to move the hoop back and forth in depth the authorsconstructed real and VE versions of a ¯attened (`2‰-D’) projection of the wirecourse used in Experiment 1. The new 2‰-D course was manufactured from a`silhouette’ of the original and thus retained similar proportions. In this case, thewire itself bent in only two directions (vertical and horizontal, with no depth-wisevariation). Therefore, although the wire was still a three-dimensional object,participants did not have to make back and forward movements in depth to the sameextent as in Experiment 1.

3.1. ParticipantsTen ®rst-year student volunteers from the University of Manchester PsychologyDepartment took part in the experiment for course credits. They were aged between18 and 19 years. All participants had normal or corrected vision and those who woreglasses were able to do so when wearing the headset. None of the participants hadtaken part in Experiment 1.

3.2. ApparatusThe apparatus used was the same as that used in Experiment 1, except that both thereal and virtual wire courses approximated to `2‰-D’ projections of the 3-D wireused previously. To perform the task, therefore, participants did not have to movethe hoop backwards and forwards in depth to a large extent, but only from left toright and up and down.

3.3. Design and procedureThese were identical to those of Experiment 1.

3.4. ResultsThe overall number of errors in the VE task was very much greater than the numberof errors in the real world task (table 2). The mean time on task for one trial was alsovery much greater for the VE task than for the real world task.

Linear regression analyses were carried out to determine whether any learningoccurred from trial to trial as participants proceeded through the experimentalsession. Number of errors in the VE task declined curvilinearly through the session(F (2,7) = 53.85, p50.001, r2= 0.939) (®gure 3(a)), whereas there was no suchrelationship in the real world task as participants’ performances were already closeto ceiling from the outset.

The time on task in the RW trials did, however, decrease curvilinearly over thesession (F (2,7) = 52.77, p50.001, r2 = 0.938), as the time on task in the VE trials (F(2,7) = 15.93, p = 0.002, r2 = 0.820) (®gure 3(b)).

Table 2. Mean number of errors for 10 trials and mean time taken for one trial in real worldand virtual environment conditions with `2‰-D’ virtual display with no background.

Task No. of errors SD of errors Time taken (s) SD of times

VE task 210 79 100.00 8.56Real task 4 4 39.75 4.03

355Motor performance in virtual and real environments

Dow

nloa

ded

by [

Tem

ple

Uni

vers

ity L

ibra

ries

] at

00:

08 1

8 N

ovem

ber

2014

3.5. DiscussionThe participants clearly still found the VE task considerably more di� cult than thereal world task. Thus, reducing the need to move the virtual hoop in depth onlymade a minimal diVerence to the di� culty of the task. This ®nding appears to diVerfrom that of Werkhoven and Groen (1998), who found that placement of virtualobjects in depth was particularly di� cult. It should be noted, however, that theyobserved that this di� culty was most marked when participants manipulated thevirtual objects by moving a mouse (as opposed to their hands) and when participantsonly had monocular vision. In this experiment manipulation of the virtual hoop wasalways carried out by hand movements and stereoscopic vision was always available,and these factors may account for the very slight bene®cial eVect of reducing theneed to move the hoop in depth.

It should also be noted that 2‰-D task performance exhibited a large amount ofbetween-participant variability. In the 2‰-D task three of the participants weresubstantially better (85±121 errors) than the best participant in the 3-D task (156errors); whereas the majority (the remaining 7) performed at the same level as theparticipants in the 3-D task (the mean number of errors in the 3-D task was 243 forall 10 participants; the mean number of 2‰-D errors for the remaining 7 participantswas 254). It is possible that reducing the need to move the hoop in depth whenstereoscopic vision and hand manipulation were already available conferred only asmall advantage relative to the 3-D task, so that only a small subgroup of theparticipants were able to bene®t from it.

4. Experiment 3: Performance on the `2‰-D’ wire task in virtual (with a structuredbackground) and real environments

Even though participants were not required to make extensive movements in depthin Experiment 2, it was still necessary for them to perceive depth in the virtual

(a) (b)

Figure 3. (a) Mean number of errors made in each trial of the virtual environment conditionwith 2‰-D virtual wire course and no background; (b) mean time on task in each trial ofthe real world and VE conditions with 2‰-D virtual wire course and no background.

356 P. Arnold et al.

Dow

nloa

ded

by [

Tem

ple

Uni

vers

ity L

ibra

ries

] at

00:

08 1

8 N

ovem

ber

2014

display in order to monitor the hoop’s progress and to keep it on the wire course. Inthe ®rst two experiments, the VE wire course was presented without a structuredbackground and this may have increased the di� culty of the task. The real worldtask, of course, was always performed against a structured background, i.e. thecontents of the laboratory. It was therefore decided in the present experiment topresent the virtual wire against a structured background that featured the ¯oor andwalls of a `room’ to see whether this would make the real and VE tasks morecomparable. As emphasized by Gibson (1950, 1979), the `ground’ against which anobject is perceived provides a number of important sources of information, such astexture gradients, specifying the distance of the object from the perceiver. Althoughsuch information is likely to have most in¯uence on large scale movements in depth,it is nevertheless possible that it could also have more subtle eVects on the motor taskstudied here. In addition, the studies by Kozak et al. (1993) and Werkhoven andGroen (1998), which were quoted earlier, made use of structured VE backgrounds,so it was thought desirable to rule out the absence of a structured background in thepresent study as a possible cause of task di� culty.

4.1. ParticipantsTen student volunteers, aged between 18 and 25 years, from the PsychologyDepartment and the Computer Science Department of Manchester University tookpart in the study. None had participated in any of the earlier experiments. Allparticipants had normal or corrected vision and those who wore glasses were able todo so when wearing the headset.

4.2. ApparatusThe apparatus was identical to that used in Experiment 2, except that the `2‰-D’virtual wire was presented against a background that represented a normal room.The virtual wire was depicted as standing on a table, which stood on a carpeted ¯oor.

4.3. Design and procedureThe design and procedure of the experiment were identical to those of the previoustwo experiments.

4.4. ResultsThe overall number of errors in the VE tasks was, as in the previous experiments,very much greater than in the RW task (table 3), and the mean time on task for onetrial was also greater in the VE task than in the RW task.

Linear regression analyses were carried out to determine if performance changedwith increasing practice. There was no decrease, whether linear or curvilinear, in thenumber of errors in the VE task (linear: F (1,8) = 1.84, p = 0.212; curvilinear: F(2,7) = 2.50, p = 0.151)(®gure 4(a)), and the errors on the RW task were already at

Table 3. Mean number of errors for 10 trials and mean time taken for one trial in real worldand virtual environment conditions with `2‰-D’ virtual display with background.

Task No. of errors SD of errors Time taken (s) SD of times

VE task 256 81 103 25Real task 5 7 26 12

357Motor performance in virtual and real environments

Dow

nloa

ded

by [

Tem

ple

Uni

vers

ity L

ibra

ries

] at

00:

08 1

8 N

ovem

ber

2014

¯oor level from the start. There was no decrease, whether linear or curvilinear, intime on task in the VE condition (linear: F(1,8) = 1.02, p = 0.342; curvilinear:F(2,7) = 0.62, p = 0.552), however, there was a curvilinear decrease in time on taskin the RW condition (F(2,7) = 120.12, p50.001, r2= 0.972) (®gure 4(b)).

The error scores from all three experiments were subjected to a two-way mixedANOVA (VE/RW6experiment) with repeated measures on the VE/RW manipula-tion. This analysis was carried out to see whether the attempts to make the VE taskeasier in¯uenced the participants’ performances. There was a signi®cant main eVectof the VE/RW manipulation (F(1,27) = 362.11, p50.0001), showing that overall theVE tasks produced far more errors than the RW tasks. There was, however, nosigni®cant diVerence in the number of errors in each experiment (F(2,27) = 1.64,p = 0.213), nor was there a signi®cant interaction between the VE/RW manipulationand experiment (F(2,27) = 1.63, p = 0.214).

The mean scores to complete a single trial in each of the three experiments werealso subjected to a two-way mixed ANOVA (VE/RW6experiment) with repeatedmeasures on the VE/RW manipulation. As with error scores, there was a signi®cantmain eVect of the VE/RW manipulation (F(1,27) = 245.09, p50.0001), indicatingthat participants spent a much longer time on a trial of the VE task than on a trial ofthe RW task. The time on task did not diVer between experiments (F(2, 27) = 0.34,p = 0.712), and there was no interaction between the VE/RW manipulation andexperiment (F(2,27) = 1.37, p = 0.272).

4.5. DiscussionAs in Experiments 1 and 2, the participants performed signi®cantly worse on the VEtask than in the RW task, both in terms of accuracy and in terms of speed ofperformance. It would appear that the introduction of a structured background didnot make the VE task any easier and, indeed, the number of errors was actually

(a) (b)

Figure 4. (a) Mean number of errors made in each trial of the virtual environment conditionwith 2‰-D virtual wire course with background; (b) mean time on task in each trial of thereal world and VE conditions with 2‰-D virtual wire course with background.

358 P. Arnold et al.

Dow

nloa

ded

by [

Tem

ple

Uni

vers

ity L

ibra

ries

] at

00:

08 1

8 N

ovem

ber

2014

somewhat higher than in the previous experiments. Moreover, in Experiments 1 and2, participants tended to become both quicker and more accurate over trials,however, no such improvement was seen in the present experiment.

One possible explanation of why the structured background did not improve VEperformance is that it increased the rendering time of the display. However, theframe rates with and without the background were measured. There was, however,little diVerence: the device produced an average of about 18 frames per second (fps)both with and without background. This varied somewhat depending on exactly howmuch of the bent wire course was in view at any one time, but the variability was verysimilar both with and without the background. It is therefore unlikely that the framerate reduction was the cause of the increased di� culty in the present experiment.

5. General discussionThe ®rst point to note is how di� cult the VE task is, both in terms of accuracy andspeed of performance, compared to the real world task. It should be noted, however,that the task used in the present study required control skill with a closed hand, andnot manipulative skills involving the use of the digits. Caution should, therefore, beexercised when attempting to generalize from the present ®ndings to other ®ne motortasks. Nevertheless, although intuitively it might be expected that ®ne motor controlin VE would be somewhat more di� cult than in the real world, the authors wereunprepared for the very large diVerences that emerged. Although other authors havereported data that point to the great di� culty of VE, they have not discussed theissue in depth. It was therefore felt that this obviously important issue is one that hasgenerally been ignored and that more attention should be paid to it.

The second point of interest is that it was not possible to reduce the di� culty ofthe VE task to any great extent: both the reduction of the depth dimension and theprovision of a structured background had little eVect.

It could be argued that the absence of physical resistance in this and most VEs isof relevance in the present study. It has indeed been shown (Macrae and Holding1965) that diVerent forms of resistance to a physical task play a role in motorlearning, such that learning a movement will be most e� cient when trainingincorporates similar levels of physical resistance to the desired movement. Never-theless, it should be noted that the RW task provided little physical resistance to theparticipants’ movements, as contact with the wire was made very infrequently.

It appears that the assumption of Kozak et al. (1993) and Werkhoven and Groen(1998) is that virtual environment is not qualitatively diVerent from the real world. Arelated view is that technological developments and improvements will, in time,make the virtual as `easy’ and usable as tasks in the real world. The alternativeperspective to these views is that virtual environment setups are essentially diVerentin qualitative ways, which are of course not yet understood. Such a view is putforward by Rose and Foreman (1999: 553):

We must be aware the perceptual and sensorimotor behaviour in the virtual andreal worlds may be signi®cantly diVerent. Similarly, cognitive loads associated withprocessing information in real and virtual environments might not be the same.

Wilson (1997: 550) has provided some evidence for this view: he found that inspatial learning the `conventional superiority of active over passive interaction withthe real-world situation has not always been found in VEs’.

359Motor performance in virtual and real environments

Dow

nloa

ded

by [

Tem

ple

Uni

vers

ity L

ibra

ries

] at

00:

08 1

8 N

ovem

ber

2014

There have been some studies (Arthur et al. 1997) that have suggested that there islittle diVerence between observation of the virtual world and observation of the realworld. Such studies, however, have not required participants to interact with eithervirtual or real displays. It may therefore be the case that virtual environmental worldscan quite accurately capture the passive experience of observing the real world, butthat they cannot capture the essence of embodied interaction with the real world.

There is a tendency to assume that the presence of a structured background in thereal world task is of bene®t to the participant, and, so, believe that a structuredbackground will also be of bene®t in VE. However, even if it was the case that astructured background was bene®cial in the real world, these results suggest that it isnot possible to conclude from this that a similar background will be bene®cial in VE.Indeed, these studies found that there was no reduction in errors when such abackground was present and, in fact, errors actually increased somewhat, albeit by anon-signi®cant amount.

The main ®nding of these experiments is that the three VE tasks are more di� cultthan the RW ones. The other ®nding is that the two attempts to make the VE taskeasier by minimizing one dimension and by adding a structured spatial backgroundfailed. Rose and Foreman (1999) have made the suggestion that VE and RW areessentially diVerent, and suggest that the two may operate on diVerent logics, whichhave yet to be elucidated. Further work is clearly required to more fully understandwhy VR is so di� cult on the way to creating more useful technologies and trainingmethods. In particular, the authors’ future work will investigate whether di� cultiesin VR motor tasks are simply due to current technological limitations or whether, asRose and Foreman (1999) suggest, there are qualitative diVerences between VR andthe real world.

ReferencesARNOLD, P. and FARRELL, M. J. 2002, Can virtual reality be used to measure and train surgical

skills? Ergonomics, 45, 362±379.ARTHUR, E. J., HANCOCK, P. A. and CHRYSLER, S. T. 1997, The perception of spatial layout in

real and virtual worlds, Ergonomics, 40, 69±77.CHANCE, S. S., GAUNET, F., BEALL, A. C. and LOOMIS, J. M. 1998, Locomotion mode aVects the

updating of objects encountered during travel: the contribution of vestibular andproprioceptive inputs to path integration, Presence: Teleoperators and VirtualEnvironments, 7, 168±178.

CHAUDHRY, A., SUTTON, C., WOOD, J., STONE, R. and MCCLOY, R. 1999, Learning rate forlaparoscopic surgical skills on MIST VE, a virtual environment simulator: quality ofhuman-computer interface, Annals of the Royal College of Surgeons of England, 81, 281±286.

GIBSON, J. J. 1950, The Perception of the Visual World (Boston: Houghton Mi‚in).GIBSON, J. J. 1979, The Ecological Approach to Visual Perception (Boston: Houghton Mi‚in).JEANNEROD, M. 1984, The timing of natural prehension movements, Journal of Motor Behavior,

16, 235±254.KOH, G., VON WIEGAND, T. E., GARNETT, R. L., DURLACH, N. I. and SHINN-CUNNINGHAM, B.

1999, Use of virtual environments for acquiring con®gurational knowledge aboutspeci®c real world places. I. Preliminary experiment, Presence: Teleoperators and VirtualEnvironments, 8, 632±656.

KOZAK, J. J., HANCOCK, P. A., ARTHUR, P. J. and CHRYSLER, S. T. 1993, Transfer of trainingfrom virtual environment, Ergonomics, 36, 777±784.

MACRAE, A. W. and HOLDING, D. H. 1965, Method and task in motor guidance, Ergonomics, 8,315±320.

MUNRO, A. J., HOÈ OÈ K, K. and BENYON, D. (eds) 1999, Social Navigation of Information Space(London: Springer).

360 P. Arnold et al.

Dow

nloa

ded

by [

Tem

ple

Uni

vers

ity L

ibra

ries

] at

00:

08 1

8 N

ovem

ber

2014

O’TOOLE, R. V., PLAYTER, R. R., KRUMMEL, T. M., BLANK, W. C., CORNELIUS, N. H., ROBERTS,W. R., BELL, W. J. and RAIBERT, M. 1999, Measuring and developing suturing techniquewith a virtual environment surgical simulator, Journal of the American College ofSurgeons, 189, 114±127.

PRYSTOWSKY, J. B., REGEHR, G., ROGERS, D. A., LOAN, J. P., HIEMENZ, L. L. and SMITH, K. M.1999, A virtual environment module for intravenous catheter placement, AmericanJournal of Surgery, 177, 171±175.

ROSE, D. and FOREMAN, N. 1999, Virtual reality, The Psychologist, 12, 550±554.ROSE, F. D., ATTREE, E. A., BROOKS, B. M., PARSLOW, D. M., PENN, P. R. and AMBIHAIPAHAN , N.

2000, Training in virtual environments: transfer to real world tasks and equivalence toreal task training, Ergonomics, 43, 494±511.

WANN, J. and MON-WILLIAMS, M. 1996, What does virtual reality NEED?: Human factorsissues in the design of three-dimensional computer environments, International Journalof Human-Compter Studies, 44, 829±847.

WERKHOVEN, P. J. and GROEN, J. 1998, Manipulation performance in interactive virtualenvironments, Human Factors, 40, 432±442.

WERKHOVEN, P. J. and KOOI, F. L. 1995, 3D spatial localization in real and virtual environments,TNO Report No. TNO-TM 1995 B-5 (Soesterberg: TNO Human Factors ResearchInstitute).

WILSON, P. 1997, Virtual environment in spatial learning research, in N. Foreman and R.Gillett (eds), A Handbook of Spatial Research Paradigms and Methodologies, Vol. 1(Hove: Psychology Press), 181±206.

361Motor performance in virtual and real environments

Dow

nloa

ded

by [

Tem

ple

Uni

vers

ity L

ibra

ries

] at

00:

08 1

8 N

ovem

ber

2014