Most research based on Fitts' law define a log-linear relationship between temporal and spatial accuracy in goal-directed aiming tasks using stationary targets. Whether this relationship holds or not when the targets have varying velocities, and how the behavioral strategies and physical activities may change accordingly are of interest. The aim of this study was to investigate the relationship between temporal and spatial accuracy in goal-directed aiming tasks with moving targets. Participants were asked to aim at two target widths using a joystick. Results demonstrated that in a goal-directed aiming task there was a negative effect on performance when target velocity was increased or target width was decreased. Participants moved faster and then made more systematic errors in a high-velocity target condition. Results may be applicable to the complex perceptual-motor behavior of people who perform tasks using computers.
Get full access to this article
View all access options for this article.
References
1.
AccotJ.ZhaiS. (1997) Beyond Fitts' law: Models for trajectory-based HCI tasks. In Proceedings of ACM CHI '97 Conference on Human Factors & Computing Systems. New York: ACM. Pp. 295–302.
2.
AkamatsuM.MacKenzieI. S. (1996) Movement characteristics using a mouse with tactile and force feedback. International Journal of Human-Computer Studies, 11,483–493.
3.
BradiA. C.AdamJ. J.FischerM. H.PrattJ. (2009) Modulating Fitts's law: The effect of disappearing allocentric information. Experimental Brain Research, 194, 571–576.
4.
BrennerE.SmeetsJ. B. J. (1997) Fast responses of the human hand to changes in target position. Journal of Motor Behavior, 29, 297–310.
5.
BrouwerA. M.BrennerE.SmeetsJ. B. J. (2000) Hitting moving objects: The dependency of hand velocity on the speed of the target. Experimental Brain Research, 133, 242–248.
6.
BrouwerA. M.MiddelburgT.SmeetsJ. B. J.BrennerE. (2003) Hitting moving targets: A dissociation between the use of the target's speed and direction of motion. Experimental Brain Research, 152, 368–375.
7.
BrouwerA. M.SmeetsJ. B. J.BrennerE. (2005) Hitting moving targets: Effects of target speed and dimensions on movement time. Experimental Brain Research, 165, 28–36.
8.
CorcosD. M.GottliebG. L.AgarwalG. C. (1988) Accuracy constraints upon rapid elbow movements. Journal of Motor Behavior, 20, 255–272.
9.
DonkelaarP.LeeR. G.GellmanR. S. (1992) Control strategies in directing the hand to moving targets. Experimental Brain Research, 91, 151–161.
10.
FischerM. H. (2003) Spatial representations in number processing-evidence from a pointing task. Visual Cognition, 10, 493–508.
11.
FittsP. M. (1954) The information capacity of the human motor system in controlling the amplitude of movement. Journal of Experimental Psychology, 47, 381–391.
12.
FittsP. M.PetersonJ. R. (1964) Information capacity of discrete motor responses. Journal of Experimental Psychology, 67, 103–112.
13.
JagacinskiR. J.HahS. (1988) Progression–regression effects in tracking repeated patterns. Journal of Experimental Psychology: Human Perception and Performance, 14, 77–88.
14.
KetchamC. J.SeidlerR. D.Van GemmertA. W. A.StelmachG. E. (2002) Age-related kinematic dfferences as influenced by task difficulty, target size, and movement amplitude. Journal of Gerontology: Psychological Sciences, 57B, 54–64.
15.
MacKenzieI. S. (1992) Fitts' law as a research and design tool in human-computer interaction. Human-Computer Interaction, 7, 91–139.
16.
MensvoortK.HermesD. J.MontfortM. (2008) Usability of optically simulated haptic feedback. International Journal of Human-Computer Studies, 66, 438–451.
17.
PlamondonR. (1993) Looking at handwriting generation from a velocity control perspective. Acta Psychologica, 82, 89–101.
18.
PlamondonR. (1995) A kinematic theory of rapid human movements: Movement representation and generation. Biological Cybernetics, 72, 295–307.
19.
PlamondonR.AlimiA. M. (1997) Speed/accuracy trade-offs in target-directed movements. Behavioral and Brain Sciences, 20, 279–349.
20.
RinkenauerG.OsmanA.UlrichR.Müller-GethmannH.MattesS. (2004) On the locus of speed-accuracy trade-off in reaction time: Inferences from the lateralized readiness potential. Journal of Experimental Psychology: General, 133, 261–282.
21.
SallnasE. L.ZhaiS. (2003) Collaboration meets Fitts' law: Passing virtual objects with and without haptic force feedback. In RauterbergM.MenozziM.WessonJ. (Eds.), Proceedings of INTERACT'03. Amsterdam: IOS Press. Pp. 97–104.
22.
SchmidtR. A. (1988) Motor control and learning: A behavioral emphasis. (2nd ed.) Champaign, IL: Human Kinetics.
23.
SmyrnisN.EvdokimidisI.ConstantinidisT. S.KastrinakisG. (2000) Speed-accuracy trade-off in the performance of pointing movements in different directions in two-dimensional space. Experimental Brain Research, 134, 21–31.
24.
SoechtingJ. E.LacquanitiF. (1983) Modification of trajectory of a pointing movement in response to a change in target location. Journal of Neurophysiology, 49, 548–564.
25.
SoukoreffR. W.MacKenzieI. S. (2004) Towards a standard for pointing device evaluation, perspectives on 27 years of Fitts' law research in HCLInternational Journal of Human-Computer Studies, 61, 751–789.
26.
SutterC.ZiefleM. (2005) Interacting with notebook input devices: An analysis of motor performance and users' expertise. Human Factors, 47, 169–187.
27.
TynanP. D.SekulerR. (1982) Motion processing in peripheral vision: Reaction time and perceived velocity. Vision Research, 22, 61–68.
28.
WalkerN.PhilbinD. A.FiskA. D. (1997) Age-related differences in movement control: Adjusting submovement structure to optimize performance. Journal of Gerontology: Psychological Sciences, 52B, 40–52.
29.
WallaceS. A.NewellK. M. (1983) Visual control of discrete aiming movements. The Quarterly Journal of Experimental Psychology A: Human Experimental Psychology, 35, 311–321.
30.
WoodworthR. S. (1899) The accuracy of voluntary movement. Psychological Monographs, 3, 1–119.
31.
WordenA.WalkerN.BharatK.HudsonS. (1997) Making computers easier for older adults to use: Area cursors and sticky icons. In Proceedings of ACM CHI '97 Conference on Human Factors & Computing Systems. New York: ACM. Pp. 266–271.
