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Micro-movements of varying difficulties: wrist and arm movements

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Abstract

An experiment was designed to determine the degree to which reducing movement amplitude (16°, 8°, to 4°) while keeping the relative accuracy requirements (IDs 1.5, 3, 4.5, and 6) and visual feedback display constant by increasing the display gain proportional to the decrease in amplitude (1×, 2×, 4×) influences reciprocal aiming movements of the wrist and arm. Research on smaller amplitude movements is limited and inconclusive, but these types of movement conditions are becoming increasingly more important as microsurgery and micro-mechanical applications increase. Participants were asked to flex/extend their limb/lever in the horizontal plane at the wrist (arm stabilized) or elbow joint (wrist stabilized) in an attempt to move back and forth between two targets as quickly and accurately as possible. The targets and current position of the limb were projected on the screen in front of the participant. Target width was manipulated with amplitude constant (16°, 8° or 4°). Results indicated that the linear relationship between MT and ID, typically observed for Fitts’ tasks, was observed. There were moderate decreases in MT as amplitude was decreased but only for high ID movements. ID 6 movements at 4° amplitude, for example, were produced more quickly than at amplitude 16° without sacrificing end-point accuracy. The decrease in movement time was, however, related to increased dwell time and very low peak velocities.

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References

  • Adam JJ, Paas FGWC (1996) Dwell time in reciprocal aiming task. Hum Move Sci 15:1–24

    Article  Google Scholar 

  • Adam JJ, Mol R, Pratt J, Fischer MH (2006) Moving farther but faster: an exception to Fitts law. Psychol Sci 17:794–798

    Article  PubMed  Google Scholar 

  • Arnaut L, Greenstein J (1990) Is display/control gain a useful metric for optimizing an interface. Hum Factors 32:651–663

    Google Scholar 

  • Balakrishnan IL, MacKenzie IS (1997) Performance differences in the fingers, wrist, and forearm in computer input control. In: Proceedings of the CHI’97 conference on human factors in computing systems. ACM, New York, pp 303–310

  • Bohan M, Thompson SG, Samuelson PJ (2003) Kinematic analysis of mouse cursor positioning as a function of movement scale and joint set. In: Proceedings of the international conference on industrial engineering-theory, applications and practice. Wichita State University, Wichita, KS, pp 442–447

  • Bohan M, McConnell DS, Chaparro A, Thompson SG (2010) The effects of visual magnification and physical movement scale on the manipulation of a tool with indirect vision. J Exp Psychol Applied 16:33–34

    Article  Google Scholar 

  • Boyle JB, Shea CH (2011) Wrist and arm movements of varying difficulties. Acta Psychol 137:382–396

    Article  Google Scholar 

  • Boyle JB, Panzer S, Shea CH (2012) Increasingly complex bimanual multi-frequency coordination patterns are equally easy to perform with on-line relative velocity feedback. Exp Brain Res 216:515–525

    Article  Google Scholar 

  • Buchanan JJ, Park J-H, Ryu YU, Shea CH (2003) Discrete and cyclical units of action in a mixed target pair aiming task. Exp Brain Res 150:473–489

    PubMed  Google Scholar 

  • Buchanan JJ, Park J-H, Shea CH (2004) Systematic scaling of target width: dynamics, planning, and feedback. Neurosci Lets 367:317–322

    Article  CAS  Google Scholar 

  • Buchanan JJ, Park J-H, Shea CH (2006) Target width scaling in a repetitive aiming task: switching between cyclical and discrete units of action. Exp Brain Res 175:710–725

    Article  PubMed  Google Scholar 

  • Buck L (1980) Motor performance in relation to control-display gain and target width. Ergon 32:579–589

    Article  Google Scholar 

  • Casiez G, Vogel D, Balakrishnan R, Cockburn A (2008) The impact of control-display gain on user performance in pointing tasks. Hum Comp Interact 23:215–250

    Article  Google Scholar 

  • Chen HJ, Lin CJ (2011) The Investigation of Laparoscopic Instrument Movement Control. In: Proceedings of the international multi conference of engineers and computer scientists, vol 2

  • Crossman ERFW (1956) The measurement of perceptual load in manual operations. Unpublished doctoral dissertation, Birmingham University

  • Crossman ERFW (1960) The information capacity of the human motor system in pursuit tracking. Q J Exp Psychol 12:1–16

    Google Scholar 

  • Crossman ERFW, Goodeve PJ (1963) Feedback control of hand movement and Fitts’ law. Q J Exp Psychol 35A:251–278

    Google Scholar 

  • Ellis RD, Cao A, Pandya A, Composto A, Chacko M, Klein MD, Auner G (2004) In Optimizing the surgeon-robot interface: The effect of control-display zoom level on movement time. In: Proceedings of the 48th annual meeting of the human factors and ergonomics society. HFES, New Orleans, LA

  • Fernandez L, Bootsma RJ (2008) Non-linear gaining in precision aiming: making Fitts’ task a bit easier. Acta Psychol 129:217–227

    Article  Google Scholar 

  • Fitts PM (1954) The information capacity of the human motor system in controlling the amplitude of movement. J Exp Psychol 47:381–391

    Article  PubMed  CAS  Google Scholar 

  • Fitts PM, Peterson JR (1964) Information capacity of discrete motor responses. J Exp Psychol 67:103–112

    Google Scholar 

  • Gibbs CB (1962) Controller design: interactions of controlling limbs, time-lags and gains in positional and velocity systems. Ergon 5:385–402

    Article  Google Scholar 

  • Golenberg L, Cao A, Ellis RD, Klein M, Auner G, Pandya AK (2007) Hand position effects on precision and speed in telerobotic surgery. Intr J of Med Rob and Comp Assis Surg 3:217–223

    Article  CAS  Google Scholar 

  • Graham E (1996) Virtual pointing on a computer display: non-linear control-display mappings. In: Proceedings of graphics interface 1996. Human-Computer Communications Society, Burnaby, Canada

  • Guiard Y (1993) On Fitts’s and Hooke’s laws: simple harmonic movement in upper-limb cyclical aiming. Acta Psychol 82:139–159

    Article  CAS  Google Scholar 

  • Guiard Y (1997) Fitts’ law in the discrete vs. cyclical paradigm. Hum Move Sci 16:97–131

    Article  Google Scholar 

  • Guiard Y (2009) The problem of consistency in the design of Fitts’ law experiments: consider either target distance and width or movement form and scale. In: Proceedings of the CHI 2009, ACM conference on human factors in computing systems. Sheridan Press, New York, pp 1908–1918

  • Guiard Y, Olafsdottir HB (2011) On the measurement of movement difficulty in the standard approach to Fitts’ law. PLoS ONE 6(10):e24389

    Google Scholar 

  • Guiard Y, Beaudouin-Lafon M, Mottet D (1999) Navigation as multiscale pointing: extending Fitts’ model to very high precision tasks. In: Proceedings of the SIGCHI conference on human factors in computing systems. ACM, pp 450–457

  • Harris CM, Wolpert DM (1998) Signal-dependent noise determines motor planning. Nature 394:1345–1346

    Article  Google Scholar 

  • Henneman E (1957) Relation between size of neurons and their susceptibility to discharge. Sci 126:1345–1346

    Article  CAS  Google Scholar 

  • Johnsgard T (1994) Fitts’ Law with a virtual reality glove and a mouse: effects of gain. In: Proceedings of graphics interface 1994. Human–Computer Communications Society, Burnaby, Canada

  • Klatzky RL, Lederman SJ, Langseth S (2003) Watching a cursor distorts haptically guided reproduction of mouse movement. J Exp Psych Appl 9:228–235

    Article  Google Scholar 

  • Kovacs AJ, Buchanan JJ, Shea CH (2008) Perceptual influences on Fitts’ law. Exp Brain Res 190:99–103

    Article  PubMed  CAS  Google Scholar 

  • Kovacs AJ, Buchanan JJ, Shea CH (2010) Perceptual and attentional influences on continuous 2:1 and 3:2 multi-frequency bimanual coordination. J Exp Psychol Hum Percept Perform 36(4):936–954

    Article  PubMed  Google Scholar 

  • Langolf GD, Chaffin DB, Foulke JA (1976) An investigation of Fitts’ law using a wide range of movement amplitudes. J Mot Behav 8:113–128

    Google Scholar 

  • MacKenzie IS (1989) A note on the information-theoretical basis for Fitts’ law. J Mot Behav 21:323–330

    PubMed  CAS  Google Scholar 

  • Meyer DE, Abrams RA, Kornblum S, Wright CE, Keith Smith JE (1988) Optimality in human motor performance: ideal control of rapid aimed movements. Psychol Rev 95:340

    Article  PubMed  CAS  Google Scholar 

  • Mottet D, Bootsma RJ (1999) The dynamics of goal-directed rhythmical aiming. Biol Cybern 80:235–245

    Article  PubMed  CAS  Google Scholar 

  • Murata A (1999) Extending effective target width in Fitts’ law to a two-dimensional pointing task. Int J Hum Comp Inter 11:137–152

    Article  Google Scholar 

  • Penfield W, Rasmussen T (1950) The cerebral cortex of man: a clinical study of localization of function. Macmillan, New York

    Google Scholar 

  • Plamondon R, Alimi AM (1997) Speed/accuracy trade-offs in target-directed movements. Behav Brain Sci 20:279–349

    Google Scholar 

  • Schmidt RA, Zelaznik H, Hawkins B, Frank JS, Quinn JT (1979) Motor-output variability: a theory for the accuracy of rapid motor acts. Psychol Rev 86:415–450

    Article  Google Scholar 

  • Shannon C (1948) A mathematical theory of communication. Bell Syst Tech J 27(379–423):623–656

    Google Scholar 

  • Shannon C, Weaver W (1949) The mathematical theory of communication. University of Illinois Press, Urbana

    Google Scholar 

  • Simorov A, Otte RS, Kopietz CM (2012) Review of surgical robotics user interface: what is the best way to control robotic surgery? Surg Endoscopy Interven Tech 26:2117–2125

    Google Scholar 

  • Tendrick F, Bhoyrul S, Way LW (1997) Comparison of laparoscopic imaging systems and conditions using a knot tying task. Comp Aided Surg 2:24–33

    Article  Google Scholar 

  • Trankle U, Deutschmann D (1991) Factors influencing speed and precision of cursor positioning using a mouse. Ergon 34:161–174

    Article  Google Scholar 

  • Welford AT (1960) The measurement of sensory-motor performance: survey and reappraisal of twelve years’ progress. Erg 3:189–230

    Article  Google Scholar 

  • Welford AT (1968) Fundamentals of skills. Methuen, London

    Google Scholar 

  • Woodworth RS (1899) The accuracy of voluntary movement. Psychol Rev 3:1–114

    Google Scholar 

  • Zhai S (2004) Characterizing computer input with Fitts’ law parameters—the information and non-information aspects of pointing. Int J Hum Comp Stud 61:791–809

    Article  Google Scholar 

  • Zhai S, Kong J, Ren X (2004) Speed-accuracy tradeoff in Fitts’ law tasks: on the equivalency of actual and nominal pointing precision. Int J Hum Comp Stud 61:823–856

    Article  Google Scholar 

Download references

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Authors and Affiliations

  1. Human Performance Laboratories, Department of Health and Kinesiology, Texas A&M University, College Station, TX, 77843-4243, USA

    Jason B. Boyle & Charles H. Shea

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  1. Jason B. Boyle
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  2. Charles H. Shea
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Correspondence to Charles H. Shea.

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Boyle, J.B., Shea, C.H. Micro-movements of varying difficulties: wrist and arm movements. Exp Brain Res 229, 61–73 (2013). https://doi.org/10.1007/s00221-013-3590-5

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