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Pointing with the ankle: the speed-accuracy trade-off

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Abstract

This study investigated the trade-off between speed and accuracy in pointing movements with the ankle during goal-directed movements in dorsal–plantar (DP) and inversion–eversion (IE). Nine subjects completed a series of discrete pointing movements with the ankle between spatial targets of varying difficulty. Six different target sets were presented, with a range of task difficulty between 2.2 and 3.8 bits of information. Our results demonstrated that for visually evoked, visually guided discrete DP and IE ankle pointing movements, performance can be described by a linear function, as predicted by Fitts’ law. These results support our ongoing effort to develop an adaptive algorithm employing the speed-accuracy trade-off concept to control our pediatric anklebot while delivering therapy for children with cerebral palsy.

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References

  • Balakrishnan R, MacKenzie IS (1997) Performance differences in the fingers, wrist, and forearm in computer input control. In: Proceedings of the ACM SIGCHI conference on human factors in computing systems. ACM, Atlanta, GA, USA, pp 303–310

  • Boone DC, Azen SP (1979) Normal range of motion of joints in male subjects. J Bone Joint Surg Am 61:756–759

    CAS  PubMed  Google Scholar 

  • Bootsma RJ, Marteniuk RG, MacKenzie CL, Zaal FT (1994) The speed-accuracy trade-off in manual prehension: effects of movement amplitude, object size and object width on kinematic characteristics. Exp Brain Res 98:535–541

    Article  CAS  PubMed  Google Scholar 

  • Bravo PE, LeGare M, Cook AM, Hussey S (1993) A study of the application of Fitts’ law to selected cerebral palsied adults. Percept Mot Skills 77:1107–1117

    Article  CAS  PubMed  Google Scholar 

  • Brown JS, Slater-Hammel AT (1949) Discrete movements in the horizontal plane as a function of their length and direction. J Exp Psychol 39:84–95

    Article  CAS  PubMed  Google Scholar 

  • Buchanan JJ, Park JH, Ryu YU, Shea CH (2003) Discrete and cyclical units of action in a mixed target pair aiming task. Exp Brain Res 150:473–489. doi:10.1007/s00221-003-1471-z

    PubMed  Google Scholar 

  • Buchanan JJ, Park JH, 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. doi:10.1007/s00221-006-0589-1

    Article  PubMed  Google Scholar 

  • Crossman ER, Goodeve PJ (1983) Feedback control of hand-movement and Fitts’ Law. Q J Exp Psychol A 35:251–278

    Article  CAS  PubMed  Google Scholar 

  • Elliott D, Helsen WF, Chua R (2001) A century later: Woodworth’s (1899) two-component model of goal-directed aiming. Psychol Bull 127:342–357

    Article  CAS  PubMed  Google Scholar 

  • Fasoli SE, Fragala-Pinkham M, Hughes R, Hogan N, Krebs HI, Stein J (2008) Upper limb robotic therapy for children with hemiplegia. Am J Phys Med Rehabil 87:929–936. doi:10.1097/PHM.0b013e31818a6aa4

    Article  PubMed  Google Scholar 

  • Fasoli SE, Ladenheim B, Mast J, Krebs HI (2012) New horizons for robot-assisted therapy in pediatrics. Am J Phys Med Rehabil 91:S280–S289. doi:10.1097/PHM.0b013e31826bcff4

    Article  PubMed  Google Scholar 

  • Fernandez L, Bootsma RJ (2004) Effects of biomechanical and task constraints on the organization of movement in precision aiming. Exp Brain Res 159:458–466. doi:10.1007/s00221-004-1964-4

    Article  PubMed  Google Scholar 

  • Fernandez L, Bootsma RJ (2008) Non-linear gaining in precision aiming: Making Fitts’ task a bit easier. Acta Psychol 129:217–227. doi:10.1016/j.actpsy.2008.06.001

    Article  Google Scholar 

  • Ferraro M, Palazzolo JJ, Krol J, Krebs HI, Hogan N, Volpe BT (2003) Robot-aided sensorimotor arm training improves outcome in patients with chronic stroke. Neurology 61:1604–1607

    Article  CAS  PubMed  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  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  • Frascarelli F, Masia L, Di Rosa G, Cappa P, Petrarca M, Castelli E, Krebs HI (2009) The impact of robotic rehabilitation in children with acquired or congenital movement disorders. Eur J Phys Rehabil Med 45:135–141

    CAS  PubMed  Google Scholar 

  • Gan KC, Hoffmann ER (1988) Geometrical conditions for ballistic and visually controlled movements. Ergonomics 31:829–839. doi:10.1080/00140138808966724

    Article  CAS  PubMed  Google Scholar 

  • Gump A, LeGare M, Hunt DL (2002) Application of Fitts’ law to individuals with Cerebral Palsy. Percept Mot Skills 94:883–895

    PubMed  Google Scholar 

  • Hay L (1981) The effect of amplitude and accuracy requirements on movement time in children. J Mot Behav 13:177–186

    Article  CAS  PubMed  Google Scholar 

  • Hoffmann E (1981) An ergonomics approach to predetermined motion time systems. In: Proceedings from the 9th national conference, institute of industrial engineers, Australia, pp 30–47

  • Hogan N, Krebs HI, Rohrer B et al (2006) Motions or muscles? Some behavioral factors underlying robotic assistance of motor recovery. J Rehabil Res Dev 43:605–618

    Article  PubMed  Google Scholar 

  • Jagacinski RJ, Monk DL (1985) Fitts’ Law in two dimensions with hand and head movements. J Mot Behav 17:77–95

    Article  CAS  PubMed  Google Scholar 

  • Kerr R (1975) Movement control and maturation in elementary-grade children. Percept Mot Skills 41:151–154

    Article  CAS  PubMed  Google Scholar 

  • Kim JY, Parnianpour M, Marras WS (1996) Quantitative assessment of the control capability of the trunk muscles during oscillatory bending motion under a new experimental protocol. Clin Biomech (Bristol, Avon) 11:385–391

    Article  Google Scholar 

  • Kovacs AJ, Buchanan JJ, Shea CH (2008) Perceptual influences on Fitts’ law. Exp Brain Res 190:99–103. doi:10.1007/s00221-008-1497-3

    Article  CAS  PubMed  Google Scholar 

  • Krebs HI, Hogan N (2012) Robotic therapy: the tipping point. Am J Phys Med Rehabil 91:S290–S297. doi:10.1097/PHM.0b013e31826bcd80

    Article  PubMed Central  PubMed  Google Scholar 

  • Krebs HI, Hogan N, Aisen ML, Volpe BT (1998) Robot-aided neurorehabilitation. IEEE Trans Rehabil Eng 6:75–87

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Krebs HI, Palazzolo JJ, Dipietro L, Volpe BT, Hogan N (2003) Rehabilitation robotics: performance-based progressive robot-assisted therapy. Auton Robots 15:7–20. doi:10.1023/A:1024494031121

    Article  Google Scholar 

  • Krebs HI, Ladenheim B, Hippolyte C, Monterroso L, Mast J (2009) Robot-assisted task-specific training in Cerebral Palsy. Dev Med Child Neurol 51(Suppl 4):140–145. doi:10.1111/j.1469-8749.2009.03416.x

    Article  PubMed  Google Scholar 

  • Krebs HI, Rossi S, Kim SJ, Artemiadis PK, Williams D, Castelli E, Cappa P (2011) Pediatric anklebot. In: 2011 IEEE international conference on rehabilitation robotics (ICORR)

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

    Article  CAS  PubMed  Google Scholar 

  • Leisman G (1989) Limb segment information-transmission capacity. J Manip Physiol Ther 12:3–9

    CAS  Google Scholar 

  • Lin JF, Drury CG (2011) Verification of two models of ballistic movements. Human–Comput Interact Interact Tech Environ Pt Ii 6762:275–284

    Article  Google Scholar 

  • Maruff P, Wilson P, Trebilcock M, Currie J (1999) Abnormalities of imagined motor sequences in children with developmental coordination disorder. Neuropsychologia 37:1317–1324. doi:10.1016/S0028-3932(99)00016-0

    Article  CAS  PubMed  Google Scholar 

  • Mazzoni P, Hristova A, Krakauer JW (2007) Why don’t we move faster? Parkinson’s disease, movement vigor, and implicit motivation. J Neurosci 27:7105–7116. doi:10.1523/Jneurosci.0264-07

    Article  CAS  PubMed  Google Scholar 

  • Meyer DE, Kornblum S, Abrams RA, Wright CE, Smith JEK (1988) Optimality in human motor-performance—ideal control of rapid aimed movements. Psychol Rev 95:340–370. doi:10.1037/0033-295x.95.3.340

    Article  CAS  PubMed  Google Scholar 

  • Michmizos KP, Krebs HI (2012a) Assist-as-needed in lower extremity robotic therapy for children with Cerebral Palsy. In: 2012 4th IEEE Ras & Embs international conference on biomedical robotics and biomechatronics (Biorob), pp 1081–1086

  • Michmizos KP, Krebs HI (2012b) Serious games for the pediatric anklebot. In: 2012 4th IEEE Ras & Embs international conference on biomedical robotics and biomechatronics (Biorob), pp 1710–1714

  • Moore KL, Dalley AF, Agur AMR (2010) Clinically oriented anatomy. Wolters Kluwer Health/Lippincott Williams & Wilkins, Philadelphia

    Google Scholar 

  • Novak KE, Miller LE, Houk JC (2000) Kinematic properties of rapid hand movements in a knob turning task. Exp Brain Res 132:419–433

    Article  CAS  PubMed  Google Scholar 

  • Perry J (1992) Gait analysis: normal and pathological function. SLACK, Thorofare, NJ

    Google Scholar 

  • Roy A, Krebs HI, Williams DJ, Bever CT, Forrester LW, Macko RM, Hogan N (2009) Robot-aided neurorehabilitation: a novel robot for ankle rehabilitation. IEEE Trans Rob 25:569–582. doi:10.1109/Tro.2019783

    Article  Google Scholar 

  • Sanger TD, Kaiser J, Placek B (2005) Reaching movements in childhood dystonia contain signal-dependent noise. J Child Neurol 20:489–496

    PubMed  Google Scholar 

  • Schmidt RA, Zelaznik H, Hawkins B, Frank JS, Quinn JT Jr (1979) Motor-output variability: a theory for the accuracy of rapid motor acts. Psychol Rev 47:415–451

    Article  CAS  PubMed  Google Scholar 

  • Smits-Engelsman BC, Van Galen GP, Duysens J (2002) The breakdown of Fitts’ law in rapid, reciprocal aiming movements. Exp Brain Res 145:222–230. doi:10.1007/s00221-002-1115-8

    Article  CAS  PubMed  Google Scholar 

  • Smits-Engelsman BC, Rameckers EA, Duysens J (2007) Children with congenital spastic hemiplegia obey Fitts’ Law in a visually guided tapping task. Exp Brain Res 177:431–439. doi:10.1007/s00221-006-0698-x

    Article  CAS  PubMed  Google Scholar 

  • Temprado JJ, Sleimen-Malkoun R, Lemaire P, Rey-Robert B, Retornaz F, Berton E (2013) Aging of sensorimotor processes: a systematic study in Fitts’ task. Exp Brain Res 228:105–116. doi:10.1007/s00221-013-3542-0

    Article  PubMed  Google Scholar 

  • Torres EB (2013) Signatures of movement variability anticipate hand speed according to levels of intent. Behav Brain Funct 9:10. doi:10.1186/1744-9081-9-10

    Article  PubMed Central  PubMed  Google Scholar 

  • Torres E, Andersen R (2006) Space-time separation during obstacle-avoidance learning in monkeys. J Neurophysiol 96:2613–2632. doi:10.1152/jn.0 0188.2006

    Article  PubMed  Google Scholar 

  • Torres EB, Brincker M, Isenhower RW et al (2013) Autism: the micro-movement perspective. Front Integr Neurosci 7:32. doi:10.3389/fnint.2013.00032

    PubMed  Google Scholar 

  • Weiss P, Stelmach GE, Adler CH, Waterman C (1996) Parkinsonian arm movements as altered by task difficulty. Parkinsonism Relat Disord 2:215–223

    Article  CAS  PubMed  Google Scholar 

  • Wilson PH, Maruff P, Ives S, Currie J (2001) Abnormalities of motor and praxis imagery in children with DCD. Hum Mov Sci 20:135–159

    Article  CAS  PubMed  Google Scholar 

  • Woodworth RS (1899) The accuracy of voluntary movement. The Macmillan Company, Columbia University, New York, London

    Google Scholar 

  • Wu J, Yang J, Honda T (2010) Fitts’ law holds for pointing movements under conditions of restricted visual feedback. Hum Mov Sci 29:882–892. doi:10.1016/j.humov.2010.03.009

    Article  PubMed  Google Scholar 

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Acknowledgments

This work is supported in part by a grant from the Cerebral Palsy International Research Foundation (CPIRF) and the Niarchos Foundation, by a grant from the VA Baltimore Medical Center contract 512-D05015 and by NIH Grant R01HD069776-02. Dr. K. P. Michmizos was partially supported by the Foundation for Education and European Culture. Dr. H. I. Krebs is a co-inventor in the MIT-held patent for the robotic device used in this work. He holds equity positions in Interactive Motion Technologies, the company that manufactures this type of technology under license to MIT.

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Correspondence to Konstantinos P. Michmizos.

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Michmizos, K.P., Krebs, H.I. Pointing with the ankle: the speed-accuracy trade-off. Exp Brain Res 232, 647–657 (2014). https://doi.org/10.1007/s00221-013-3773-0

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