Gaze and Movement Assessment (GaMA): Inter-site validation of a visuomotor upper limb functional protocol


Autoři: Heather E. Williams aff001;  Craig S. Chapman aff002;  Patrick M. Pilarski aff003;  Albert H. Vette aff001;  Jacqueline S. Hebert aff003
Působiště autorů: Department of Mechanical Engineering, Faculty of Engineering, University of Alberta, Edmonton, Alberta, Canada aff001;  Faculty of Kinesiology, Sport, and Recreation, University of Alberta, Edmonton, Alberta, Canada aff002;  Department of Medicine, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada aff003;  Department of Biomedical Engineering, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada aff004;  Glenrose Rehabilitation Hospital, Alberta Health Services, Edmonton, Alberta, Canada aff005
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
doi: 10.1371/journal.pone.0219333

Souhrn

Background

Successful hand-object interactions require precise hand-eye coordination with continual movement adjustments. Quantitative measurement of this visuomotor behaviour could provide valuable insight into upper limb impairments. The Gaze and Movement Assessment (GaMA) was developed to provide protocols for simultaneous motion capture and eye tracking during the administration of two functional tasks, along with data analysis methods to generate standard measures of visuomotor behaviour. The objective of this study was to investigate the reproducibility of the GaMA protocol across two independent groups of non-disabled participants, with different raters using different motion capture and eye tracking technology.

Methods

Twenty non-disabled adults performed the Pasta Box Task and the Cup Transfer Task. Upper body and eye movements were recorded using motion capture and eye tracking, respectively. Measures of hand movement, angular joint kinematics, and eye gaze were compared to those from a different sample of twenty non-disabled adults who had previously performed the same protocol with different technology, rater and site.

Results

Participants took longer to perform the tasks versus those from the earlier study, although the relative time of each movement phase was similar. Measures that were dissimilar between the groups included hand distances travelled, hand trajectories, number of movement units, eye latencies, and peak angular velocities. Similarities included all hand velocity and grip aperture measures, eye fixations, and most peak joint angle and range of motion measures.

Discussion

The reproducibility of GaMA was confirmed by this study, despite a few differences introduced by learning effects, task demonstration variation, and limitations of the kinematic model. GaMA accurately quantifies the typical behaviours of a non-disabled population, producing precise quantitative measures of hand function, trunk and angular joint kinematics, and associated visuomotor behaviour. This work advances the consideration for use of GaMA in populations with upper limb sensorimotor impairment.

Klíčová slova:

Eye movements – Eyes – Kinematics – Musculoskeletal system – Skeletal joints


Zdroje

1. Lang CE, Wagner JM, Bastian AJ, Hu Q, Edwards DF, Sahrmann SA, et al. Deficits in grasp versus reach during acute hemiparesis. Exp Brain Res. 2005;166: 126–136. doi: 10.1007/s00221-005-2350-6 16021431

2. Metzger AJ, Dromerick AW, Holley RJ, Lum PS. Characterization of compensatory trunk movements during prosthetic upper limb reaching tasks. Arch Phys Med Rehabil. 2012;93: 2029–2034. doi: 10.1016/j.apmr.2012.03.011 22449551

3. Mateo S, Roby-Brami A, Reilly KT, Rossetti Y, Collet C, Rode G. Upper limb kinematics after cervical spinal cord injury: A review. J Neuroeng Rehabil. 2015;12: 9. doi: 10.1186/1743-0003-12-9 25637224

4. Shumway-Cook A, Woollacott MH. Motor control: Translating research into clinical practice. 4th ed. Motor Control: Translating Research into Clinical Practice: Fourth Edition. Philadelphia, USA: Wolters Kluwer Health/Lippincott Williams & Wilkins; 2012.

5. Stokes EK. Rehabilitation Outcome Measures. Rehabilitation Outcome Measures. Edinburgh, UK; 2011.

6. Velstra IM, Ballert CS, Cieza A. A Systematic Literature Review of Outcome Measures for Upper Extremity Function Using the International Classification of Functioning, Disability, and Health as Reference. PM&R. 2011;3: 846–860. doi: 10.1016/j.pmrj.2011.03.014 21944302

7. Valevicius AM, Boser QA, Lavoie EB, Murgatroyd GS, Pilarski PM, Chapman CS, et al. Characterization of normative hand movements during two functional upper limb tasks. PLoS One. 2018;13: e0199549. doi: 10.1371/journal.pone.0199549 29928022

8. Valevicius AM, Boser QA, Lavoie EB, Chapman CS, Pilarski PM, Hebert JS, et al. Characterization of normative angular joint kinematics during two functional upper limb tasks. Gait Posture. 2019;69: 176–186. doi: 10.1016/j.gaitpost.2019.01.037 30769260

9. Lavoie EB, Valevicius AM, Boser QA, Kovic O, Vette AH, Pilarski PM, et al. Using synchronized eye and motion tracking to determine high-precision eye-movement patterns during object-interaction tasks. J Vis. 2018;18: 18. doi: 10.1167/18.6.18 30029228

10. Cognolato M, Atzori M, Müller H. Head-mounted eye gaze tracking devices: An overview of modern devices and recent advances. J Rehabil Assist Technol Eng. 2018;5: 1–13. doi: 10.1177/2055668318773991 31191938

11. Cacho EWA, De Oliveira R, Ortolan RL, Varoto R, Cliquet A. Upper limb assessment in tetraplegia: Clinical, functional and kinematic correlations. Int J Rehabil Res. 2011;34: 65–72. doi: 10.1097/MRR.0b013e32833d6cf3 20805758

12. Chang JJ, Wu TI, Wu WL, Su FC. Kinematical measure for spastic reaching in children with cerebral palsy. Clin Biomech. 2005;20: 381–8. doi: 10.1016/j.clinbiomech.2004.11.015 15737445

13. Jaspers E, Feys H, Bruyninckx H, Harlaar J, Molenaers G, Desloovere K. Upper limb kinematics: Development and reliability of a clinical protocol for children. Gait Posture. 2011;33: 279–85. doi: 10.1016/j.gaitpost.2010.11.021 21196120

14. Lobo-Prat J, Font-Llagunes JM, Gómez-Pérez C, Medina-Casanovas J, Angulo-Barroso RM. New biomechanical model for clinical evaluation of the upper extremity motion in subjects with neurological disorders: An application case. Comput Methods Biomech Biomed Engin. 2014;17: 1144–56. doi: 10.1080/10255842.2012.738199 23181596

15. Reid S, Elliott C, Alderson J, Lloyd D, Elliott B. Repeatability of upper limb kinematics for children with and without cerebral palsy. Gait Posture. 2010;32: 10–7. doi: 10.1016/j.gaitpost.2010.02.015 20430623

16. Rönnqvist L, Rösblad B. Kinematic analysis of unimanual reaching and grasping movements in children with hemiplegic cerebral palsy. Clin Biomech. 2007;22: 165–75. doi: 10.1016/j.clinbiomech.2006.09.004 17070630

17. Vanezis A, Robinson MA, Darras N. The reliability of the ELEPAP clinical protocol for the 3D kinematic evaluation of upper limb function. Gait Posture. 2015;41: 431–9. doi: 10.1016/j.gaitpost.2014.11.007 25534948

18. Yang N, Zhang M, Huang C, Jin D. Synergic analysis of upper limb target-reaching movements. J Biomech. 2002;35: 739–46. doi: 10.1016/s0021-9290(02)00018-0 12020993

19. Valevicius AM, Jun PY, Hebert JS, Vette AH. Use of optical motion capture for the analysis of normative upper body kinematics during functional upper limb tasks: A systematic review. J Electromyogr Kinesiol. 2018;40: 1–15. doi: 10.1016/j.jelekin.2018.02.011 29533202

20. Boser QA, Valevicius AM, Lavoie EB, Chapman CS, Pilarski PM, Hebert JS, et al. Cluster-based upper body marker models for three-dimensional kinematic analysis: Comparison with an anatomical model and reliability analysis. J Biomech. 2018;72: 228–234. doi: 10.1016/j.jbiomech.2018.02.028 29530500

21. Land MF, Hayhoe M. In what ways do eye movements contribute to everyday activities? Vision Res. 2001;41: 3559–65. doi: 10.1016/s0042-6989(01)00102-x 11718795

22. Slezák P, Waczulíková I. Reproducibility and repeatability. Physiol Res. 2011;60: 203–204. 21469910

23. Pinzone O, Schwartz MH, Thomason P, Baker R. The comparison of normative reference data from different gait analysis services. Gait Posture. 2014;40: 286–290. doi: 10.1016/j.gaitpost.2014.03.185 24831115

24. Schaefer SY, Saba A, Baird JF, Kolar MB, Duff K, Stewart JC. Within-session practice effects in the jebsen hand function test (JHFT). Am J Occup Ther. 2018;72: 7206345010p1–7206345010p5. doi: 10.5014/ajot.2018.024745 30760402

25. Darling WG, Cooke JD. Changes in the variability of movement trajectories with practice. J Mot Behav. 1987;19: 291–309. doi: 10.1080/00222895.1987.10735414 14988049

26. Shmuelof L, Krakauer JW, Mazzoni P. How is a motor skill learned? Change and invariance at the levels of task success and trajectory control. J Neurophysiol. 2012;108: 578–594. doi: 10.1152/jn.00856.2011 22514286

27. Williams JG. Visual Demonstration and Movement Production: Effects of Timing Variations in a Model’s Action. Percept Mot Skills. 2011;68: 891–896. doi: 10.2466/pms.1989.68.3.891 2748306

28. McGinley JL, Baker R, Wolfe R, Morris ME. The reliability of three-dimensional kinematic gait measurements: A systematic review. Gait Posture. 2009;29: 360–369. doi: 10.1016/j.gaitpost.2008.09.003 19013070

29. Schwartz MH, Trost JP, Wervey RA. Measurement and management of errors in quantitative gait data. Gait Posture. 2004;20: 196–203. doi: 10.1016/j.gaitpost.2003.09.011 15336291


Článek vyšel v časopise

PLOS One


2019 Číslo 12