International Journal of Internet, Broadcasting and Communication

The Institute of Internet, Broadcasting and Communication (한국인터넷방송통신학회)
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Design of a Brain Motor Control Ability Assessment System Using a Portable Tablet PC

  • Jongho Lee (Department of Clinical Engineering, Komatsu University) ;
  • Ayami Kondo (Department of Clinical Engineering, Komatsu University) ;
  • Shigeyuki Igarashi (Division of Health Sciences, Komatsu University) ;
  • Mayumi Tokuda (Division of Health Sciences, Komatsu University) ;
  • Hyeonseok Kim (Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego)
  • Received : 2024.10.01
  • Accepted : 2024.10.12
  • Published : 2024.11.30
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Abstract

We developed and validated a portable tablet-based system to assess brain motor control abilities by engaging participants in a manual tracking task with both visible and invisible targets, thereby eliciting feedback and feedforward control mechanisms. We measured the accuracy of these mechanisms using error terms, comparing 1) the performance of the dominant and non-dominant hands and 2) the intervals of feedback and feedforward control. We showed that the dominant hand demonstrated greater accuracy than the non-dominant hand, particularly when tracking a faster-moving visible target. Furthermore, the non-dominant hand transitioned from feedback to feedforward control at a slower target speed compared to the dominant hand. This suggests differential motor control processing between hands. We present this tablet-based system as an accessible and versatile tool for assessing feedback and feedforward control during target tracking tasks, based on feedback-error learning theory. It enables efficient analysis of motor development in children, motor decline in older adults, and stroke rehabilitation outcomes from a brain motor control perspective.

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References

  1. R. C. Miall, D. J. Weir, J. F. Stein, "Planning of movement parameters in a visuo-motor tracking task," Behav. Brain Res., Vol. 27, pp.1-8, 1988 DOI: https://doi.org/10.1016/0166-4328(88)90104-0.
  2. R. C. Miall, D. J. Weir, J. F. Stein, "Intermittency in human manual tracking tasks," J. Mot. Behav., Vol. 25, pp.53-63, 1993DOI: https://doi.org/10.1080/00222895.1993.9941639.
  3. H. Beppu, M. Suda, R. Tanaka, "Analysis of cerebellar motor disorders by visually guided elbow tracking movement," Brain, Vol. 107, pp.787-809, 1984 DOI: https://doi.org/10.1093/brain/107.3.787.
  4. Y. Hayashi, Y. Tamura, K. Sase, K. Sugawara, Y. Sawada, "Intermittently-visual Tracking Experiments Reveal the Roles of Error-correction and Predictive Mechanisms in the Human Visual-motor Control System," T. SICE, Vol. 46, pp.391-400, 2010 DOI: https://doi.org/10.9746/sicetr.46.391.
  5. J. Kim, J. Lee, S. Kakei, J. Kim, "Motor control characteristics for circular tracking movements of human wrist," Advanced Robotics, Vol. 31, pp.29-39, 2017 DOI: https://doi.org/10.1080/01691864.2016.1266121.
  6. W. Choi, J. Lee, N. Yanagihara, L. Li, J. Kim, "Development of a quantitative evaluation system for visuo-motor control in three-dimensional virtual reality space," Sci. Rep., Vol. 8, 13439, 2018 DOI: https://doi.org/10.1038/s41598-018-31758-y.
  7. W. Park, W. Choi, H. Jo, G. Lee, J. Kim, "Analysis of Control Characteristics between Dominant and NonDominant Hands by Transient Responses of Circular Tracking Movements in 3D Virtual Reality Space," Sensors, Vol. 20, 2020 DOI: https://doi.org/10.3390/s20123477.
  8. W. Choi, N. Yanagihara, L. Li, J. Kim, J. Lee, "Visuomotor control of intermittent circular tracking movements with visually guided orbits in 3D VR environment," PLoS ONE, Vol. 16, e0251371, 2021 DOI: https://doi.org/10.1371/journal.pone.0251371.
  9. R. C. Oldfield, "The assessment and analysis of handedness: the Edinburgh inventory," Neuropsychologia, Vol. 9, No. 1, pp. 97-113, 1971. DOI: https://doi.org/10.1016/0028-3932(71)90067-4
  10. T. Yamaguchi, N. Murayama, Y. Hayashida, T. Igasaki, K. Yamaguchi, "Upper limb movement function evaluation system for classification of ataxia -- Neural network model for classification of ataxia," IEICE Technical Report, Vol.104, pp.77-80, 2005.
  11. J. Tokunaga, "Quantitative assessment of motor coordination of ataxia by iPad® ," NIIGATA MEDICAL JOURNAL, Vol.129, pp.10-20, 2015.
  12. M. Kawato, H. Gomi, "The cerebellum and VOR/OKR learning models," Trends Neurosci., Vol.15, pp.445-453, 1992. DOI: https://doi.org/10.1016/0166-2236(92)90008-v.
  13. H. Imamizu, S. Miyauchi, T. Tamada, Y. Sasaki, R. Takino, B. Putz, T. Yoshioka, M. Kawato, "Human cerebellar activity reflecting an acquired internal model of a new tool," Nature, Vol.403, pp.192-195, 2000. DOI: https://doi.org/10.1038/35003194.
  14. B. Dexheimer, A. Przybyla, T. E. Murphy, S. Akpinar, R. Sainburg, "Reaction time asymmetries provide insight into mechanisms underlying dominant and non-dominant hand selection," Exp. Brain Res., Vol.240, pp.2791-2802, 2022. DOI: https://doi.org/10.1007/s00221-022-06451-2.
  15. H. Heuer, "Control of the dominant and nondominant hand: exploitation and taming of nonmuscular forces," Exp. Brain Res., Vol.178, pp.363-373, 2007. DOI: https://doi.org/10.1007/s00221-006-0747-5.
  16. D. V. Callaert, K. Vercauteren, R. Peeters, F. Tam, S. Graham, S. P. Swinnen, S. Sunaert, N. Wenderoth, "Hemispheric asymmetries of motor versus nonmotor processes during (visuo)motor control," Hum. Brain Mapp., Vol.32, pp.1311-1329, 2011. DOI: https://doi.org/10.1002/hbm.21110.
  17. A. Grosskopf, J. P. Kuhtz-Buschbeck, "Grasping with the left and right hand: a kinematic study," Exp. Brain Res., Vol.168, pp.230-240, 2006. DOI: https://doi.org/10.1007/s00221-005-0083-1.
  18. T. Oyama, "Manual asymmetry of time-delay effect on visual feedback in arm movements," In The 6th International Conference on Soft Computing and Intelligent Systems, and The 13th International Symposium on Advanced Intelligence Systems; IEEE, pp. 2015-2020, 2012.
  19. E. H. E. Walker, E. J. Perreault, "Arm dominance affects feedforward strategy more than feedback sensitivity during a postural task," Exp. Brain Res., Vol.233, pp.2001-2011, 2015. DOI: https://doi.org/10.1007/s00221-015-4271-3.
  20. J. M. Fine, K. L. Ward, E. L. Amazeen, "Manual coordination with intermittent targets: velocity information for prospective control," Acta Psychol (Amst), Vol.149, pp.24-31, 2014. DOI: https://doi.org/10.1016/j.actpsy.2014.02.012.
  21. J. Pola, H. J. Wyatt, "Target position and velocity: the stimuli for smooth pursuit eye movements," Vision Res., Vol.20, pp.523-534, 1980. DOI: https://doi.org/doi:10.1016/0042-6989(80)90127-3.
  22. A. Tavassoli, D. L. Ringach, "Dynamics of smooth pursuit maintenance," J. Neurophysiol., Vol.102, 110-118, 2009. DOI: https://doi.org/10.1152/jn.91320.2008.
  23. T. Ekaterina and S. Lee, "Data Acquisition System based on Hand Tracking to evaluate Children's Cognitive Abilities.," IJIBC, Vol. 14, No. 3, Jun 2022. DOI: http://dx.doi.org/10.7236/IJIBC.2022.14.3.108
  24. N. Shimoda, J. Lee, M. Kodama, S. Kakei, and Y. Masakado, "Quantitative evaluation of age-related decline in control of preprogramed movement," PLoS ONE, Vol. 12, no. 11, e0188657, 2017. DOI: https://doi.org/10.1371/journal.pone.0188657.