The effects of reactive and proactive motor decision-making strategies on the hand kinematics features in post-stroke patients
- Authors: Tumyalis A.V.1,2, Ivanov T.B.2,3, Ivanova G.E.3, Ivanova E.A.1, Kirichenko A.A.1, Ossadtchi A.E.1,2
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Affiliations:
- Laboratory of Medical Neurointerfaces and Artificial Intelligence of Federal State Budgetary Institution “Federal center of brain research and neurotechnologies”
- Center for Bioelectrical Interfaces of Higher School of Economics
- Federal Scientific and Clinical Center of Medical Rehabilitation and Balneology
- Issue: Vol 15, No 1 (2024)
- Pages: 43-53
- Section: Original Study Articles
- URL: https://journals.rcsi.science/clinpractice/article/view/257929
- DOI: https://doi.org/10.17816/clinpract624222
- ID: 257929
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Abstract
BACKGROUND: Motor disorders of the upper limbs often develop after stroke. The use of traditional methods to restore the motor functions of the upper limbs has limited effectiveness thus making the search and development of new rehabilitation approaches important. We propose to use a proactive selection of a purposeful movement as such an approach.
AIM: to investigate the influence of different strategies of the upper limb movement regulation on the motor decision making and hand kinematics parameters in stroke patients.
METHODS: Ten patients with stroke participated in the study during their hospital stay. They were divided into 2 groups and performed the task of selecting a movement target and performing arm movements for 10 sessions of 10 minutes each. The sessions were performed on separate days. When performing the task, patients selected one of the targets, either the near target or the distant one. The groups differed in the type of presentation of the distant target; the near target was stationary. The stimuli were presented on a touch screen arranged horizontally. A patient sat in front of the screen and placed the hand with a foam ball fixed in it on the starting area. The patient’s forearm was supported by means of a pendant. The patient selected a target to reach in each attempt and then performed the movement by swiping the ball on the touch screen. The frequency of the target selection to perform the movement, the range of the selected target, the latencies of the movement onset, the hand speed and acceleration, and the accuracy in reaching the target were assessed.
RESULTS: The results indicate that amidst the overall effects represented by a reduced movement on-set time [F (9.72)=8.59; p <0.001], a greater movement speed in reaching the distant target [F (9.72)=2.79; p=0.007], a lower selection rate [F (9.72)=2.78; p=0.008] and a reduced mean distance of the selected distant target [F (9.72)=2.19; p=0.033], the differences in the distant target presentation between the groups have an impact on the hand movement dynamics in patients. Presenting a target at a random distance results in a greater selected target distance [F (1.8)=17.04; p=0.003], and an increased hand speed [F (9.72)=3.03; p=0.004] compared to the adaptive presentation. There is also a greater decrease in the movement onset time [F (9.72)=2.71; p=0.009] in the group of patients with the adaptive presentation of the distant target compared to the group with the random presentation.
CONCLUSION: The differences in the target presentation strategy are reflected in the motor decision making and hand movement dynamics of stroke patients. A randomized range of target presentation results in a higher amplitude arm movement closer to the activation threshold of the stretch reflex. The results of the study may be useful for selecting the rehabilitation strategies for stroke patients.
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##article.viewOnOriginalSite##About the authors
Alexey V. Tumyalis
Laboratory of Medical Neurointerfaces and Artificial Intelligence of Federal State Budgetary Institution “Federal center of brain research and neurotechnologies”; Center for Bioelectrical Interfaces of Higher School of Economics
Email: atumyalis@gmail.com
ORCID iD: 0000-0002-8868-6312
SPIN-code: 4266-1634
PhD, Cand. Sci. (Biol.), Associate Professor
Russian Federation, Moscow; MoscowTimur B. Ivanov
Center for Bioelectrical Interfaces of Higher School of Economics; Federal Scientific and Clinical Center of Medical Rehabilitation and Balneology
Author for correspondence.
Email: timuriva@yandex.ru
Russian Federation, Moscow; Moscow
Galina E. Ivanova
Federal Scientific and Clinical Center of Medical Rehabilitation and Balneology
Email: ivanova.ge@fccps.ru
ORCID iD: 0000-0003-3180-5525
SPIN-code: 4049-4581
MD, PhD, Professor
Russian Federation, MoscowEkaterina A. Ivanova
Laboratory of Medical Neurointerfaces and Artificial Intelligence of Federal State Budgetary Institution “Federal center of brain research and neurotechnologies”
Email: kattyandiva@gmail.com
Russian Federation, Moscow
Andrey A. Kirichenko
Laboratory of Medical Neurointerfaces and Artificial Intelligence of Federal State Budgetary Institution “Federal center of brain research and neurotechnologies”
Email: vDRONikv@gmail.com
Russian Federation, Moscow
Alex E. Ossadtchi
Laboratory of Medical Neurointerfaces and Artificial Intelligence of Federal State Budgetary Institution “Federal center of brain research and neurotechnologies”; Center for Bioelectrical Interfaces of Higher School of Economics
Email: ossadtchi@gmail.com
ORCID iD: 0000-0001-8827-9429
SPIN-code: 5631-4743
PhD, Dr. Sci. (Physiology and Mathematics), Professor
Russian Federation, Moscow; MoscowReferences
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