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Shaklai, S., Mimouni-Bloch, A., Levin, M., & Friedman, J. (2017). Development of finger force coordination in children. Experimental Brain Research, 235(12), 3709–3720.
Abstract: Coordination is often observed as body parts moving together. However, when producing force with multiple fingers, the optimal coordination is not to produce similar forces with each finger, but rather for each finger to correct mistakes of other fingers. In this study, we aim to determine whether and how this skill develops in children aged 4-12 years. We measured this sort of coordination using the uncontrolled manifold hypothesis (UCM). We recorded finger forces produced by 60 typically developing children aged between 4 and 12 years in a finger-pressing task. The children controlled the height of an object on a screen by the total amount of force they produced on force sensors. We found that the synergy index, a measure of the relationship between “good” and “bad” variance, increased linearly as a function of age. This improvement was achieved by a selective reduction in “bad” variance rather than an increase in “good” variance. We did not observe differences between males and females, and the synergy index was not able to predict outcomes of upper limb behavioral tests after controlling for age. As children develop between the ages of 4 and 12 years, their ability to produce negative covariation between their finger forces improves, likely related to their improved ability to perform dexterous tasks.
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Mimouni-Bloch, A., Shaklai, S., Levin, M., Ingber, M., Karolitsky, T., Grunbaum, S., et al. (2023). Developmental and acquired brain injury have opposite effects on finger coordination in children. Front. Hum. Neurosci., 17, 1083304.
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Merdler, T., Liebermann, D. G., Levin, M. F., & Berman, S. (2013). Arm-plane representation of shoulder compensation during pointing movements in patients with stroke. J Electromyogr Kinesiol, 23(4), 938–947.
Abstract: Improvements in functional motor activities are often accompanied by motor compensations to overcome persistent motor impairment in the upper limb. Kinematic analysis is used to objectively quantify movement patterns including common motor compensations such as excessive trunk displacement during reaching. However, a common motor compensation to assist reaching, shoulder abduction, is not adequately characterized by current motion analysis approaches. We apply the arm-plane representation that accounts for the co-variation between movements of the whole arm, and investigate its ability to identify and quantify compensatory arm movements in stroke subjects when making forward arm reaches. This method has not been previously applied to the analysis of motion deficits. Sixteen adults with right post-stroke hemiparesis and eight healthy age-matched controls reached in three target directions (14 trials/target; sampling rate: 100Hz). Arm-plane movement was validated against endpoint, joint, and trunk kinematics and compared between groups. In stroke subjects, arm-plane measures were correlated with arm impairment (Fugl-Meyer Assessment) and ability (Box and Blocks) scores and were more sensitive than clinical measures to detect mild motor impairment. Arm-plane motion analysis provides new information about motor compensations involving the co-variation of shoulder and elbow movements that may help to understand the underlying motor deficits in patients with stroke.
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Liebermann, D. G., Levin, M. F., McIntyre, J., Weiss, P. L., & Berman, S. (2010). Arm path fragmentation and spatiotemporal features of hand reaching in healthy subjects and stroke patients. Conf Proc IEEE Eng Med Biol Soc, 2010, 5242–5245.
Abstract: Arm motion in healthy humans is characterized by smooth and relatively short paths. The current study focused on 3D reaching in stroke patients. Sixteen right-hemiparetic stroke patients and 8 healthy adults performed 42 reaching movements towards 3 visual targets located at an extended arm distance. Performance was assessed in terms of spatial and temporal features of the movement; i.e., hand path, arm posture and smoothness. Differences between groups and within subjects were hypothesized for spatial and temporal aspects of reaching under the assumption that both are independent. As expected, upper limb motion of patients was characterized by longer and jerkier hand paths and slower speeds. Assessment of the number of sub-movements within each movement did not clearly discriminate between groups. Principal component analyses revealed specific clusters of either spatial or temporal measures, which accounted for a large proportion of the variance in patients but not in healthy controls. These findings support the notion of a separation between spatial and temporal features of movement. Stroke patients may fail to integrate the two aspects when executing reaching movements towards visual targets.
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Liebermann, D. G., Berman, S., Weiss, P. L. T., & Levin, M. F. (2012). Kinematics of reaching movements in a 2-d virtual environment in adults with and without stroke. IEEE Trans Neural Syst Rehabil Eng, 20(6), 778–787.
Abstract: Virtual reality environments are increasingly being used for upper limb rehabilitation in poststroke patients. Our goal was to determine if arm reaching movements made in a 2-D video-capture virtual reality environment are similar to those made in a comparable physical environment. We compared arm and trunk kinematics for reaches made with the right, dominant arm to three targets (14 trials per target) in both environments by 16 adults with right poststroke hemiparesis and by eight healthy age-matched controls. Movement kinematics were recorded with a three-camera optoelectronic system at 100 samples/s. Reaching movements made by both control and stroke subjects were affected by viewing the targets in the video-capture 2-D virtual environment. Movements were slower, shorter, less straight, less accurate and involved smaller ranges of shoulder and elbow joint excursions for target reaches in the virtual environment compared to the physical environment in all subjects. Thus, there was a decrease in the overall movement quality for movements made in the 2-D virtual environment. This suggests that 2-D video-capture virtual reality environments should be used with caution when the goal of the rehabilitation program is to improve the quality of movement patterns of the upper limb.
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