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Liebermann, D. G., Krasovsky, T., & Berman, S. (2008). Planning maximally smooth hand movements constrained to nonplanar workspaces. J Mot Behav, 40(6), 516–531.
Abstract: The article characterizes hand paths and speed profiles for movements performed in a nonplanar, 2-dimensional workspace (a hemisphere of constant curvature). The authors assessed endpoint kinematics (i.e., paths and speeds) under the minimum-jerk model assumptions and calculated minimal amplitude paths (geodesics) and the corresponding speed profiles. The authors also calculated hand speeds using the 2/3 power law. They then compared modeled results with the empirical observations. In all, 10 participants moved their hands forward and backward from a common starting position toward 3 targets located within a hemispheric workspace of small or large curvature. Comparisons of modeled observed differences using 2-way RM-ANOVAs showed that movement direction had no clear influence on hand kinetics (p < .05). Workspace curvature affected the hand paths, which seldom followed geodesic lines. Constraining the paths to different curvatures did not affect the hand speed profiles. Minimum-jerk speed profiles closely matched the observations and were superior to those predicted by 2/3 power law (p < .001). The authors conclude that speed and path cannot be unambiguously linked under the minimum-jerk assumption when individuals move the hand in a nonplanar 2-dimensional workspace. In such a case, the hands do not follow geodesic paths, but they preserve the speed profile, regardless of the geometric features of the workspace.
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Levin, M. F., Banina, M. C., Frenkel-Toledo, S., Berman, S., Soroker, N., Solomon, J. M., et al. (2018). Personalized upper limb training combined with anodal-tDCS for sensorimotor recovery in spastic hemiparesis: study protocol for a randomized controlled trial. Trials, 19(1), 7.
Abstract: BACKGROUND: Recovery of voluntary movement is a main rehabilitation goal. Efforts to identify effective upper limb (UL) interventions after stroke have been unsatisfactory. This study includes personalized impairment-based UL reaching training in virtual reality (VR) combined with non-invasive brain stimulation to enhance motor learning. The approach is guided by limiting reaching training to the angular zone in which active control is preserved (“active control zone”) after identification of a “spasticity zone”. Anodal transcranial direct current stimulation (a-tDCS) is used to facilitate activation of the affected hemisphere and enhance inter-hemispheric balance. The purpose of the study is to investigate the effectiveness of personalized reaching training, with and without a-tDCS, to increase the range of active elbow control and improve UL function. METHODS: This single-blind randomized controlled trial will take place at four academic rehabilitation centers in Canada, India and Israel. The intervention involves 10 days of personalized VR reaching training with both groups receiving the same intensity of treatment. Participants with sub-acute stroke aged 25 to 80 years with elbow spasticity will be randomized to one of three groups: personalized training (reaching within individually determined active control zones) with a-tDCS (group 1) or sham-tDCS (group 2), or non-personalized training (reaching regardless of active control zones) with a-tDCS (group 3). A baseline assessment will be performed at randomization and two follow-up assessments will occur at the end of the intervention and at 1 month post intervention. Main outcomes are elbow-flexor spatial threshold and ratio of spasticity zone to full elbow-extension range. Secondary outcomes include the Modified Ashworth Scale, Fugl-Meyer Assessment, Streamlined Wolf Motor Function Test and UL kinematics during a standardized reach-to-grasp task. DISCUSSION: This study will provide evidence on the effectiveness of personalized treatment on spasticity and UL motor ability and feasibility of using low-cost interventions in low-to-middle-income countries. TRIAL REGISTRATION: ClinicalTrials.gov, ID: NCT02725853 . Initially registered on 12 January 2016.
Keywords: Neurorehabilitation; Spasticity; Spatial threshold; Stroke; tDCS
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Liebermann, D. G., Buchman, A. S., & Franks, I. M. (2006). Enhancement of motor rehabilitation through the use of information technologies. Clin Biomech (Bristol, Avon), 21(1), 8–20.
Abstract: The recent development of information technologies has dramatically increased the tools available for facilitating motor rehabilitation. This review focuses on technologies which can be used to augment movement-related information both to patients as well as to their therapists. A brief outline of the motor system emphasizes the role of spinal motor neurons in the control of voluntary movement and rehabilitative efforts. Technologies which induce passive motion to stimulate spinal motor output as well as technologies that stimulate active voluntary movements are discussed. Finally, we review technologies and notational methods that can be used to quantify and assess the quality of movement for evaluating the efficacy of motor rehabilitation efforts. We conclude that stronger evidence is necessary to determine the applicability of the wide range of technologies now available to clinical rehabilitation efforts.
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Liebermann, D. G., Katz, L., Hughes, M. D., Bartlett, R. M., McClements, J., & Franks, I. M. (2002). Advances in the application of information technology to sport performance. J Sports Sci, 20(10), 755–769.
Abstract: This paper overviews the diverse information technologies that are used to provide athletes with relevant feedback. Examples taken from various sports are used to illustrate selected applications of technology-based feedback. Several feedback systems are discussed, including vision, audition and proprioception. Each technology described here is based on the assumption that feedback would eventually enhance skill acquisition and sport performance and, as such, its usefulness to athletes and coaches in training is critically evaluated.
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Liebermann, D. G., Biess, A., Friedman, J., Gielen, C. C. A. M., & Flash, T. (2006). Intrinsic joint kinematic planning. I: reassessing the Listing's law constraint in the control of three-dimensional arm movements. Exp Brain Res, 171(2), 139–154.
Abstract: This study tested the validity of the assumption that intrinsic kinematic constraints, such as Listing's law, can account for the geometric features of three-dimensional arm movements. In principle, if the arm joints follow a Listing's constraint, the hand paths may be predicted. Four individuals performed 'extended arm', 'radial', 'frontal plane', and 'random mixed' movements to visual targets to test Listing's law assumption. Three-dimensional rotation vectors of the upper arm and forearm were calculated from three-dimensional marker data. Data fitting techniques were used to test Donders' and Listing's laws. The coefficient values obtained from fitting rotation vectors to the surfaces described by a second-order equation were analyzed. The results showed that the coefficients that represent curvature and twist of the surfaces were often not significantly different from zero, particularly not during randomly mixed and extended arm movements. These coefficients for forearm rotations were larger compared to those for the upper arm segment rotations. The mean thickness of the rotation surfaces ranged between approximately 1.7 degrees and 4.7 degrees for the rotation vectors of the upper arm segment and approximately 2.6 degrees and 7.5 degrees for those of the forearm. During frontal plane movements, forearm rotations showed large twist scores while upper arm segment rotations showed large curvatures, although the thickness of the surfaces remained low. The curvatures, but not the thicknesses of the surfaces, were larger for large versus small amplitude radial movements. In conclusion, when examining the surfaces obtained for the different movement types, the rotation vectors may lie within manifolds that are anywhere between curved or twisted manifolds. However, a two-dimensional thick surface may roughly represent a global arm constraint. Our findings suggest that Listing's law is implemented for some types of arm movement, such as pointing to targets with the extended arm and during radial reaching movements.
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