Individuals with multiple sclerosis (MS) often have poor balance control that is especially apparent during dynamic tasks such as gait initiation (GI). The purpose of this study was to investigate how balance symptoms due to MS alter spatiotemporal variables, coordination, and temporal margins within the stability boundary during gait initiation. Twelve women with MS (Expanded Disability Status Scale [EDSS] mean = 4.0, SD = 1.4) and 12 women without MS (control group) initiated gait at their preferred speed. MS participants attained a slower anterior velocity because of smaller anterior center of mass displacements and took longer to complete the initiation of gait than the control group. MS participants exhibited a smaller posterior shift in center of pressure during GI and stepped with a longer dual support time than the control group. However, these changes may be due to differences in initiation velocity. Relative timing analysis showed invariance in postural and locomotor phases of gait initiation between groups. The MS group showed different coordination between anterior-posterior and medio-lateral center of pressure components while increasing temporal margins to the posterior and lateral stability boundaries in comparison with the control group. Overall, during gait initiation at their preferred speed the MS participants adopted a functional strategy that produces lower speed and reduced proximity to the stability boundaries prior to stepping.
Jebb G. Remelius, Joseph Hamill, Jane Kent-Braun and Richard E.A. Van Emmerik
Ricardo Pires, Thays Falcari, Alexandre B. Campo, Bárbara C. Pulcineli, Joseph Hamill and Ulysses Fernandes Ervilha
The aim of this study is to use a support vector machine algorithm to identify and classify shod and barefoot running as well as rearfoot and forefoot landings. Ten habitually shod runners ran at self-selected speed. Thigh and leg muscle surface electromyography were recorded. Discrete wavelet transformation and fast Fourier transformation were used for the assembly of vectors for training and classification of a support vector machine. Using the fast Fourier transformation coefficients for the gastrocnemius and tibialis anterior muscles presented the best results for differentiating between rearfoot/forefoot running in the window before foot-floor contact possibly due to these muscles’ critical role in determining which part of the foot will first touch the floor. The classification rate was 76% and 67%, respectively, with a probability of being random of 0.5% and 4%, respectively. For the same terms and conditions of classification, the discrete wavelet transformation produced a reduction in the percentage of correctness of 60% and 53% with a probability of having reached these levels randomly of 15% and 35%. In conclusion, based on electromyographic signals, the use a fast Fourier transformation to train a support vector machine was a better option to differentiate running forefoot/rearfoot than to use the discrete wavelet transformation. Shod/barefoot running that could not be differentiated.
Richard E.A. Van Emmerik, Michael T. Rosenstein, William J. McDermott and Joseph Hamill
Nonlinear dynamics and dynamical systems approaches and methodologies are increasingly being implemented in biomechanics and human movement research. Based on the early insights of Nicolai Bernstein (1967), a significantly different outlook on the movement control “problem” over the last few decades has emerged. From a focus on relatively simple movements has arisen a research focus with the primary goal to study movement in context, allowing the complexity of patterns to emerge. The approach taken is that the control of multiple degrees-of-freedom systems is not necessarily more difficult or complex than that of systems only comprising a few degrees of freedom. Complex patterns and dynamics might not require complex control structures. In this paper we present a tutorial overview of the mathematical underpinnings of nonlinear dynamics and some of its basic analysis tools. This should provide the reader with a basic level of understanding about the mathematical principles and concepts underlying pattern stability and change. This will be followed by an overview of dynamical systems approaches in the study of human movement. Finally, we discuss recent progress in the application of nonlinear dynamical techniques to the study of human locomotion, with particular focus on relative phase techniques for the assessment of coordination.
Christine D. Pollard, Bryan C. Heiderscheit, Richard E.A. van Emmerik and Joseph Hamill
The purpose of this study was to determine if gender differences exist in the variability of various lower extremity (LE) segment and joint couplings during an unanticipated cutting maneuver. 3-D kinematics were collected on 24 college soccer players (12 M, 12 F) while each performed the cutting maneuver. The following intralimb couplings were studied: thigh rotation (rot)/leg rot; thigh abduction-adduction/leg abd-add; hip abd-add/knee rot; hip rot/knee abd-add; knee flexion-extension/knee rot; knee flx-ext/hip rot. A vector-coding technique applied to angle-angle plots was used to quantify the coordination of each coupling. The average between-trial standard deviation of the coordination pattern during the initial 40% of stance was used to indicate the coordination variability. One-tailed t-tests were used to determine differences between genders in coordination variability for each coupling. Women had decreased variability in four couplings: 32% less thigh rot/leg rot variability; 40% less thigh abd-add/leg abd-add variability; 46% less knee flx-ext/knee rot variability; and 44% less knee flx-ext/hip rot variability. These gender differences in LE coordination variability may be associated with the increased incidence of ACL injury in women. If women exhibit less flexible coordination patterns during competition, they may be less able to adapt to the environmental perturbations experienced during sports. These perturbations applied to a less flexible system may result in ligament injury.
Jeffrey M. Haddad, Jeff L. Gagnon, Christopher J. Hasson, Richard E.A. Van Emmerik and Joseph Hamill
Postural stability has traditionally been examined through spatial measures of the center of mass (CoM) or center of pressure (CoP), where larger amounts of CoM or CoP movements are considered signs of postural instability. However, for stabilization, the postural control system may utilize additional information about the CoM or CoP such as velocity, acceleration, and the temporal margin to a stability boundary. Postural time-to-contact (TtC) is a variable that can take into account this additional information about the CoM or CoP. Postural TtC is the time it would take the CoM or CoP, given its instantaneous trajectory, to contact a stability boundary. This is essentially the time the system has to reverse any perturbation before stance is threatened. Although this measure shows promise in assessing postural stability, the TtC values derived between studies are highly ambiguous due to major differences in how they are calculated. In this study, various methodologies used to assess postural TtC were compared during quiet stance and induced-sway conditions. The effects of the different methodologies on TtC values will be assessed, and issues regarding the interpretation of TtC data will also be discussed.