The purpose of the present study was to examine the influence of anthropometric data on joint kinetics during gait. We particularly focused on the sensitivity of inverse dynamics solutions to the use of models for body segment parameters (BSP) estimation. Six often used estimation models were selected to provide BSP values for the three segments of the lower limb. Kinematics and dynamics were sampled from seven subjects performing barefoot gait at three different speeds. Joint kinetics were estimated with the bottom-up method using BSP values derived from each estimation model as anthropometric inputs. The BSP estimates were highly sensitive to the model used with deviations ranging from at least 9.73% up to 60%. Maximal variations of peak values for the hip joint flexion/extension moment during the swing phase were 20.11%. Hence, our findings suggest that the influence of BSP cannot be neglected. Observed deviations are especially due to the effect of varying simultaneously the mass, moments of inertia and the center of mass location values, according to the underlying relationship of interdependency linking each component. Considering both the differences found in joint kinetics and the level of accuracy of BSP models, evidence is provided that using multiple regression BSP estimation functions derived from Zatsiorsky and Seluyanov should be recommended to assess joint kinetics.

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The study of the correlations that may exist between neurophysiological signals is at the heart of modern techniques for data analysis in neuroscience. Wavelet coherence is a popular method to construct a time-frequency map that can be used to analyze the time-frequency correlations between two time series. Coherence is a normalized measure of dependence, for which it is possible to construct confidence intervals, and that is commonly considered as being more interpretable than the wavelet cross-spectrum (WCS). In this paper, we provide empirical and theoretical arguments to show that a significant level of wavelet coherence does not necessarily correspond to a significant level of dependence between random signals, especially when the number of trials is small. In such cases, we demonstrate that the WCS is a much better measure of statistical dependence, and a new statistical test to detect significant values of the cross-spectrum is proposed. This test clearly outperforms the limitations of coherence analysis while still allowing a consistent estimation of the time-frequency correlations between two non-stationary stochastic processes. Simulated data are used to investigate the advantages of this new approach over coherence analysis. The method is also applied to experimental data sets to analyze the time-frequency correlations that may exist between electroencephalogram (EEG) and surface electromyogram (EMG).

To investigate the strategies developed by the central nervous system to compensate for fatigue in muscles, we studied the changes in the relative mechanical contribution of the joint torques in a multi-joint movement following an isometric exhaustion test. Eighteen male subjects performed throws, moving the arm in the horizontal plane, before and after two fatigue protocols. Muscular fatigue was induced either in the distal (extensor digitorum communis) or in the proximal (triceps brachii) agonist muscle of the arm. The kinematic, kinetic and electromyographic parameters of the movement were analysed. The subjects produced two different coordinations following the fatigue protocols. In the distal fatigue condition, the wrist angular velocity was maintained by decreasing elbow active torque. In the proximal fatigue condition, the compensatory strategy involved increasing the contribution of the wrist. In fact, the control of elbow and wrist was modified in order to compensate for the different mechanical effects.

BackgroundStroke patients have impaired postural balance that increases the risk of falls and impairs their mobility. Assessment of postural balance is commonly carried out by recording centre of pressure (CoP) displacements, but the lack of data concerning reliability of these measures compromises their interpretation. The purpose of this study was to investigate the between-day reliability of six CoP-based variables, in order to provide i) reliability data for monitoring postural sway and weight-bearing asymmetry of stroke patients in clinical practice and ii) consistent assessment method of measurement error for applications in physical medicine and rehabilitation.MethodsPostural balance of 20 stroke patients was assessed in quiet standing on a force platform, in two sessions, 7 days apart. Six CoP-based variables were collected in eyes open and eyes closed conditions: postural sway was assessed with mean and standart deviation of CoP-velocity, CoP-velocity along the mediolateral and anteroposterior axes, and confidence ellipse area (CEAREA); weight-bearing asymmetry was assessed with mean CoP position along the mediolateral axis (CoPML). The intraclass correlation coefficient (ICC) was used to determine the level of agreement between test-retest. Small real difference (SRD), corresponding to the smallest change that indicates a real improvement for a single individual, was used to determine the extent of measurement error.ResultsICCs were satisfactory (>0.9) for all CoP-based variables, except for CEAREA in eyes open condition and CoPML (<0.8). The SRDs (eyes open/closed conditions) were: 6.1/9.5 mm.s-1 for mean velocity; 12.3/12.2 mm.s-1 for standard deviation of CoP-velocity; 3.6/5.5 mm.s-1 and 4.9/7.3 mm.s-1 for CoP-velocity in mediolateral and anteroposterior axes, respectively; 17.4/21.4 mm for CoPML. Because CEAREA showed heteroscedasticity of measurement error distribution, SRD (eyes open/closed conditions) was expressed as a percentage (121/75%) and a ratio (3.68/2.16) obtained after log-antilog procedure.ConclusionsIn clinical practice, the CoP-based velocity variables should be prefer to CEAREA to assess and monitor postural sway over time in hemiplegic stroke patients. The poor reliability of CoPML compromises its use to assess weight-bearing asymmetry. The procedure we used could be applied in reliability studies concerning other CoP-based variables or other biological variables in the field of physical medicine and rehabilitation.

The present study investigated the influence of additional loads on the knee net joint moment, flexor and extensor muscle group moments, and cocontraction index during a closed chain exercise. Loads of 8, 28, or 48 kg (i.e., respectively, 11.1+/-1.5%, 38.8+/-5.3%, and 66.4+/-9.0% of body mass) were added to subjects during dynamic half squats. The flexor and extensor muscular moments and the amount of cocontraction were estimated at the knee joint using an EMG-and-optimization model that includes kinematics, ground reaction, and EMG measurements as inputs. In general, our results showed a significant influence of the Load factor on the net knee joint moment, the extensor muscular moment, and the flexor muscle group moment (all Anova p<.05). Hence we confirmed an increase in muscle moments with increasing load and moreover, we also showed an original "more than proportional" evolution of the flexor and extensor muscle group moments relative to the knee net joint moment. An influence of the Phase (i.e., descent vs. ascent) factor was also seen, revealing different activation strategies from the central nervous system depending on the mode of contraction of the agonist muscle group. The results of the present work could find applications in clinical fields, especially for rehabilitation protocols.

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