Victoria Yule

Validation and Application of a Computational Model for Wrist and Hand Movements Using Surface Markers

A kinematic model is presented based on surface marker placement generating wrist, metacarpal arch, fingers and thumb movements. Standard calculations are used throughout the model and then applied to the specified marker placement. A static trial involving eight unimpaired participants was carried out to assess inter-rater reliability. The standard deviations across the data were comparable to manual goniometers. In addition, a test-retest trial of ten unimpaired participants is also reported to illustrate the variability of movement at the wrist joint, metacarpal arch, and index finger as an example of model output when repeating the same task many times. Light and heavyweight versions of the tasks are assessed and characteristics of individual movement strategies presented. The participant trial showed moderate correlation in radial/ulnar deviation of the wrist (r = 0.65), and strong correlation in both metacarpal arch joints (r = 0.75 and r = 0.85), the MCP (r = 0.79), and PIP (r = 0.87) joints of the index finger. The results indicate that individuals use repeated strategies of movement when lifting light and heavyweight versions of the same object, but showed no obvious repeated pattern of movement across the population.

Effect of gait cycle selection on EMG analysis during walking in adults and children with gait pathology.

This paper presents the results of a project to evaluate different methods of gait cycle selection on the analysis of electromyography recorded during gait. Electromyography (EMG) describes the electrical activity associated with the muscle and is often interpreted in gait analysis using a simultaneously obtained signal to identify phases of the gait cycle. Phase transitions are often selected manually from reference signals derived from additional instrumentation, such as pressure platforms, footswitches and video cameras. We propose two methods (automatic and semi-automatic) as an alternative to the more traditional manual selection, and analyse how the gait cycle selection affects the EMG analysis. To quantify the differences between the gait cycles obtained using each method and to classify each cycle, three indices have been introduced. The effect of the gait cycle selection has been evaluated with respect to the EMG step profiles and temporal gait descriptors. An asymptomatic adult, an asymptomatic child and two children with cerebral palsy were examined using telemetric EMG devices and pressure footswitches. The results obtained showed that the method of gait cycle selection did not have a major influence for the adult, but it altered considerably the analysis in the case of the children with cerebral palsy.

Changes in Hand Function with Age and Normative Unimpaired Scores when Measured with the Southampton Hand Assessment Procedure

Assessment of limitations in hand function due to impairment is commonplace in clinical practice and clinical research. When assessing impairment, it is useful to have an understanding of what comparative results an aged-match unimpaired participant population would generate and how the natural effects of an increase in age have on these results. Using the Southampton Hand Assessment Procedure (SHAP), this study assessed dominant hand function of 95 unimpaired participants between the ages of 18–75 years. The results extended available data from previous research and showed that the average SHAP score was 98 (± 3.3). The results indicate that there is a natural decline in hand function after the age of 65 years (p <0.001), which concurs with previously published studies using other assessments.

Application of complex wavelets for EMG analysis during gait of asymptomatic and pathological subjects

The wavelet transform seems particularly suited to analyse the electromyographic signal (EMG) during gait of asymptomatic and pathological subjects. Firstly, because physiologically the electrical activity generated by the muscles derives from a weighted sum of individual physiological components having limited support in time and in frequency. Secondly, because it is important to analyze muscle activity during specific phases of the cycle, and finally, because specific ranges of frequency are important pathological discriminators. In this paper we report the preliminary results of a project aimed at classifying asymptomatic and pathological subjects by analysing the complex wavelet transform of the EMG signal derived from two muscles (Tibialis Anterior and Lateral Gastrocnemius) during gait. An asymptomatic adult, an asymptomatic child and two pathological (cerebral palsy) children were examined using telemetric EMG devices and pressure footswitches. The results showed that the indices derived from the coefficient amplitudes (Gastrocnemius) and from frequency distribution (Tibialis) are capable of classifying the subjects into three groups. Despite the small number of cases analyzed, we believe that the relevance of the results deserves particular attention because of the novelty of the use of the wavelet transform for this application and of the potential application to monitor patients during interventions aimed at improving muscle behavior, particularly antispasticity treatment such as Botulinum Toxin injections.

THE EFFECT OF HANDEDNESS ON MOVEMENT STRATEGIES OF THE WRIST

INTRODUCTION Rehabilitation of upper limb impairment has historically used the same techniques and assessments of function regardless of hand dominance. Although previous studies of hand dominance have found no statistical difference in functional outcome [1], left-hand dominant individuals are found to adapt to right-handed tasks more easily and are more ambidextrous than their right-handed counterparts [2].