No abstract

TAR surgery improved muscle function (torque, EMG intensity) in osteoarthritic ankles. However, after 1 year, patients did not reach the level of the contralateral healthy leg, and the EMG frequency remained unchanged.

No abstract

Functional magnetic resonance (MR) MR imaging (fMRI) with blood-oxygenation-level-dependent (BOLD) contrast localizes neuronal processing of cognitive paradigms. As magnetic resonance signal responses are small, functional mapping requires statistical analysis of temporally averaged image data. Although voxels activating at the paradigm frequency can be identified from the Fourier power spectrum, such analyses collapse the temporal information that is useful to establish consistency of responses during the paradigm. The design of a set of nonorthogonal wavelets of specified frequency resolution within the power spectrum was investigated for extracting desired frequency responses from the noisy signal intensity of individual voxels. These wavelets separate the low-frequency cognitive response to the paradigm from the respiratory and cardiac responses at higher frequencies. The retention of the temporal information, possible by wavelet analysis, allows the MR signal changes to be compared to changes in behavioral responses over the duration of an entire paradigm. The amplitude and time delay of the wavelet specified by the paradigm identify quantitatively the size of the MR signal change and the temporal delay of the hemodynamic BOLD response, respectively. This specified-resolution wavelet analysis was demonstrated for individual voxels and maps through the frontal eye fields using a visually guided saccade paradigm.

The comparison of electromyograms represents a challenge for data analysis. The aim of the project was to present a method that uses a minimal computational effort to resolve small but significant changes in the muscular activity that occur while walking with and without a knee brace. The wavelet transformed electromyograms were represented as intensity patterns that resolve the power of the signal in time and frequency. The intensity pattern of each electromyogram defines single points in a pattern space. The distance between these points in pattern space were used to detect and show the separation between the groups of electromyograms that were recorded while walking with and without a knee brace. The method proposes a distance versus angle representation to visually discriminate the intensity patterns. Once it has been shown that the differences are statistically significant, one can visualize the result in a difference intensity pattern that indicates at what time and at what frequency the electromyograms vary between the two conditions tested. It is to be expected that interventions that are more intrusive than a knee brace will reveal even more distinct differences.