Movement parameters that distinguish between voluntary movements and levodopa-induced dyskinesia in Parkinson's disease.

Contains fulltext : 83236.pdf (author's version ) (Open Access)It is well known that long-term use of levodopa by patients with Parkinson's disease causes dyskinesia. Several methods have been proposed for the automatic, unsupervised detection and classification of levodopa induced dyskinesia. Recently, we have demonstrated that neural networks are highly successful to detect dyskinesia and to distinguish dyskinesia from voluntary movements. The aim of this study was to use the trained neural networks to extract parameters, which are important to distinguish between dyskinesia and voluntary movements.Thirteen patients were continuously monitored in a home-like situation performing in about 35 daily life tasks for a period of approximately 2.5 h. Behavior of the patients was measured using triaxial accelerometers, which were placed at six different positions of the body. A neural network was trained to assess the severity of dyskinesia. The neural network was able to assess the severity of dyskinesia and could distinguish dyskinesia from voluntary movements in daily life. For the trunk and the leg, the important parameters appeared to be the percentage of time that the trunk or leg was moving and the standard deviation of the segment velocity of the less dyskinetic leg. For the arm, the combination of the percentage of time, that the wrist was moving, and the percentage of time, that a patient was sitting, explained the largest part of the variance of the output. Dyskinesia differs from voluntary movements in the fact that dyskinetic movements tend to have lower frequencies than voluntary movements and in the fact that movements of different body segments are not well coordinated in dyskinesia

Interaction between gaze and pointing toward remembered visual targets.

Contains fulltext : 83235.pdf (preprint version ) (Open Access)We examined the role of gaze in a task where subjects had to reproduce the position of a remembered visual target with the tip of the index finger, referred to as pointing. Subjects were tested in 3 visual feedback conditions: complete darkness (dark), complete darkness with visual feedback of the finger position (finger), and with vision of a well-defined environment and feedback of the finger position (frame). Pointing accuracy increases with feedback about the finger or visual environment. In the finger and frame conditions, the 95% confidence regions of the variable errors have an ellipsoidal distribution with the main axis oriented toward the subjects' head. During the 1-s period when the target is visible, gaze is almost on target. However, gaze drifts away from the target relative to the subject in the delay period after target disappearance. In the finger and frame conditions, gaze returns toward the remembered target during pointing. In all 3 feedback conditions, the correlations between the variable errors of gaze and pointing position increase during the delay period, reaching highly significant values at the time of pointing. Our results demonstrate that gaze affects the accuracy of pointing. We conclude that the covariance between gaze and pointing position reflects a common drive for gaze and arm movements and an effect of gaze on pointing accuracy at the time of pointing. Previous studies interpreted the orientation of variable errors as indicative for a frame of reference used for pointing. Our results suggest that the orientation of the error ellipses toward the head is at least partly the result of gaze drift in the delay period

An assessment of the information lost when applying data reduction techniques to dynamic plantar pressure measurements

Contains fulltext : 203261.pdf (publisher's version ) (Open Access)Data reduction techniques are commonly applied to dynamic plantar pressure measurements, often prior to the measurement's analysis. In performing these data reductions, information is discarded from the measurement before it can be evaluated, leading to unkonwn consequences. In this study, we aim to provide the first assessment of what impact data reduction techniques have on plantar pressure measurements. Specifically, we quantify the extent to which information of any kind is discarded when performing common data reductions. Plantar pressure measurements were collected from 33 healthy controls, 8 Hallux Valgus patients, and 10 Metatarsalgia patients. Eleven common data reductions were then applied to the measurements, and the resulting datasets were compared to the original measurement in three ways. First, information theory was used to estimate the information content present in the original and reduced datasets. Second, principal component analysis was used to estimate the number of intrinsic dimensions present. Finally, a permutational multivariate ANOVA was performed to evaluate the significance of group differences between the healthy controls, Hallux Valgus, and Metatarsalgia groups. The evaluated data reductions showed a minimum of 99.1% loss in information content and losses of dimensionality between 20.8% and 83.3%. Significant group differences were also lost after each of the 11 data reductions (alpha=0.05), but these results may differ for other patient groups (especially those with highly-deformed footprints) or other region of interest definitions. Nevertheless, the existence of these results suggest that the diagnostic content of dynamic plantar pressure measurements is yet to be fully exploited

Automatic assessment of Levodopa-induced Dyskinesias in daily life by neural networks

Contains fulltext : 63060.pdf (publisher's version ) (Closed access

Gaze affects pointing toward remembered visual targets after a self-initiated step.

Item does not contain fulltextWe have investigated pointing movements toward remembered targets after an intervening self-generated body movement. We tested to what extent visual information about the environment or finger position is used in updating target position relative to the body after a step and whether gaze plays a role in the accuracy of the pointing movement. Subjects were tested in three visual conditions: complete darkness (DARK), complete darkness with visual feedback of the finger (FINGER), and with vision of a well-defined environment and with feedback of the finger (FRAME). Pointing accuracy was rather poor in the FINGER and DARK conditions, which did not provide vision of the environment. Constant pointing errors were mainly in the direction of the step and ranged from about 10 to 20 cm. Differences between binocular fixation and target position were often related to the step size and direction. At the beginning of the trial, when the target was visible, fixation was on target. After target extinction, fixation moved away from the target relative to the subject. The variability in the pointing positions appeared to be related to the variable errors in fixation, and the co-variance increases during the delay period after the step, reaching a highly significant value at the time of pointing. The significant co-variance between fixation position and pointing is not the result of a mutual dependence on the step, since we corrected for any direct contributions of the step in both signals. We conclude that the co-variance between fixation and pointing position reflects 1) a common command signal for gaze and arm movements and 2) an effect of fixation on pointing accuracy at the time of pointing

Linear dependence of peak, mean, and pressure-time integral values in plantar pressure images.

Dynamic plantar pressure images are routinely used in clinical gait assessment, and peak pressure, mean pressure, and pressure-time integral are the most frequently used parameters to summarize these images. Many studies report only one parameter, but other studies report all three. The interdependency of these variables has not been explicitly studied previously. The purpose of this study was to describe the linear relation between these three pressure parameters. 327 subjects walked normally over a pressure plate. Peak pressure, mean pressure and pressure-time integral were calculated for 10 different anatomical areas and, after applying a previously described spatial normalization procedure, these variables were also calculated for each pixel. Mean pressure was highly correlated with peak pressure (r=0.90+/-0.09) and pressure-time integral (r=0.81+/-0.13) for pixels. Peak pressure and pressure-time integral showed a linear correlation coefficient of r=0.78+/-0.21. The pressure parameters of the forefoot pixels were more highly correlated than the heel pixels. The current results have two major implications: (1) plantar pressure parameters (peak, mean, and impulse) can be reasonably compared across studies, even across parameters, and (2) the variables most commonly used to characterize plantar pressures are highly inter-correlated, implying that a smaller set of parameters may more efficiently capture the biomechanical behavior of interest

Cortical control of normal gait and precision stepping: an fNIRS study

Item does not contain fulltextRecently, real time imaging of the cortical control of gait became possible with functional near-infrared spectroscopy (fNIRS). So far, little is known about the activations of various cortical areas in more complex forms of gait, such as precision stepping. From previous work on animals and humans one would expect precision stepping to elicit extra activity in the sensorimotor cortices (S1/M1), supplementary motor area (SMA), as well as in prefrontal cortices (PFC). In the current study, hemodynamic changes in the PFC, SMA, M1, and S1 were measured with fNIRS. In contrast to previous fNIRS gait studies, the technique was optimized by the use of reference channels (to correct for superficial hemodynamic interference). Eleven subjects randomly performed ten trials of treadmill walking at 3 km/h (normal walking) and ten trials of 3 km/h treadmill walking on predefined spots for the left and right foot presented on the treadmill (precision stepping). The walking trials of approximately 35 seconds were alternated with rest periods of 25-35 seconds consisting of quiet standing. The PFC revealed profound activation just prior to the onset of both walking tasks. There was also extra activation of the PFC during the first half of the task period for precision stepping. The SMA showed mainly increased activation prior to the start of both tasks. In contrast, the sensorimotor cortex did not show a change in activation during either task as compared to a condition of standing. The SMA, M1, and S1 revealed no significant differences between normal walking and precision stepping. It was concluded that fNIRS is suited to record the planning and initiation of gait. The lack of M1/S1 activation during gait suggests that even in the current precision stepping task the control of ongoing gait depended mostly on subcortical automatisms, while motor cortex contributions did not differ between standing and walking.8 p