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

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.     

Catching oriented objects

We have investigated how participants match the orientation of a line, which moves on a vertical screen towards the subject. On its path to the participant, the line could disappear at several positions. Participants were instructed to put a bar on a predefined interception point on the screen, such that the bar touched the screen with the same orientation as the moving line at the very moment when the line passed through the interception point or (in case of line disappearance) when the hidden line would pass through the interception point (like in catching). Participants made significant errors for oblique orientations, but not for vertical and horizontal orientations of the moving line. These errors were small or absent when the moving line was visible all the way along its path on the screen. However, these errors became larger when the line disappeared farther away from the interception point. In the second experiment we tested whether these errors could be related to errors in visual perception of line orientation. The results demonstrate that errors in matching of the bar do not correspond to the last perceived orientation of the line, but rather to the perceived orientation of the moving line near the beginning of the movement path. This corresponds to earlier observations that participants shortly track a moving target and then make a saccadic eye movement to the interception point.     

Relation between EMG activation patterns and kinematic properties of aimed arm movements

Aimed flexion movements of the arm of different amplitude and duration were studied. Velocity and acceleration traces of movements with equal duration but different amplitude were equal, apart from a scaling factor (ratio between movement amplitudes). After appropriate scaling, EMG activity of the first agonist burst for these movements superimposed. This was not true for EMG activity in the antagonist muscle. For movements with equal amplitude, but different duration, the time to peak acceleration was constant for all MT'. Except for this fact, traces of acceleration, velocity, and agonist activity following the time of peak acceleration were about equal after appropriate scaling in time and amplitude. The integral of EMG activity in the first agonist burst increased linearly with peak velocity. For the antagonist burst, the integrated EMG activity increased more than proportionally. During movements made as fast as possible, subjects used a different strategy by varying the duration of the accelerating phase for movements of different amplitude. Movement amplitude was achieved by adjusting the duration of the agonist burst and the onset time for the antagonist muscle. Amplitude of the antagonist burst was constant within a narrow range for movements of different amplitude. These results did not change when the inertial mass was doubled by loading the arm with an additional mass.     

Stiffness control after fast goal-directed arm movements

Mechanical parameters of the effector system directly after the termination of fast goal-directed arm movements were studied.Subjects were asked to move their hand as fast as possible to a target the instant the target was presented. Only movements of the subjects' forearms were allowed. They were also instructed not to react actively to forces applied suddenly to their forearm after the movement. As a result of such a force pulse the arm moved to a new position. The apparent stiffness, i.e. the quotient of the applied force and the resultant change of position, was measured. This stiffness is a measure for the resistance of the forearm to externally applied mechanical disturbances.It was found that after the arm has reached the target the apparent stiffness decreases as a function of time. This is an agreement with the declining amplitude of the electromyographic activity of the muscles that effect the movement.Arguments are given to support the hypothesis that this apparent stiffness control is part of the motor programme for movements of the forearm, i.e. the stiffness is planned together with the movement.     

Are the Orientations of the Head and Arm Related During Pointing Movements?

The head, eye, and shoulder are each free to rotate around three mutually orthogonal axes. These three degrees of freedom allow a given gaze or pointing direction of the eye, head, or arm to be obtained in many different possible orientations. Unlike translations in three dimensions, three-dimensional (3-D) rotations are noncommutative. Therefore, the orientation of a rigid body following sequential rotations about two different axes depends on the order of the rotations. In this article, we demonstrate that only two degrees of freedom are used during orienting movements of the head and pointing movements of the arm. This provides a unique orientation of head and arm for each gaze or pointing direction despite the noncommutativity of three-dimensional rotations. This observation is in itself not new. We found, however, that (a) the two-dimensional lquot;rotation surface,rquot; which describes the orientation of the head for all gaze directions, is curved, unlike the analogous flat plane for the eye. (b) The rotation surface for the head is curved differently than that for the arm. This result argues against the hypothesis that the orientations of head and arm are directly coupled during pointing. It also implies that the orientation of the eye in space during gaze shifts of the eye and head is not uniquely determined for a given direction of gaze. This finding argues against a perceptual basis for the reduction of rotational degrees of freedom.     

Arm-Tracking Performance With and Without Visual Feedback in Children and Adults

Tracking performance was investigated in children (aged 6-7 and 10-11) and in adult subjects. Target signals, moving unpredictably along a straight line, were tracked with the preferred arm, alternately with and without visual feedback. Qualitative observations indicate that tracking is based on continuous adjustments of the ongoing response to the continuously changing target position. No step-and-hold strategy could be detected in any of the three age groups. Tracking performance was described with four simple parameters, derived from linear systems analysis: (a) the delay between target signal and tracking movement (DL); (b) performance at the low-frequency range (LF), (c) performance at the high-frequency range (HF); and (d) a measure of tracking quality or overall similarity in the shape of target signal and tracking movement (Q). There was a considerable improvement in tracking performance with age, even after the age of 10-11, which was mainly demonstrated by a decrease in DL and increases in HF and Q. Tracking performance decreased only to a small extent when visual feedback was withdrawn. Age-related differences in the contribution of visual feedback to tracking performance could not be demonstrated.