Effects of Stroke on Ipsilesional End-Effector Kinematics in a Multi-Step Activity of Daily Living

Abstract

Background: Stroke frequently impairs activities of daily living (ADL) and deteriorates the function of the contra- as well as the ipsilesional limbs. In order to analyze alterations of higher motor control unaffected by paresis or sensory loss, the kinematics of ipsilesional upper limb movements in patients with stroke has previously been analyzed during prehensile movements and simple tool use actions. By contrast, motion recording of multi-step ADL is rare and patient-control comparisons for movement kinematics are largely lacking. Especially in clinical research, objective quantification of complex externally valid tasks can improve the assessment of neurological impairments.Methods: In this preliminary study we employed three-dimensional motion recording and applied kinematic analysis in a multi-step ADL (tea-making). The trials were examined with respect to errors and sub-action structure, durations, path lengths (PLs), peak velocities, relative activity (RA) and smoothness. In order to check for specific burdens the sub-actions of the task were extracted and compared. To examine the feasibility of the approach, we determined the behavioral and kinematic metrics of the (ipsilesional) unimanual performance of seven chronic stroke patients (64a ± 11a, 3 with right/4 with left brain damage (LBD), 2 with signs of apraxia, variable severity of paresis) and compared the results with data of 14 neurologically healthy age-matched control participants (70a ± 7a).Results: T-tests revealed that while the quantity and structure of sub-actions of the task were similar. The analysis of end-effector kinematics was able to detect clear group differences in the associated parameters. Specifically, trial duration (TD) was increased (Cohen’s d = 1.77); the RA (Cohen’s d = 1.72) and the parameters of peak velocities (Cohen’s d = 1.49/1.97) were decreased in the patient group. Analysis of the task’s sub-actions repeated measures analysis of variance (rmANOVA) revealed no impact of the different demands of the sub-actions on the relative performance of the patient group.Conclusion: The analyses revealed kinematic peculiarities in the performance with the ipsilesional hand. These deficits apparently arose from the cognitive demands like sequencing rather than motor constraints. End-effector kinematics proved as a sensitive method to detect and quantify aspects of disturbed multi-step ADL performance after stroke. If standardized, the examination and the analysis are quick and deliver objective data supporting clinical research.

Smoothness Metrics in Complex Movement Tasks

“…Smaller movements, like repetitive approaches to the mug or hesitating and retrieving the hand could explain this: They produce peaks with small movements and at the same time add (unnecessary) path length. This would make the parameter better suited for the comparison of groups with similar path lengths and a comparable number of actions, this is for instance given in stroke patients and age-matched controls, who revealed comparable path lengths and action steps in the ADL of tea making ( 6 ). The spectral arc length was also able to detect the group differences, proved to be highly sensitive, revealed a low within-group variance, but showed a correlation in the intra-trial comparison with a power lower than 0.80, and revealed a strong dependence on kinematic parameters.…”

“…With technologies like advanced motion-tracking devices, it recently became more feasible to investigate human behavior in a natural, ecological valid setting. In the performance of such tasks, goals can be achieved in various ways and actions can't be precisely predicted ( 6 ). However, certain actions, like phases of inactivity, transporting, grasping, rotating, circling, or balancing, repeatedly appear in ADL.…”

“…For different types of movement tasks, trajectories and corresponding velocity profiles differ in the signals' structures ( 14 ). Assessing complex tasks, like ADL, the signal can show peculiarities like phases of inactivity or different quantities of actions ( 6 , 15 ). This can lead to misestimations, when using approaches that utilize data processing that is developed for less complex signals, which can be periodic ( 16 , 17 ) [brushing teeth, sawing, or hammering ( 18 )] or of short lengths ( 8 ) [reaching or grasping movements ( 8 , 13 )].…”

“…The present classification bases on the differentiation between velocity peak, different kinds of jerk and spectral analysis metrics ( 12 , 17 , 19 ), whereas spectral analysis metrics follow the assumptiom that less smooth movements are more complex in terms of their frequency composition when approximating the original signal with a Fourier series [for an easy introduction to spectral analysis see ( 20 )]. Various velocity-based parameters were suggested: the number of velocity peaks ( 6 , 21 – 23 ), the normalized average speed ( 12 , 24 ), the relative level of activity ( 6 , 21 , 24 , 25 ), or the peak-based composition of the velocity profile ( 12 , 26 ). Acceleration-based parameters are examining the rate of change of movement acceleration and are usually forms of the jerk metric like the normalized jerk ( 27 , 28 ), the log dimensionless jerk ( 8 ), the normalized squared jerk ( 14 ), or the normalized mean jerk ( 12 ).…”

“…Further, we examined if the parameters are quantifying a general ability to produce smooth movements. ADL offer a way to examine behavior in the context of disease and aging in an ecological valid way and should therefore be considered in research and clinical assessment ( 6 , 10 , 11 , 21 , 32 ). This study tries to explore the behavior of different parameters in an empirical way in order to give suggestions and an outlook on future developments.…”