Posts Tagged discriminative validity

[ARTICLE] Upper Limb Kinematics in Stroke and Healthy Controls Using Target-to-Target Task in Virtual Reality – Full Text

Background: Kinematic analysis using virtual reality (VR) environment provides quantitative assessment of upper limb movements. This technique has rarely been used in evaluating motor function in stroke despite its availability in stroke rehabilitation.

Objective: To determine the discriminative validity of VR-based kinematics during target-to-target pointing task in individuals with mild or moderate arm impairment following stroke and in healthy controls.

Methods: Sixty-seven participants with moderate (32–57 points) or mild (58–65 points) stroke impairment as assessed with Fugl-Meyer Assessment for Upper Extremity were included from the Stroke Arm Longitudinal study at the University of Gothenburg—SALGOT cohort of non-selected individuals within the first year of stroke. The stroke groups and 43 healthy controls performed the target-to-target pointing task, where 32 circular targets appear one after the other and disappear when pointed at by the haptic handheld stylus in a three-dimensional VR environment. The kinematic parameters captured by the stylus included movement time, velocities, and smoothness of movement.

Results: The movement time, mean velocity, and peak velocity were discriminative between groups with moderate and mild stroke impairment and healthy controls. The movement time was longer and mean and peak velocity were lower for individuals with stroke. The number of velocity peaks, representing smoothness, was also discriminative and significantly higher in both stroke groups (mild, moderate) compared to controls. Movement trajectories in stroke more frequently showed clustering (spider’s web) close to the target indicating deficits in movement precision.

Conclusion: The target-to-target pointing task can provide valuable and specific information about sensorimotor impairment of the upper limb following stroke that might not be captured using traditional clinical scale.

Introduction

In stroke, the prevalence of upper limb impairment is approximately 50–80% in the acute phase (13) and 40–50% in the chronic phase (24). The frequently observed upper limb impairments after stroke are paresis, abnormal muscle tone, decreased somatosensation, and coordination. As a consequence of these impairments, individuals with stroke may experience reduced ability to perform everyday activities such as opening a door, handling a key, or working with a computer. Therefore, assessment of upper limb motor function is critical for determining the prognosis and evaluating the treatment effects following stroke (56).

The assessment of motor functions in stroke is usually performed using standardized clinical scales. Some of the most frequently used clinical instruments for assessing upper extremity impairment and activity capacity in stroke are Fugl-Meyer Assessment of Upper Extremity (FMA-UE) and Action Research Arm Test (ARAT) (79). These scales are reliable (1012) and responsive to change (1314) for measuring gross changes in motor function. They have also been recommended as core measures to be included in every stroke recovery trial (6). However, observer-based ordinal instruments like FMA-UE and ARAT lack the sensitivity to assess subtle, yet, potentially important changes in movement performance (15). These clinical scales tend to have ceiling effect since they rely on scoring criteria rather than a continuous measurement construct (16).

Kinematic assessment is one solution for the need for a more objective, accurate, and sensitive measurement method (6). Kinematic assessment is being increasingly used in upper limb evaluation after stroke, out of which motion capture systems (17), robotic devices, and virtual reality (VR) systems with haptic devices (18) have become popular in the last decade. Kinematic assessment has revealed that the arm movements in subjects with stroke are slower, less accurate, less smooth, and more segmented than healthy subjects (1926).

Kinematic assessment involving the use of VR with haptic device has shown to be a promising tool for upper limb stroke rehabilitation (2728). Despite the availability of the VR system for stroke rehabilitation, it has been rarely used in assessment of upper limb movements after stroke. Individuals with stroke use similar strategies for reaching objects in both real and virtual environments (29). Previous studies using the target-to-target pointing task have shown that the movement time, velocity, and trajectory straightness were improved after a 5-week computer gaming practice in individuals with stroke (30). Movement time, mean velocity, and trajectory straightness were also stable in a test–retest study in healthy subjects (31). A clear advantage with VR systems as a measurement tool is its standardized instructions, adaptation of tasks according to patients’ functioning level, and availability of quick feedback (32). The VR assessment and training are often described as enjoyable and challenging by the users (3334).

The target-to-target pointing task is similar to routinely used tasks in everyday life, such as interacting with touch screens, using electrical switches, and pushing buttons on various devices. The choice of a regularly performed, purposeful task for this study increases its ecological validity. With VR technologies becoming more available, it opens up an opportunity to use the VR interface to acquire accurate and detailed kinematic data of upper limb movements after stroke (35). The novelty of this study is in evaluating a compact and easy-to-use haptic device coupled with VR in 3D space in order to measure movement performance during a common upper limb task.

The aim of this study was to identify the end-point kinematic variables obtained during the VR-based target-to-target pointing task that discriminate among individuals with mild and moderate upper limb impairment after stroke and healthy controls.[…]

 

Continue —>  Frontiers | Upper Limb Kinematics in Stroke and Healthy Controls Using Target-to-Target Task in Virtual Reality | Neurology

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