Describing something without having protocols to fix anything is ABSOLUTELY FUCKING WORTHLESS!
Send me hate mail on this: oc1dean@gmail.com. I'll print your complete statement with your name and my response in my blog. Or are you afraid to engage with my stroke-addled mind? No excuses are allowed! You're medically trained; it should be simple to precisely state EXACTLY WHAT GOOD 'Kinematic descriptions' do for recovery with NO EXCUSES! Your definition of competence in stroke is obviously much lower than stroke survivors' definition of your competence! Swearing at me is allowed, I'll return the favor. Don't even attempt to use the excuse that brain research is hard.
Kinematic descriptions of upper limb function using simulated tasks in activities of daily living after stroke
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Introduction
Stroke
is a leading cause of long-term disability and most stroke survivors
have chronic upper limb dysfunction. Dysfunction in upper limbs is a
combination of muscle weakness, paralysis, spasticity, sensory loss and
abnormal motor synergies, which impairs the performance of activities of
daily living (ADLs). Therefore, assessment of upper limb function is
critical for clinical management and determining the efficacy of
interventions.
Assessment
of upper limb function in stroke patients is usually performed using
standardized clinical scales, such as Fugl-Meyer Assessment (FMA), Wolf
Motor Function Test (WMFT), Motor Activity Log (MAL), and Action
Research Arm Test (ARAT). These clinical scales are reliable measures,
but could lack sensitivity to detect minor changes in motor performance
due to the nature of ordinal scales, especially when patients are close
to full recovery. Detecting minor changes in motor performance could
provide a more comprehensive view of recovery process and help
clinicians evaluate the efficacy of interventions (van Dokkum et al.,
2014).
Apart from
clinical scales, researchers use motion capture systems to evaluate
upper limb function via kinematic analysis. Over the past decade, there
was an increasing trend of using kinematic analysis, which provides
detailed spatiotemporal information of limbs movements (Santisteban et
al., 2016). Kinematic analysis represents the best way to distinguish
behavioral restitution from substitution, which is essential to assess
motor performance in stroke recovery(Kwakkel et al., 2017; Schwarz Anne,
Kanzler, Olivier, Luft, & Veerbeek, 2019). Behavioral restitution
is defined as a return pre-lesion movement pattern or function of the
affected limb. Behavioral substitution is defined as the emergence of
new movement strategies that differ from the original, which is referred
to as compensation. Unlike gait analysis which primarily examine
cyclical movements of the lower limbs, assessment of upper limb
movements is challenging due to a large repertoire of upper limbs
movement for ADLs. Previous studies used forward reaching (Massie,
Malcolm, Greene, & Browning, 2012; Robertson & Roby-Brami,
2011), side reaching (Verheyden et al., 2011), and grasping (Alt Murphy,
Willén, & Sunnerhagen, 2012) to measure upper limb kinematics.
Results showed that stroke patients had greater movement duration,
greater reach path ratio, reduced shoulder and elbow excursions, and
greater trunk displacement during reaching tasks with paretic
arms(Collins, Kennedy, Clark, & Pomeroy, 2018). While these studies
contain a wealth of information about upper limb control, there is a gap
between real-life activities and the simple tasks used in research
settings. Those simple tasks may not reflect the level of abilities to
perform ADLs because movements in simple tasks are primarily performed
in two-dimensional plane and one or two steps. Since most ADLs involving
upper limbs are performed in three-dimensional space and multi-steps,
three-dimensional tasks that require the coordination of shoulder, elbow
and hand should be favored to assess behavioral restitution(Schwarz
Anne et al., 2019). Here, we designed a unilateral upper limb task to
simulate ADLs and examined how chronic stroke survivors control serial
movements of reaching, grasping and handling an ergonomic spoon to
transfer liquid from a large bowl to a small personal bowl in
three-dimensional space. Moreover, we intended to examine both temporal
and spatial aspects of kinematics between paretic and nonparetic arms
when chronic stroke survivors perform the unilateral upper limb task
with an ergonomic spoon.
A
movement pattern is coordinated if individuals can perform the movement
pattern consistently in repeated trials to accomplish a desired task,
reflecting the stability of a movement pattern (Magill, 2011). The term
“stability” refers to the consistency of the spatiotemporal pattern of
movement, which can be measured by the variability of kinematic
variables. If the motor system is perturbed due to stroke, the
variability of kinematic variables may be increased (Thies et al.,
2009). We intended to examine the variability of kinematic variables by
testing whether the movement patterns of upper limbs could be reproduced
with consistency when participants use their paretic arm to perform the
task.
The purpose of
this study was to 1) examine temporal aspects of kinematics between
paretic and nonparetic arms when chronic stroke survivors perform the
unilateral upper limb task with an ergonomic spoon, 2) examine the
spatial aspects of kinematics between paretic and nonparetic arms during
the task, and 3) compare the kinematic variability of paretic arm
movements to the kinematic variability of nonparetic arm movements
during the task. Outcome measures included movement duration, relative
timing, path length, joint excursions, and trial-to-trial variability.
