Assessing recovery is so damn fucking easy. You ask the survivor: 'Are you 100% recovered?' 'Y/N'. Quit overthinking this.
Psychometric Properties of a New Measure of Upper Limb Performance in Post-Stroke Individuals: Trunk-Based Index of Performance
Abstract
Background
Several
measures of upper limb (UL) motor tasks have been developed to
characterize recovery. However, UL performance and movement quality
measures in isolation may not provide a true profile of functional
recovery.
Objective
To
investigate the measurement properties of a new trunk-based Index of
Performance (IPt) of the UL combining endpoint performance (accuracy and
speed) and movement quality (trunk displacement) in stroke.
Methods
Participants
with stroke (n = 25, mean time since stroke: 18.7 ± 17.2 months)
performed a reaching task over 3 evaluation sessions. The IPt was
computed based on Fitts’ Law that incorporated endpoint accuracy and
speed corrected by the amount of trunk displacement. Test–retest
reliability was analyzed using intraclass correlation coefficient (ICC)
and Bland–Altman plots. Standard error of measurement (SEM) and Minimal
Detectable Change (MDC) were determined. Validity was investigated
through the relationship between IPt, Fugl–Meyer Assessment (FMA-UE),
and Action Research Arm Test (ARAT), as well as the ability of IPt to
distinguish between levels of UL motor impairment severity.
Results
Test–retest
reliability was excellent (ICC = .908, 95% CI: 0.807-0.96).
Bland–Altman did not show systematic differences. SEM and MDC95 were 14% and 39%, respectively. Construct validity was satisfactory. The IPt showed low-to-moderate relationships with FMA-UE (R2 ranged from .236 to .428) and ARAT (R2 ranged from .277 to .306). IPt scores distinguished between different levels of UL severity.
Conclusions
The
IPt showed evidence of good reliability, and initial validity. The IPt
may be a promising tool for research and clinical settings. Further
research is warranted to investigate its validity with additional
comparator instruments.
Introduction
The
first consensus meeting of the Stroke Recovery and Rehabilitation
Roundtable (SRRR) concluded that more accurate and predictive kinematic
measures of upper limb (UL) function need to be developed to distinguish
between changes in behavior due to functional recovery or compensation.1
They concluded that more informative measures of motor behavior are
vital to the understanding of neural repair processes and training
effects on motor action.2,3
Consequently, the second SRRR consensus panel recommended 4 performance
“assays” to characterize real change at the body structure/function
level and 1 functional task at the activity level.4
In this context, “assay” refers to a movement component that is
applicable to a wide range of motor actions or tasks. Assays were chosen
based on their ability to quantify the execution of a movement
component outside the context of the performance of any specific motor
task. They include a measure of coordination between shoulder and elbow
movements; finger force individuation; maximal isometric grip and pinch
strength. At the activity level, evaluation of endpoint kinematics (eg,
speed, smoothness), and joint and trunk displacements during a
standardized reaching task were recommended.4
Although
deviations from typical movement patterns provide information about the
motor elements contributing to task performance, it is unclear how
individual elements, including the presence of motor compensations,
reflect skilled movement. Regarding UL reaching, skilled movement has
been defined as an action that is executed at a short latency with high
speed and precision.5 This is often referred to as the speed–accuracy trade-off relationship, based on the concept of Fitts’ law.6
Fitts’ Law results in a measure that integrates the time to move the
hand to the target as a function of the hand-to-target distance and the
target width, but does not account for the influence of compensatory
trunk movements. Quantification of compensatory movement is vital to the
development of a metric for skilled reaching since, in contrast to
healthy participants, in patients with moderate-to-severe stroke,
endpoint precision is often influenced by trunk displacement.7,8
We
propose a novel application of Fitts’ Law characterizing skilled
reaching in people with stroke, that also accounts for the amount of
trunk displacement used during reaching, called the Trunk-based Index of
Performance, IPt. The new measure incorporates trunk displacement in
the classic Index of Performance (IP) measure, which is expressed as the
Index of Difficulty (ID) of the task divided by the Movement Time (MT;
IP = ID/MT), where ID is a function of the reaching distance (D) to the target divided by the target width (W), such that ID = log2 (2D/W).
The classic IP has been used in numerous experiments in motor control, psychology, and neuroscience.9,10 However, it has received less attention in studies of the recovery of reaching skill in the neurorehabilitation literature11 (but see Smits-Engelsman et al12), in which motor skill is usually characterized as smaller endpoint error and/or faster movement speed.13
The new measure, IPt, may be better able to capture real-world
manifestations of motor skill learning, where increased skill is
inferred if both variables change in the expected direction (faster
speed, increased precision),14 with less trunk compensation.
The
study goal was to determine the clinimetric properties, that is,
reliability (ie, test–retest reliability, measurement error) and
validity of IPt as a measure of motor skill in people with chronic
stroke performing a standardized reaching task. We hypothesized that IPt
would show high test–retest reliability and discriminate between
participants with mild or moderate-to-severe hemiparesis. Preliminary
results have appeared in abstract form.15
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