Muscles
in the post-stroke arm commonly demonstrate abnormal reflexes that
result in increased position- and velocity-dependent resistance to
movement (i.e. spastic hypertonus: [21, 25]. Spastic hypertonia is understood to reflect systematic reductions in stretch reflex thresholds [16, 24], decreased range of regulation of these stretch reflex thresholds [23, 47],
as well as altered non-reflex phenomena such as abnormalities in the
intrinsic mechanical properties of spastic muscles and altered
viscoelastic properties of passive tissues [28, 43, 49].
Importantly, systematic reduction in stretch reflex threshold could
lead to significant increase in stretch reflex excitability [17] and agonist/antagonist coactivation in some regions of the workspace [22, 30],
which could lead to complex, posture-dependent and potentially
time-varying joint impedances in the hemiparetic arm. Because the
feedforward control of goal-directed movements relies on accurate
predictions of limb impedance [38],
spatial and temporal complexity of joint impedance may be a significant
contributor to impairment of movement coordination post-stroke [20, 40, 48].
Although a velocity-dependent increase in muscle tone (spasticity is
frequently assessed clinically and has been quantified in single joints
such as the elbow and wrist [15, 23, 26, 44], quantitative assessments of multi-joint control deficits have been rare (see [30, 36])
and sometimes rely on techniques such as kinematic and/or inverse
dynamics analyses, which can be insensitive to the presence and effects
of abnormal muscle coactivations (e.g., [18, 33]).
The
goal of this study was to develop a reliable approach for measuring the
mechanical consequences of abnormal neuromuscular mechanisms as a
function of hand location in the reachable workspace in the hemiparetic
arm post-stroke. We are motivated in this work by a growing body of
experimental evidence supporting the idea that the neural mechanisms
contributing to the control of limb posture and movement can be
differentially compromised by stroke [19, 27, 40], see also [8, 37, 48] and by other neuromotor disorders (cf. [10, 11]),
and by the belief that greater understanding of the mechanisms
contributing to sensorimotor deficits will eventually lead to improved
efficacy of therapeutic interventions [13].
Our work builds on prior studies that examined transient mechanical and
electromyographic responses to passive displacements of the wrist or
elbow to quantitatively assess post-stroke spasticity (cf. [15, 23, 26, 44, 47]) and spastic dystonia [46].
In one example, Schmit and colleagues used a motorized device to
passively flex and extend the elbow of hemiparetic stroke survivors over
a range of speeds ranging from slow (6º/s) to fast (90º/s) [44].
Their goal was to assess the reliability of three different
biomechanical correlates of spasticity, which they isolated from other
aspects of spastic hypertonia associated with dystonia, contracture, and
increased joint stiffness. They did so by subtracting the torque
response to the slowest displacement from responses to faster
displacements, leaving only reflex torque. This approach is effective
because the stiffness of the passive tissues about the elbow joint are
largely velocity insensitive [9].
Of the three biomechanical measures considered—peak torque, peak joint
stiffness, and onset angle of reflex torque responses—peak torque values
measured during displacements at 90°/s were most reliable on repeated
measures in a single testing session (> 80% reliability), and most
highly correlated with clinical assessments of spasticity (Ashworth
Scale). In another example, Mirbhageri and colleagues [29]
used system identification techniques to quantify the contributions of
reflex and intrinsic (i.e., non-reflex) stiffness to total elbow
stiffness at several different elbow angles in the paretic and
nonparetic arm of chronic hemiparetic stroke survivors. Each position
was examined under passive conditions in the range of full elbow flexion
to full elbow extension. They reported that intrinsic and reflex
stiffness both contributed strongly to net joint torque, that the
effects were significantly larger in the paretic than in the non-paretic
elbow muscles, and that these differences increased with the increasing
joint angle indicating position dependence. Although these prior
studies suggest that manifestations of spasticity and hypertonia may
vary in complex ways across the reachable workspace after stroke, a more
comprehensive approach to quantifying mechanical expressions of
spasticity and hypertonia across the workspace has yet to be described.
We
designed a set of experiments using a two-joint, planar robot to
measure the dynamic and quasistatic mechanical and electromyographic
responses to controlled displacements of the upper extremity at several
locations in the arm’s workspace. Subjects were instructed to relax as
the robot moved their hand sequentially between target locations
spanning the reachable workspace at speeds ranging from very slow to
fast. Trajectories were selected such that movements were largely
limited to either the shoulder or elbow joint, but not both. The robot
stabilized the hand at the target for at least 20 s following the end of
each movement. We analyzed the time series of horizontal planar hand
forces and electromyographic (EMG) activations for selected arm muscles
to determine the duration of phasic, velocity-dependent resistance to
stretch, to characterize the spatial topography of tonic,
position-dependent hand forces throughout the workspace, and to
characterize the muscle activations that give rise to these postural
bias forces. The resulting data demonstrate that the robotic assessment
of posture-dependent bias forces was repeatable across days, that the
phasic component of these stroke-related forces lasted no more than 2 s
after the end of limb re-positioning, and that these bias forces were
partly neuromuscular in origin (not merely due to passive tissue
resistance to stretch) such that elevated “resting” EMG activations
exhibited posture-dependence in some muscles, but posture-invariance in
others. We expect that quantitative evaluation of posture-dependent bias
forces may facilitate future assessments of stroke's impact on the
interaction between the control of upper extremity posture and movement.
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