Exp Brain Res (2015) 233:15–25 DOI 10.1007/s00221-014-4061-3
RESEARCH ARTICLE
Anomalous EMG–force relations during low-force isometric tasks in hemiparetic stroke survivors Nina L. Suresh · Nicole S. Concepcion · Janina Madoff · W. Z. Rymer
Received: 1 October 2012 / Accepted: 1 August 2014 / Published online: 17 September 2014 © Springer-Verlag Berlin Heidelberg 2014
Abstract Hemispheric brain injury resulting from a stroke is often accompanied by muscle weakness in contralateral limbs. In neurologically intact subjects, appropriate motoneuronal recruitment and rate modulation are utilized to optimize muscle force production. In the present study, we sought to determine whether weakness in an affected hand muscle in stroke survivors is partially attributable to alterations in the control of muscle activation. Specifically, our goal was to characterize whether the surface EMG amplitude was systematically larger as a function of (low) force in paretic hand muscles as compared to contralateral muscles in the same subject. We tested a multifunctional muscle, the first dorsal interosseous (FDI), in multiple directions about the second metacarpophalangeal joint in ten hemiparetic and six neurologically intact subjects. In six of the ten stroke subjects, the EMG–force slope was significantly greater
N. L. Suresh (*) · J. Madoff · W. Z. Rymer Sensory Motor Performance Program, Rehabilitation Institute of Chicago, 345 E Superior Street, Room 1378, Chicago, IL 60611, USA e-mail: [email protected] N. S. Concepcion Research Foundation at State University of New York, New York, NY, USA W. Z. Rymer Department of Physical Medicine and Rehabilitation, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA W. Z. Rymer Department of Physiology, Northwestern University, Chicago, IL, USA W. Z. Rymer Department of Biomedical Engineering, Northwestern University, Chicago, IL, USA
on the affected side as compared to the contralateral side, as well as compared to neurologically intact subjects. An unexpected set of results was a nonlinear relation between recorded EMG and generated force commonly observed in the paretic FDI, even at very low-force levels. We discuss possible experimental as well as physiological factors that may contribute to an increased EMG–force slope, concluding that changes in motor unit (MU) control are the most likely reasons for the observed changes. Keywords Electromyography · First dorsal interosseous · Paresis · Stroke
Introduction Hemispheric brain injury resulting from a stroke is often accompanied by weakness of voluntary movement in the limbs contralateral to the injury, as part of the “upper motoneuron” syndrome. This weakness has been attributed, in large part, to a loss of descending cortical excitatory input to segmental neurons. Although it is inherently plausible, there is surprisingly little direct evidence for this hypothesis. Alternative explanations such as changes in muscle properties as a function of disuse or changes in the efficacy of spinal segmental activation of motoneurons (MN) within a MN pool could also play a role. Regardless of whether changes in descending drive or changes in muscle properties occur, appropriate motoneuronal activation is necessary to optimize muscle force production utilizing residual muscular elements. To explain further, under normal conditions force gradation during voluntary contraction is generated primarily through the coordinated recruitment and rate modulation of motor units. If motor unit activation is ineffectual, such as when
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the firing rate of the motor unit is not well matched to the contractile properties of the innervated muscle fibers, then a greater portion of the MN pool might be required to reach a specified force level. This ineffectual activation could be accompanied by a greater level of motor unit recruitment for a given force, resulting in a larger surface EMG signal. We have known for some time that there may be major abnormalities of motor unit recruitment and rate modulation in muscles of paretic limbs. For example, Tang and Rymer (1981) reported a significant increase in the slope of the (surface) EMG–force relation during steady-state force contractions in the affected biceps brachii of human stroke survivors. Descriptions of motor unit discharge patterns in human spastic–paretic muscles are few in number, but those available support the existence of altered neural control of muscle (Rosenfalck and Andreassen 1980; Suresh et al. 2011; Hu et al. 2012). In an earlier study from our group, Gemperline et al. (1995) reported that more than half the tested stroke subjects exhibited significant reductions in mean motor unit discharge rate (at a fixed force level) in the paretic biceps brachii. Additionally, most study subjects exhibited a striking compression of the motoneuronal recruitment force range as well as limited rate modulation. In light of the uncertainty as to the origin of neural contributions to muscle weakness, as well as the possibility that proximal and distal muscles exhibit different impairment patterns with respect to force production (Thomas and del Valle 2001; Zijdewind and Thomas 2003), the objective of our present study was to use surface EMG and joint force recordings to determine whether weakness in a hand muscle in stroke survivors is at least partially attributable to alterations in the neural control of the motor units in these affected muscles. Here, the surface EMG signal is a gauge of the level of muscle activity required to generate a given amount of force. Our study was performed in the first dorsal interosseous (FDI), a multifunctional muscle that is activated for a variety of force directions about the second metacarpophalangeal (MCP) joint. Accordingly, we computed and made comparisons of the EMG–force slopes in paretic, contralateral and intact controls, in multiple force directions. This allowed us to test the uniformity of any EMG–force slope increases on the paretic side and in turn allowed us to understand whether changes in the pattern of antagonist and synergist muscle activation contribute to any observed differences. To derive EMG–force slope estimates, consecutive time periods of constant force and EMG signals obtained during the rising phase of a slow ramp low-force level task were used, thus enabling the characterization of the EMG–force relation over a continuous but low-force range and in a variety of force directions. The stationarity of the EMG signal over large [100 % maximum voluntary contractions (MVC)] forces during a 5 s ramp has been previously reported (Bilodeau et al. 1997).
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Exp Brain Res (2015) 233:15–25
Our primary finding is that in the paretic FDI of the majority of our stroke subjects, the EMG–force slope is significantly greater than slope estimates drawn from the contralateral FDI or in neurologically intact subjects. We report no systematic differences in the computed slopes between the three groups as a function of force task direction. An unexpected observation was that during the rising force phase, the EMG–force relation was nonlinear with a steep initial EMG slope followed by a reduced or flat slope in the paretic FDI only, even at relatively low-force levels. We discuss the possible neuromuscular mechanisms and experimental factors that might contribute to the observed anomalous EMG–force relations.
Methods Data collection We examined the activity of the first dorsal interosseous muscle (FDI) of ten hemiparetic stroke subjects and six neurologically intact subjects. Muscle activity was examined by recording surface EMG activity during controlled isometric force generation at the second metacarpophalangeal (MCP) joint. All participants gave informed consent via protocols approved by the Institutional Review Board under the Office for the Protection of Human Subjects at Northwestern University. Stroke participants Stroke participants were adults who had sustained a hemiparetic stroke at least 6 months prior to experimental testing. A research physical therapist evaluated the ability of the participants to complete the specified finger tasks as well, the ability to attain and maintain the experimental sitting posture and performed the Fugl-Meyer and the ChedokeMcMaster hand clinical assessments on both sides of our hemiparetic stroke subjects. Neurologically intact participants Our neurologically intact subjects were, on average, ageand sex-matched. A clinical assessment of our intact subjects was performed by the research physical therapist to affirm the lack of neurological injuries and/or motor deficits. Experimental setup Study participants were seated upright in a Biodex chair with their upper arm comfortably resting on a plastic support. In order to help standardize hand position as well as to minimize activity of unrecorded muscles, the forearm was
Exp Brain Res (2015) 233:15–25
17
Fig. 1 Experimental setup. a The forearm is cast and firmly clamped at the wrist in a metal ring with a plastic interface. The index finger is cast and is then inserted into a vice attached to the load cell. The other fingers are splayed and held in place with a Velcro strap, and
the thumb is placed in a plastic insert. Schematic representation of the task force plane. b The axes represent four primary isometric force directions, i.e., abduction, adduction, flexion and extension. Each quadrant is a linear combination of these primary directions
casted and placed in a ring-mount interface attached to an elbow rest: This rest was securely mounted with magnetic stands to a heavy steel table. The right shoulder was placed in 45° of abduction and neutral rotation, the elbow in 60° of flexion, the forearm in full pronation, and the wrist was held neutral with respect to flexion/extension. The 3rd–5th digits were comfortably splayed and strapped to the support surface. The 1st digit was secured at a 60° angle to the 2nd digit. The 2nd digit was placed in line with the second metacarpal and the long axis of the forearm creating a 0° or neutral (abduction/adduction) metacarpophalangeal (MCP) joint angle. To ensure maximal isolation of the FDI muscle, specially designed finger vises were attached to a six degrees-of-freedom load cell (JR3, Inc. and ATI, Inc), such that the index finger, which was cast, was coupled to the load cell at the proximal phalanx of the 2nd digit (Fig. 1a). The proximal interphalangeal (PIP) and distal interphalangeal (DIP) joints were left uncast.
EMG–force slope estimates to those force tasks generated in quadrant III. Data collected from the other quadrants were used to assess whether there was abnormal activation of the paretic FDI as an antagonist and thus provide insight as to whether antagonist coactivation may be a contributing factor to any observed increases in EMG–force slopes. The recordings from x, y and z coordinates of the force generated at the MCP joint were band passed (DC-200 Hz) and digitized at a sampling rate of 1 kHz. Force in the z direction, which is outside the force generation plane, was used to monitor the generated forces.
Force coordinate plane and force recordings In the experimental apparatus described above, isometric adduction about the second MCP joint was designated a positive horizontal deviation (+x) and isometric abduction to a negative horizontal deviation (−x) in the plane perpendicular to the index finger. Isometric extension about the MCP joint was designated as a positive vertical deviation (+y) and isometric flexion to a negative deviation (−y). In this x–y plane (Fig. 1b), angles from 180 to 270 or quadrant III are combinations of abduction and flexion. In this study, we limited the
Participant instructions Participants were instructed to generate isometric forces in abduction, flexion, extension and combinations of abduction/ flexion and abduction/extension. For each trial, the subject was instructed to slowly (approximately 10 s to peak force) generate force in a given radial direction and then slowly reduce the force level to 0, thereby generating an isometric force ramp. However, stroke subjects were not always able to generate force in all directions on both the paretic and contralateral sides. Attainable directions were repeated 2–3 times, in random order, with a minimum of 20 s between each force ramp. To aid participants control the forces they exerted, two-dimensional forces (vertical and horizontal) were displayed on an oscilloscope placed before them. Each stroke subject was tested on their paretic side first, in order to determine the force range for testing on the nonparetic side. The subjects were provided with practice
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trials and were familiar and able to perform the isometric force tasks. The objective of the study was to assess EMG– force slopes during low-force contractions and to compare the EMG–force slopes over the same force range on both sides of a given subject. Thus, (absolute) force levels were consistent between the two sides of one subject but varied across the pool of tested stroke subjects. During the first trial of each session, subjects were asked to perform isometric (maximum voluntary contraction) MVCs in the primary directions of abduction and flexion, with each direction repeated twice, although not all stroke subjects could generate MVCs in both directions. Subjects were given 5 min of rest between each MVC contractions. EMG recordings Small, surface electrodes that include self-contained preamplifiers (Delsys, Inc.) were placed on the skin surface covering the FDI for EMG recordings. The EMG electrodes were placed in a similar orientation over the FDI for both sides of every tested stroke subject and for our intact subjects. In five stroke subjects, we were able to obtain surface recordings from the extensor digitorum communis (EDC) as well. For all surface EMG recordings, large reference electrodes were placed over the elbow on the same side as the recording. The EMG preamplifier has a bandwidth of 20–450 Hz for surface signals, which were digitized at a rate of 2 kHz (CED, Power 1401). Force and EMG signals were collected using the software program from CED, Spike2 (version 6), and were stored on a computer for subsequent analysis (Fig. 2). Data analysis EMG, force pairs To quantify the surface EMG signal, we computed the averaged, rectified (ARV) EMG. The ARV EMG was computed by first subtracting a 250 ms average of the precontraction, baseline (raw) EMG signal from the EMG trace for each trial. The EMG signal was then rectified and then subsequently averaged over 250 ms, stationary, nonoverlapping intervals during the rising phase of the force ramp task. The raw force signal, with a resting force value subtracted, was averaged over the same 250 ms (steady), nonoverlapping data windows. The output of this analysis was a set of EMG–force pairs computed from the rising phase of each force ramp trial. Slope computation: force direction and magnitude The EMG–force pairs were exported to our MATLAB program in order to perform slope calculations. We observed
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Exp Brain Res (2015) 233:15–25
that on the affected side of our stroke subjects, the EMG– force relation was not always linear for the entire force ramp rise, instead there were often trials in which the EMG–force plot exhibited two or more distinct regions, including a flattened, decreasing or steeply rising second slope (Fig. 3a). To identify the linear regions of the EMG–force relations for the purposes of slope estimation, we used a method that utilized correlation coefficient computations over successively longer intervals of the EMG–force trace until the correlation coefficient began to decrease in value. Using cursors for visual confirmation and manual override, only the identified linear region was utilized for slope computation (Fig. 3b). These linear regions were identified for all three limbs (paretic, contralateral, and intact controls) and the force magnitude and task angle at which the nonlinear transition occurred was documented. Even for a single stroke subject, there was variability in the force range over which the EMG–force relation was linear. In order to make slope computations over a uniform force range between the two sides of one subject, we derived an average of the linear force ranges (LFR) obtained across all recorded force ramp trials for the affected side of each subject. The average force value was used as the largest force magnitude over which slope computations were performed on both the affected and contralateral sides of each subject. Regression analysis of the relationship between force direction and LFR, ramp force magnitude and LFR for each side of each stroke subject was determined utilizing a firstand second-order fit. The same analysis was performed for the regression analysis of slope ratio (affected/contralateral) as a function of direction for each side of each stroke subject. The r-squared values for each fit were computed and recorded. The maximum surface EMG (MsEMG) was obtained by averaging the steady-state region of the rectified surface EMG signal over a 1 s interval. The largest MsEMG obtained during repeat trials (4–5) of maximal voluntary force (in any direction) was used for further analysis. The MsEMG EMG was calculated for every subject, for each side. A second set of slopes was computed utilizing the EMG–force pairs and % MsEMG EMG force pairs for each side separately. Statistical comparisons between the two sides were made (see below). Statistical assessment The computed slope values were tested for statistical significance using SPSS (SPSS, Inc.) software. Unpaired t-tests were performed between the slope estimates derived from the affected side compared with slope estimates derived from the contralateral side of each stroke subject
Exp Brain Res (2015) 233:15–25
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EMG measurements for the impaired hand and for the contralateral hand and compared these results with the responses of FDI muscles in control subjects. Table 1 provides a summary of the Fugl-Meyer and Chedoke-McMaster clinical assessments that were performed as well as other relevant information for our tested stroke subjects. Our clinical assessments show that there was a wide range of motor impairments on the affected side and our stroke subjects were comparatively unimpaired on the contralateral side. Experimental assessment of muscle weakness in stroke subjects
Fig. 2 Examples of raw data recorded from the contralateral FDI (a) and affected FDI (b) of stroke subject#8. In each plot from top to bottom, the traces are as follows: force from y axis of the load cell (corresponds to force task in the y direction), force from the x axis of the load cell (corresponds to force task in the x direction), the first dorsal interosseous (FDI) surface EMG, the extensor digitorum communis (EDC) surface EMG
for both EMG–force pairs and % MsEMG EMG–force pairs. In addition, the average slope estimates obtained across all of our neurologically intact subjects were tested for statistical differences from the pooled slope estimates obtained on the contralateral as well as on the affected sides of our stroke subjects. In order to test for differences in the relative activation of the antagonist muscle, the ratio of EDC EMG/FDI EMG was computed for both sides of each stroke subject for the force directions in which slope estimates were computed, that is, the region including abduction, flexion and combinations of abduction/flexion. An unpaired t-test was performed between the values obtained from the two sides of each subject.
Results To assess the potential contributions of impaired control of muscle to the characteristic weakness of hand muscles in stroke survivors, we derived joint MCP force and FDI
To further characterize the severity of the stroke-induced motor deficit, we assessed the ability of our subjects to generate voluntary force in the first dorsal interosseus muscle in both flexion and abduction directions at the MCP joint. The maximum (averaged) force values obtained on the affected side were between 9 and 82 % of the maximum force produced on the contralateral side. On the affected side, the maximum voluntary force values ranged from 1.73 to 20.5 N, and on the contralateral side, they ranged from 11.8 to 30.8 N. Maximum force values were significantly higher (p
RESEARCH ARTICLE
Anomalous EMG–force relations during low-force isometric tasks in hemiparetic stroke survivors Nina L. Suresh · Nicole S. Concepcion · Janina Madoff · W. Z. Rymer
Received: 1 October 2012 / Accepted: 1 August 2014 / Published online: 17 September 2014 © Springer-Verlag Berlin Heidelberg 2014
Abstract Hemispheric brain injury resulting from a stroke is often accompanied by muscle weakness in contralateral limbs. In neurologically intact subjects, appropriate motoneuronal recruitment and rate modulation are utilized to optimize muscle force production. In the present study, we sought to determine whether weakness in an affected hand muscle in stroke survivors is partially attributable to alterations in the control of muscle activation. Specifically, our goal was to characterize whether the surface EMG amplitude was systematically larger as a function of (low) force in paretic hand muscles as compared to contralateral muscles in the same subject. We tested a multifunctional muscle, the first dorsal interosseous (FDI), in multiple directions about the second metacarpophalangeal joint in ten hemiparetic and six neurologically intact subjects. In six of the ten stroke subjects, the EMG–force slope was significantly greater
N. L. Suresh (*) · J. Madoff · W. Z. Rymer Sensory Motor Performance Program, Rehabilitation Institute of Chicago, 345 E Superior Street, Room 1378, Chicago, IL 60611, USA e-mail: [email protected] N. S. Concepcion Research Foundation at State University of New York, New York, NY, USA W. Z. Rymer Department of Physical Medicine and Rehabilitation, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA W. Z. Rymer Department of Physiology, Northwestern University, Chicago, IL, USA W. Z. Rymer Department of Biomedical Engineering, Northwestern University, Chicago, IL, USA
on the affected side as compared to the contralateral side, as well as compared to neurologically intact subjects. An unexpected set of results was a nonlinear relation between recorded EMG and generated force commonly observed in the paretic FDI, even at very low-force levels. We discuss possible experimental as well as physiological factors that may contribute to an increased EMG–force slope, concluding that changes in motor unit (MU) control are the most likely reasons for the observed changes. Keywords Electromyography · First dorsal interosseous · Paresis · Stroke
Introduction Hemispheric brain injury resulting from a stroke is often accompanied by weakness of voluntary movement in the limbs contralateral to the injury, as part of the “upper motoneuron” syndrome. This weakness has been attributed, in large part, to a loss of descending cortical excitatory input to segmental neurons. Although it is inherently plausible, there is surprisingly little direct evidence for this hypothesis. Alternative explanations such as changes in muscle properties as a function of disuse or changes in the efficacy of spinal segmental activation of motoneurons (MN) within a MN pool could also play a role. Regardless of whether changes in descending drive or changes in muscle properties occur, appropriate motoneuronal activation is necessary to optimize muscle force production utilizing residual muscular elements. To explain further, under normal conditions force gradation during voluntary contraction is generated primarily through the coordinated recruitment and rate modulation of motor units. If motor unit activation is ineffectual, such as when
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16
the firing rate of the motor unit is not well matched to the contractile properties of the innervated muscle fibers, then a greater portion of the MN pool might be required to reach a specified force level. This ineffectual activation could be accompanied by a greater level of motor unit recruitment for a given force, resulting in a larger surface EMG signal. We have known for some time that there may be major abnormalities of motor unit recruitment and rate modulation in muscles of paretic limbs. For example, Tang and Rymer (1981) reported a significant increase in the slope of the (surface) EMG–force relation during steady-state force contractions in the affected biceps brachii of human stroke survivors. Descriptions of motor unit discharge patterns in human spastic–paretic muscles are few in number, but those available support the existence of altered neural control of muscle (Rosenfalck and Andreassen 1980; Suresh et al. 2011; Hu et al. 2012). In an earlier study from our group, Gemperline et al. (1995) reported that more than half the tested stroke subjects exhibited significant reductions in mean motor unit discharge rate (at a fixed force level) in the paretic biceps brachii. Additionally, most study subjects exhibited a striking compression of the motoneuronal recruitment force range as well as limited rate modulation. In light of the uncertainty as to the origin of neural contributions to muscle weakness, as well as the possibility that proximal and distal muscles exhibit different impairment patterns with respect to force production (Thomas and del Valle 2001; Zijdewind and Thomas 2003), the objective of our present study was to use surface EMG and joint force recordings to determine whether weakness in a hand muscle in stroke survivors is at least partially attributable to alterations in the neural control of the motor units in these affected muscles. Here, the surface EMG signal is a gauge of the level of muscle activity required to generate a given amount of force. Our study was performed in the first dorsal interosseous (FDI), a multifunctional muscle that is activated for a variety of force directions about the second metacarpophalangeal (MCP) joint. Accordingly, we computed and made comparisons of the EMG–force slopes in paretic, contralateral and intact controls, in multiple force directions. This allowed us to test the uniformity of any EMG–force slope increases on the paretic side and in turn allowed us to understand whether changes in the pattern of antagonist and synergist muscle activation contribute to any observed differences. To derive EMG–force slope estimates, consecutive time periods of constant force and EMG signals obtained during the rising phase of a slow ramp low-force level task were used, thus enabling the characterization of the EMG–force relation over a continuous but low-force range and in a variety of force directions. The stationarity of the EMG signal over large [100 % maximum voluntary contractions (MVC)] forces during a 5 s ramp has been previously reported (Bilodeau et al. 1997).
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Exp Brain Res (2015) 233:15–25
Our primary finding is that in the paretic FDI of the majority of our stroke subjects, the EMG–force slope is significantly greater than slope estimates drawn from the contralateral FDI or in neurologically intact subjects. We report no systematic differences in the computed slopes between the three groups as a function of force task direction. An unexpected observation was that during the rising force phase, the EMG–force relation was nonlinear with a steep initial EMG slope followed by a reduced or flat slope in the paretic FDI only, even at relatively low-force levels. We discuss the possible neuromuscular mechanisms and experimental factors that might contribute to the observed anomalous EMG–force relations.
Methods Data collection We examined the activity of the first dorsal interosseous muscle (FDI) of ten hemiparetic stroke subjects and six neurologically intact subjects. Muscle activity was examined by recording surface EMG activity during controlled isometric force generation at the second metacarpophalangeal (MCP) joint. All participants gave informed consent via protocols approved by the Institutional Review Board under the Office for the Protection of Human Subjects at Northwestern University. Stroke participants Stroke participants were adults who had sustained a hemiparetic stroke at least 6 months prior to experimental testing. A research physical therapist evaluated the ability of the participants to complete the specified finger tasks as well, the ability to attain and maintain the experimental sitting posture and performed the Fugl-Meyer and the ChedokeMcMaster hand clinical assessments on both sides of our hemiparetic stroke subjects. Neurologically intact participants Our neurologically intact subjects were, on average, ageand sex-matched. A clinical assessment of our intact subjects was performed by the research physical therapist to affirm the lack of neurological injuries and/or motor deficits. Experimental setup Study participants were seated upright in a Biodex chair with their upper arm comfortably resting on a plastic support. In order to help standardize hand position as well as to minimize activity of unrecorded muscles, the forearm was
Exp Brain Res (2015) 233:15–25
17
Fig. 1 Experimental setup. a The forearm is cast and firmly clamped at the wrist in a metal ring with a plastic interface. The index finger is cast and is then inserted into a vice attached to the load cell. The other fingers are splayed and held in place with a Velcro strap, and
the thumb is placed in a plastic insert. Schematic representation of the task force plane. b The axes represent four primary isometric force directions, i.e., abduction, adduction, flexion and extension. Each quadrant is a linear combination of these primary directions
casted and placed in a ring-mount interface attached to an elbow rest: This rest was securely mounted with magnetic stands to a heavy steel table. The right shoulder was placed in 45° of abduction and neutral rotation, the elbow in 60° of flexion, the forearm in full pronation, and the wrist was held neutral with respect to flexion/extension. The 3rd–5th digits were comfortably splayed and strapped to the support surface. The 1st digit was secured at a 60° angle to the 2nd digit. The 2nd digit was placed in line with the second metacarpal and the long axis of the forearm creating a 0° or neutral (abduction/adduction) metacarpophalangeal (MCP) joint angle. To ensure maximal isolation of the FDI muscle, specially designed finger vises were attached to a six degrees-of-freedom load cell (JR3, Inc. and ATI, Inc), such that the index finger, which was cast, was coupled to the load cell at the proximal phalanx of the 2nd digit (Fig. 1a). The proximal interphalangeal (PIP) and distal interphalangeal (DIP) joints were left uncast.
EMG–force slope estimates to those force tasks generated in quadrant III. Data collected from the other quadrants were used to assess whether there was abnormal activation of the paretic FDI as an antagonist and thus provide insight as to whether antagonist coactivation may be a contributing factor to any observed increases in EMG–force slopes. The recordings from x, y and z coordinates of the force generated at the MCP joint were band passed (DC-200 Hz) and digitized at a sampling rate of 1 kHz. Force in the z direction, which is outside the force generation plane, was used to monitor the generated forces.
Force coordinate plane and force recordings In the experimental apparatus described above, isometric adduction about the second MCP joint was designated a positive horizontal deviation (+x) and isometric abduction to a negative horizontal deviation (−x) in the plane perpendicular to the index finger. Isometric extension about the MCP joint was designated as a positive vertical deviation (+y) and isometric flexion to a negative deviation (−y). In this x–y plane (Fig. 1b), angles from 180 to 270 or quadrant III are combinations of abduction and flexion. In this study, we limited the
Participant instructions Participants were instructed to generate isometric forces in abduction, flexion, extension and combinations of abduction/ flexion and abduction/extension. For each trial, the subject was instructed to slowly (approximately 10 s to peak force) generate force in a given radial direction and then slowly reduce the force level to 0, thereby generating an isometric force ramp. However, stroke subjects were not always able to generate force in all directions on both the paretic and contralateral sides. Attainable directions were repeated 2–3 times, in random order, with a minimum of 20 s between each force ramp. To aid participants control the forces they exerted, two-dimensional forces (vertical and horizontal) were displayed on an oscilloscope placed before them. Each stroke subject was tested on their paretic side first, in order to determine the force range for testing on the nonparetic side. The subjects were provided with practice
13
18
trials and were familiar and able to perform the isometric force tasks. The objective of the study was to assess EMG– force slopes during low-force contractions and to compare the EMG–force slopes over the same force range on both sides of a given subject. Thus, (absolute) force levels were consistent between the two sides of one subject but varied across the pool of tested stroke subjects. During the first trial of each session, subjects were asked to perform isometric (maximum voluntary contraction) MVCs in the primary directions of abduction and flexion, with each direction repeated twice, although not all stroke subjects could generate MVCs in both directions. Subjects were given 5 min of rest between each MVC contractions. EMG recordings Small, surface electrodes that include self-contained preamplifiers (Delsys, Inc.) were placed on the skin surface covering the FDI for EMG recordings. The EMG electrodes were placed in a similar orientation over the FDI for both sides of every tested stroke subject and for our intact subjects. In five stroke subjects, we were able to obtain surface recordings from the extensor digitorum communis (EDC) as well. For all surface EMG recordings, large reference electrodes were placed over the elbow on the same side as the recording. The EMG preamplifier has a bandwidth of 20–450 Hz for surface signals, which were digitized at a rate of 2 kHz (CED, Power 1401). Force and EMG signals were collected using the software program from CED, Spike2 (version 6), and were stored on a computer for subsequent analysis (Fig. 2). Data analysis EMG, force pairs To quantify the surface EMG signal, we computed the averaged, rectified (ARV) EMG. The ARV EMG was computed by first subtracting a 250 ms average of the precontraction, baseline (raw) EMG signal from the EMG trace for each trial. The EMG signal was then rectified and then subsequently averaged over 250 ms, stationary, nonoverlapping intervals during the rising phase of the force ramp task. The raw force signal, with a resting force value subtracted, was averaged over the same 250 ms (steady), nonoverlapping data windows. The output of this analysis was a set of EMG–force pairs computed from the rising phase of each force ramp trial. Slope computation: force direction and magnitude The EMG–force pairs were exported to our MATLAB program in order to perform slope calculations. We observed
13
Exp Brain Res (2015) 233:15–25
that on the affected side of our stroke subjects, the EMG– force relation was not always linear for the entire force ramp rise, instead there were often trials in which the EMG–force plot exhibited two or more distinct regions, including a flattened, decreasing or steeply rising second slope (Fig. 3a). To identify the linear regions of the EMG–force relations for the purposes of slope estimation, we used a method that utilized correlation coefficient computations over successively longer intervals of the EMG–force trace until the correlation coefficient began to decrease in value. Using cursors for visual confirmation and manual override, only the identified linear region was utilized for slope computation (Fig. 3b). These linear regions were identified for all three limbs (paretic, contralateral, and intact controls) and the force magnitude and task angle at which the nonlinear transition occurred was documented. Even for a single stroke subject, there was variability in the force range over which the EMG–force relation was linear. In order to make slope computations over a uniform force range between the two sides of one subject, we derived an average of the linear force ranges (LFR) obtained across all recorded force ramp trials for the affected side of each subject. The average force value was used as the largest force magnitude over which slope computations were performed on both the affected and contralateral sides of each subject. Regression analysis of the relationship between force direction and LFR, ramp force magnitude and LFR for each side of each stroke subject was determined utilizing a firstand second-order fit. The same analysis was performed for the regression analysis of slope ratio (affected/contralateral) as a function of direction for each side of each stroke subject. The r-squared values for each fit were computed and recorded. The maximum surface EMG (MsEMG) was obtained by averaging the steady-state region of the rectified surface EMG signal over a 1 s interval. The largest MsEMG obtained during repeat trials (4–5) of maximal voluntary force (in any direction) was used for further analysis. The MsEMG EMG was calculated for every subject, for each side. A second set of slopes was computed utilizing the EMG–force pairs and % MsEMG EMG force pairs for each side separately. Statistical comparisons between the two sides were made (see below). Statistical assessment The computed slope values were tested for statistical significance using SPSS (SPSS, Inc.) software. Unpaired t-tests were performed between the slope estimates derived from the affected side compared with slope estimates derived from the contralateral side of each stroke subject
Exp Brain Res (2015) 233:15–25
19
EMG measurements for the impaired hand and for the contralateral hand and compared these results with the responses of FDI muscles in control subjects. Table 1 provides a summary of the Fugl-Meyer and Chedoke-McMaster clinical assessments that were performed as well as other relevant information for our tested stroke subjects. Our clinical assessments show that there was a wide range of motor impairments on the affected side and our stroke subjects were comparatively unimpaired on the contralateral side. Experimental assessment of muscle weakness in stroke subjects
Fig. 2 Examples of raw data recorded from the contralateral FDI (a) and affected FDI (b) of stroke subject#8. In each plot from top to bottom, the traces are as follows: force from y axis of the load cell (corresponds to force task in the y direction), force from the x axis of the load cell (corresponds to force task in the x direction), the first dorsal interosseous (FDI) surface EMG, the extensor digitorum communis (EDC) surface EMG
for both EMG–force pairs and % MsEMG EMG–force pairs. In addition, the average slope estimates obtained across all of our neurologically intact subjects were tested for statistical differences from the pooled slope estimates obtained on the contralateral as well as on the affected sides of our stroke subjects. In order to test for differences in the relative activation of the antagonist muscle, the ratio of EDC EMG/FDI EMG was computed for both sides of each stroke subject for the force directions in which slope estimates were computed, that is, the region including abduction, flexion and combinations of abduction/flexion. An unpaired t-test was performed between the values obtained from the two sides of each subject.
Results To assess the potential contributions of impaired control of muscle to the characteristic weakness of hand muscles in stroke survivors, we derived joint MCP force and FDI
To further characterize the severity of the stroke-induced motor deficit, we assessed the ability of our subjects to generate voluntary force in the first dorsal interosseus muscle in both flexion and abduction directions at the MCP joint. The maximum (averaged) force values obtained on the affected side were between 9 and 82 % of the maximum force produced on the contralateral side. On the affected side, the maximum voluntary force values ranged from 1.73 to 20.5 N, and on the contralateral side, they ranged from 11.8 to 30.8 N. Maximum force values were significantly higher (p
