Research Report
Effects of Treadmill Training on Gait in a Hemiparetic Patient
JÓnina Waagfjörd Pamela K Levangie Catherine ME Certo
The purpose of this study was to investigate the effects of treadmill training on temporal-distance gait variables. An A-B-A treatment-withdrawal, single-subject experimental design was used on a hemiparetic patient who was 3 years postinjury. The inked footprint method was used to obtain the variables of walking velocity, cadence, base of support, stride length, and step length. Treatment was a maximum of 10 minutes on a motorized treadmill without elevation at a comfortable walking speed. Data collection for all three phases (A-B-A) and treadmill training during the treatment phase were performed three times per week for 3 weeks. Data were analyzed using a celeration line approach and a C statistic. Treatment was found to affect the base of support and right step length. An increase in symmetry between right and left step length was apparent after treadmill training. There was no effect on right or left stride length, left step length, cadence, or walking velocity. The results indicate improvement in some aspects of gait with treadmill training in the patient studied. Further research is needed to confirm the generalizability of these findings and to identify which patients might benefit from treadmill training. [Waagfjord f, Levangie PK, Certo CME. Effects of treadmill training on gait in a hemiparetic patient. Phys Ther. 1990;70:549-560] K e y Words: Cerebrovascular accident; Gait; Hemiplegia, Tests and measurements, functional; Treadmill.
Individuals who experience cerebrovascular accidents (CVAs) go through extensive treatment programs designed to restore the patient's previous functional capabilities. The most
frequently stated functional goal of patients who have experienced a CVA is restoration of the ability to walk.1 Gait training, therefore, is an important part of treatment programs, with
J Waagfjord, MS, PT, is Staff Physical Therapist, Braintree Hospital, 250 Pond St, Braintree, MA 02184. She was a student in the master's degree program, Department of Physical Therapy, Sargent College of Allied Health Professions, Boston University, Boston, MA, when this study was conducted in partial fulfillment of her degree requirements. P Levangie, MS, PT, is Assistant Professor and Coordinator of Entry-level Programs, Sargent College of Allied Health Professions, Boston University, 1 University Rd, Boston, MA 02215. Address all correspondence to Ms Levangie. C Certo, ScD, PT, is Associate Professor and Chair, Sargent College of Allied Health Professions, Boston University. This study was approved by the Human Subject Research Review Committee of Boston University's Sargent College of Allied Health Professions. This article was submitted October 4, 1989, and was accepted May 22, 1990.
a substantial amount of rehabilitation time devoted to restoring optimal gait. Many of those who achieve functional ambulation, however, continue to demonstrate gait patterns that deviate from normal.2 In order to reduce the gait deviations seen in patients who are functional ambulators, new treatment strategies for gait training continue to be sought. Nelson3 used the Kinetron®* for retraining reciprocal stepping motion. The treatment group showed greater improvement in ambulation velocity than did the comparison group receiving conventional physical therapy. Brown and DeBacher4 used a bicycle ergometer together with electromyographic (EMG) feedback to treat muscle hypertonia in patients
*Cybex, Div of Lumex Inc, 2100 Smithtown Ave, Ronkonkoma, NY 11779.
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with spastic hemiparesis. After treatment, improvements in gait were observed, including absence of hip circumduction, decreased trunk flexion during swing-through, and increased hip extension in the stance phase. In view of positive effects on gait that have been shown when exercises promote reciprocal movements of the legs, devices such as the treadmill warrant investigation. The treadmill has been used in hospital settings for many years for testing patients with cardiac and pulmonary disorders. It has become a standard pan of these patients' rehabilitation programs, used to increase both strength and endurance.5 The potential musculoskeletal or neuromuscular benefits of the treadmill on patients' performance are just beginning to receive the attention of investigators. Baker6 used a treadmill to rehabilitate one group of patients following femoral neck fracture, while a control group walked on a level surface. Results indicated that the treadmill group was superior to the control group on all temporal-distance (TD) gait variables measured, including velocity, cadence, stride length, and amount of time spent in doublesupport phases of stance. Baker6 recommended the treadmill as an effective training device for practicing functionally improved gait patterns. He noted that speed and distance walked can be adapted to the patient's requirements and that cardiovascular monitoring during exercise was simple. However, practicing on a treadmill can only be expected to lead to functional gains in patients with lower extremity dysfunction if it approximates the requirements of functional ambulation. Many studies have demonstrated the similarities between treadmill walking and walking on a level surface. Murray and associates7 found that lower extremity EMG activity and kinematics did not differ markedly between treadmill and floor walking. Ralston8 found that in healthy subjects no significant difference existed in energy cost between treadmill and
floor walking. Although the energy cost of walking among hemiparetic patients has been shown to be greater than that in healthy subjects at similar speeds, both hemiparetic patients and healthy subjects who walk at selfdetermined, comfortable speeds have similar energy consumption levels.9 Consequently, it is reasonable to assume that a hemiparetic patient walking on a treadmill at a selfselected, comfortable walking speed will consume the same amount of energy in level-surface walking and will approximate the kinetic and kinematic requirements of walking on a level surface. Evidence of therapeutic benefits from treadmill walking can be demonstrated by improvement in objectively measured variables. Gait variables such as TD measures have been shown to be indicators of improvement in gait1011 and can be accurately and reliably measured using the ink footprint method of gait analysis.1213 Although the footprint method of gait assessment can be used to document change, its use in a sample of hemiparetic patients can pose problems, given the high variability in gait among hemiplegic patients.1415 Because these patients, as a group, are heterogeneous, changes in TD gait characteristics over time would . be hard to document. A single-subject design, however, prevents individual variation from being masked by the average performance of the group. Sex, age, diagnosis, onset of disease, and level of disability are also kept constant. By statistically analyzing the measured variables in a single-subject study, even a small treatment effect can be detected. The purpose of this study, therefore, was to use a single-subject design to determine the effects of treadmill training on TD gait variables in a hemiparetic patient. These variables included right and left stride length, right and left step length, base of support, cadence, and walking velocity. We hypothesized that training on a treadmill would improve measured TD gait values. Results of this study
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may provide evidence to clinicians of an alternative method of gait training applicable to selected patients with gait deviations secondary to hemiparesis.
Method An A-B-A treatment-withdrawal, singlesubject design was used in this study. The designation A-B-A refers to a three-phase design that identifies the way the intervention is offered. In this design, the study is initiated by recording the measured variables at baseline (A) without any intervention. The measured variables are then recorded during the period when the intervention is applied (B). In the final phase, the variables are measured when the intervention is removed. This phase is a return to baseline (A), which can also be designated as the treatment-withdrawal phase. The subject for the study was chosen based on having a diagnosis of unilateral hemiparesis after a CVA, with onset at least 6 months prior to participation in the study. The recovery interval was selected to ensure the medical stability of the patient and to minimize functional gains independent of the intervention. The subject had to be able to walk independently with no assistive devices and to be capable of using a treadmill without relying on the railing. Patients with unstable medical conditions or other major pathological conditions were excluded from the study, as were patients with major perceptual disorders, marked cognitive disturbances, apraxia, receptive aphasia, or decreased attention span. The subject had to be sufficiently informed and motivated to complete the study. A physician at the Reykjavik City Hospital (Reykjavik, Iceland) identified a potential subject after reviewing the selection criteria. We relied on the judgment of the physician and the patient's physical therapist relative to inclusion and exclusion criteria. The subject was a 40-year-old woman who had suffered a CVA, resulting in leftsided hemiparesis, 3 years prior to
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the beginning of the study. Her angiogram showed a thrombus in the right middle cerebral artery. The subject had begun her rehabilitation as an inpatient. After discharge from the hospital, she continued physical therapy twice weekly for about a year. Concentration in treatment was on reducing spasticity and muscle tightness in the left lower extremity. In ambulation, this spasticity and muscle tightness were manifested by the subject's difficulty in advancing her left limb because of inadequate knee flexion and by her strong foot grasp with weight bearing. Thirteen months before her recruitment into the study, the subject returned to physical therapy for a 5-week period, receiving treatment three times weekly. In summary, the subject received physical therapy for 1 year post-CVA and again for one 5-week period in the second year after her CVA. She did not undergo any physical therapy for the 12-month period preceding her agreement to participate in the study. The subject signed an informed consent statement.
Procedure The study took place at Reykjavik City Hospital in the Rehabilitation Department. Footprint data were collected three times per week for 3 weeks during each of the three study phases (A-B-A) (27 trials over 9 weeks). Data collection took place at the same time of day for all trials, and the subject wore the same shoes for all trials. During the baseline (A-I) and treatment-withdrawal (A-II) phases, the subject came in solely for collection of footprint data. During the treatment phase (B), treadmill training and collection of footprint data were both included in the visit. Treatment during phase B consisted of training three times weekly for 3 weeks on a motor-driven Burdick® treadmill,‡ which was kept level. Before the treatment period started,
the subject performed one practice trial on the treadmill to familiarize herself with the device and the procedure. At the start of each treatment, the treadmill speed was slowly increased by the principal investigator (JW) to what the subject identified as a comfortable level. The subject was not allowed to grasp the rails of the treadmill except while reaching her chosen gait speed and while decelerating at the end of the session. The maximum speed of the treadmill was recorded for each session. Heart rate and blood pressure measurements were taken before each treatment, 5 minutes into the treatment, and at the end of treatment. The Borg scale and Karvonen's formula were used as safety guidelines for treatment time. Treadmill training was to continue for 10 minutes unless the subject exceeded set limits for perceived exertion or heart rate. The perceived exertion limit was an indication of more than 12 on the Borg scale. A Borg scale value of 12 is considered to be approximately 60% of maximal oxygen consumption.1617 The recommended training pulse rate calculated by Karvonen's formula was used to establish the target heart rate for training.18 If the subject exceeded the calculated value, treatment was stopped. Footprint data collection for each session of the baseline, treatment, and treatment-withdrawal phases was conducted similarly, with the exception that footprint data were collected both before and after treadmill training during the treatment phase to permit assessment of both immediate and longer-term effects. Strips of moleskin were applied to the soles of the subject's shoes, one strip across the greatest width of the sole of the shoe and another along the length of the shoe from the midpoint of the heel along a line approximating the
†
Burdick® Model TMS-400, The Burdick Corp, Milton, WI 53563.
longitudinal axis of the second metatarsal. The subject performed one practice trial on a 9-m paper pathway before ink was applied to the moleskin. The moleskin was then inked with water-based ink, the right foot in red and the left foot in blue. The subject was instructed to walk down the length of the paper pathway at what she felt was a comfortable walking speed. The pathway was marked with lines 1.5 m from either end, leaving a central 6-m area in which data should be unaffected by any changes attributable to initial acceleration or concluding deceleration. Using a digital stopwatch,‡ ambulation time was measured as the time between the first foot contact inside the central area and the first foot contact outside the central area. Cadence was determined by the number of steps taken during the measured ambulation time and recorded as steps per minute. Walking velocity was the distance covered divided by the measured ambulation time, recorded in meters per second. Using the footprints included in the calculation of cadence, lines of progression were drawn from the reference point of one footprint to the reference point of the next ipsilateral footprint. The reference point for each foot was the intersection of the two moleskin strips. Base of support, stride length, and step length were determined referencing the lines of progression (Fig. 1). All data were reduced by the principal investigator. To ascertain intrarater reliability of the measured footprint variables (ie, step length, stride length, and base of support), data from one trial were reduced twice. Intraclass correlation coefficients (ICC [1,1]) were calculated on these two series of measurements.19 Intrarater reliability of walking velocity and cadence measurements could not be assessed because the timing of the trial could not be repeated. An ICC value of .90 or better was considered acceptable. The ICCs obtained are presented in Table 1.
‡
Aristo Model, Frank DePrisco Inc, Boston, MA 02108.
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were plotted and analyzed both visually and statistically. A “split-middle," or celeration line, approach was used. The celeration line divides the data of each phase into equal halves, with 50% of the data points above the line and 50% below. The effect of treatment is visually evaluated by assessing change in level or trend of the celeration lines in the baseline and treatment phases. A similar assessment can indicate the effect of treatment withdrawal by comparing the celeration lines for the treatment and treatmentwithdrawal phases. A change in level of the celeration line from one phase to the next indicates variation in the average performance on the measured variable, while a change in trend would indicate acceleration or deceleration of effect. The slope of the celeration line and the mean variable value for a phase were also calculated. Figure 1 - Schematic drawing of ink footprint record and measurement of gait variables. Base of support - perpendicular distance (in centimeters) from line of progression to reference point of contralateral footprint; stride length = distance (in centimeters) from one reference point to next ipsilateral reference point; step length = distance (in centimeters) between reference point of one footprint and reference point of next contralateral footprint. Data Analysis Footprint data were measured for each trial. Because each trial consisted of a series of steps, strides, and bases of support, mean values for these variables for each trial were calculated and used in subsequent analyses. For walking velocity and cadence, only one mean value was obtained per trial. Data were assessed for serial dependency by computing an autocorrelation coefficient.20 Data that demonstrate statistically significant coefficients may complicate visual analysis and interfere with further statistical interpretation. The presence of serial dependency in data, therefore, suggests that conclusions about those data should be made cautiously. The values obtained for each variable from each trial across all three phases
T a b l e 1 • Intrarater Reliability for Footprint Variables Variablea
df
Walking velocity Cadence Base of support
.9994
8,9
Stride length (R)
.9995
3,4
Stride length (L)
.9994
4,5
Step length (R)
.9923
3,4
Step length (L)
.9908
4,5
a
Intrarater reliability could not be assessed for walking velocity and cadence because the investigator could not time the same trial twice.
b
ICC = intraclass correlation coefficient (1,1).
has been a treatment effect (a change between baseline and treatment phases). If the C statistic is applied to the treatment data and those data are found to be stable, treatment and treatment-withdrawal data can be combined and analyzed with the C statistic. A significant result would indicate a change in performance after termination of treatment (treatment-withdrawal effect). When a significant trend exists in the initial data, usefulness of the C statistic to assess treatment effect or treatmentwithdrawal effect is more limited.2021 In such instances, we chose to rely on
Statistical analysis of single-subject data can serve as an adjunct to visual analysis. The C statistic is one procedure that can be used on small data sets and is sensitive both to the overall variability of the data and to possible trends in the data.20 The C statistic is first used to assess baseline data. If no trend exists in these data, the baseline and treatment phase data are combined and the C statistic is again computed. A statistically significant test result would indicate that there
Table 2.
ICCb
Means and Standard Errors for Each
Variable
Phasea A-l Variable
Walking velocity (m/sec) Cadence (steps/min)
X
B SE
A-ll
X
SE
X
SE
0.76
0.02
0.82
0.01
0.79
0.02
94.87
1.98
94.22
1.40
95.89
1.34
Base of support (cm)
14.33
0.37
11.89
0.42
11.89
0.35
Stride length (L) (cm)
105.56
1.13
111.67
1.08
108.67
1.30
Stride length (R) (cm)
105.78
0.97
111.44
1.18
108.00
1.14
Step length (L) (cm)
57.44
0.69
58.44
0.58
57.33
0.85
Step length (R) (cm)
48.00
1.01
53.22
0.70
50.33
0.58
“A-I = baseline phase; B = treatment phase; A-II = treatment-withdrawal phase.
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visual analysis alone. The statistical significance of the C statistic is computed using a Z score.20 A probability value of .05 or less was accepted as statistically significant. Results The patient completed all trials in all phases without exceeding heart rate or perceived exertion limits. Footprint data were reduced by the principal investigator and the mean values for each variable for each trial were ascertained. Table 2 presents the mean values and the standard errors for each variable for each phase. Data and celeration lines for each variable are shown in Figures 2 through 8. The mean variable values for each phase and the slopes of the celeration lines are also indicated (Figs. 2-8).
Figure 2 . Graphical presentation of walking velocity data for each trial and phase. Phase A-I = baseline, phase B = treatment; phase A-II = treatment withdrawal.
Table 3 presents the autocorrelation coefficients for each variable. Data demonstrated no serial dependency with the exception of right step length in the treatment-withdrawal phase. Both visual and statistical analyses of a variable can be affected by serial dependency, so a significant correlation should be taken into consideration in interpretation of results for that phase. Table 4 reports the 2 scores for the C statistics computed on baseline and treatment phases and on both treatment and treatmentwithdrawal effects. Discussion There was an observed trend in the direction of treatment effect seen in the baseline data for all variables. Although sufficient time should have been accorded to permit stabilization of baseline data, time constraints prevented extension of the baseline phase. The C statistic was used to augment visual analysis by indicating where trends in baseline or treatment data were significant and where treatment and treatment-withdrawal effects could be validly assessed. Visual inspection revealed a substantial accelerating trend in the baseline
Figure 3. Graphical presentation of cadence data for each trial and phase. Phase A-I = baseline; phase B = treatment; phase A-II = treatment withdrawal. phase for walking velocity (Fig. 2). Because the C statistic confirmed a significant trend in the baseline phase, the data from the baseline and treatment phases could not be combined to assess treatment effects using the C statistic (Tab. 4). Extension of the baseline celeration line into the
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treatment phase would lead to the conclusion that there was a decrease in velocity with treatment (all but one data point fell below the extended celeration line). For cadence, the slight trends seen in the baseline and treatment phases
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(Fig. 3) were not found to be significant using the C statistic. No significant treatment effects of treadmill training were evident when baseline and treatment data were combined. The visual trends seen for base of support (Fig. 4) in the baseline and treatment phases were not of sufficient magnitude to be statistically significant. When data from the baseline and treatment phases were combined, a significant decrease in base of support with treatment was supported. Because base of support increases with the need for increased stability, a decrease in base of support would appear to be consistent with improvement in gait. Both left and right stride lengths had significant trends in the baseline phase (Figs. 5, 6), preventing assessment of treatment effect using the C statistic. Extension of the baseline celeration line into the treatment phase shows the treatment phase data points about evenly split above and below the line. This would be consistent with no treatment effect.
Figure 4 . Graphical presentation of base-of-support data for each trial and phase. Phase A-I — baseline; phase B = treatment; phase A-II = treatment withdrawal.
For right step length (Fig. 7), the trends seen visually within phases were not found to be significant. The C-statistic analysis showed evidence of both treatment and treatmentwithdrawal effects. Of the variables for which the effects of treatment withdrawal could be assessed, only the C statistic for right step length was statistically significant. The trends seen in left step length (Fig. 8) were similar to those seen for right step length (Fig. 7) and were not found to be significant using the C statistic. Combining baseline and treatment phase data did not show evidence of a significant treatment effect. It should be noted that treatmentwithdrawal data on right step length did exhibit serial dependency. Tryon21 supports the use of the C statistic with serial dependent data and concludes that the dependency does not affect the results of the statistic. That is, right step length improved with use
Figure 5. Graphical presentation of right stride-length data for each trial and phase. Phase A-I = baseline; phase B = treatment; phase A-II = treatment withdrawal. of the treadmill and deteriorated when training was withdrawn. The increase in right step length during treatment brought the right step length closer to that of the contralateral limb, improving the symmetry of step length. A post hoc analysis of step symmetry was conducted as another
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way of assessing improvement in step symmetry. Data for both right and left step lengths for each phase were plotted on the same graph (Fig. 9). The Pearson product-moment correlation coefficients between these variables were computed for each phase. Also corn-
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The increase in right step length and resulting improved step symmetry shown in our study indicate improved function in the subject's hemiparetic left limb. The larger right step can be accomplished only if there is an increase in stance time on the affected limb. Because decreased stance time on the affected limb is a prominent factor in hemiplegic gait,15 improvements in this gait variable are particularly desirable. The increase in stance time on the affected limb may well account for the decrease in walking velocity seen with treatment. This diminished velocity may, to some extent, suggest improved rather than diminished function. Both the increase in stance symmetry and the decrease in velocity also are in accordance with the decrease in base of support, which would imply a Figure 6- Graphical presentation of left stride-length data for each trial and phase. diminished need for stability during ambulation. Phase A-I = baseline; phase B = treatment; phase A-II = treatment withdrawal. Considering visual inspection, celeration line assessment, and C-statistic analysis, positive effects of treatment are suggested for right step length and base of support. For a number of measured variables, however, there are apparent decreases in function during the treatment phase. Some of this decrease may have been explained by the improvement in step symmetry. Another component of the decrease may be due to a perceived loss of motivation by the subject. Initially, the principal investigator perceived the patient to be very eager to participate. In the last 3 weeks of the study, her enthusiasm appeared to wane as she complained about the necessity of frequent visits to the physical therapy department. Data in this study were collected from a Figure 7. Graphical presentation of right step-length data for each trial and phase. patient who was 3 years postinjury. The gait training on the treadmill was Phase A-I = baseline, phase B = treatment; phase A-II = treatment withdrawal. the only treatment she had received in over a year. She was also a fullputed was the difference between the tations are shown in Table 5. Analyses time ambulator who should have staarea under the curve of the right stepof step lengths support improvement bilized her gait pattern by this point length data and the area under the in step-length symmetry during treatin her recovery. The data analyses curve of the left step-length data for ment, with the effect diminishing supporting a treatment effect with each phase. Symmetrical steps would somewhat when treatment was treadmill training seem to be valid yield a difference of zero, whereas withdrawn. given this patient's background. The large values indicate increased asympatient also reported experiencing metry. Results of both sets of compurelief during treatment from a persisPhysical Therapy/Volume 70, Number 9/September 1990 Downloaded from https://academic.oup.com/ptj/article-abstract/70/9/549/2728687 by Frankfurt Univesity Library user on 22 January 2018
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tent pain in her paretic leg, resulting in more flexibility in her gait. She reported that the pain returned shortly after the treatment phase ended. Clinical Implications The conclusions drawn from this study are based on the results from only one subject and are valid for this single subject only. Generalization of findings from such an investigation is a controversial matter22 and customarily necessitates replication of intervention effects. The careful choice of subjects based on type and severity of injury would be important in subsequent studies, as previous studies have demonstrated varied results for patients with different functional abilities and etiology.12 The treatment effect seen with our patient in this study was small, but could be clinically relevant. Presuming this same treatment effect can be demonstrated in other hemiparetic patients or a subgroup of hemiparetic patients, small gains may mean the difference between independent ambulation or more limited mobility. One of the benefits of a single-subject design is the ability to detect small, but potentially important, treatment effects. Conventional studies would require very large sample sizes to detect such small effects. Small gains may result in the ability to ambulate greater distances or in reduced energy expenditure. Improved treatment effectiveness over a large number of patients may result in a substantial reduction in the costs of rehabilitative care through earlier discharge from the hospital or physical therapy. It is also possible that greater improvements may be found when treadmill training is extended beyond the 3-week training period we were able to implement. The evaluation tools used in this study were chosen for their simplicity and clinical applicability. More sensitive instrumentation might produce different results. Measurement of additional variables such as muscle activity through use of electromyogra-
Figure 8 . Graphical presentation of left step-length data for each trial and phase. Phase A-I = baseline; phase B = treatment; phase A-II = treatment withdrawal.
Figure 9 . Graphical presentation of right and left step-length data showing differences between the two sets of data. Phase A-I = baseline; phase B — treatment; phase A-II = treatment withdrawal. phy might demonstrate effects in muscle performance that could not be identified in our study. Similarly, measurement of physiological variables may show evidence of effects of treadmill training on endurance and on other cardiovascular variables in hemiparetic patients. Results of our single-
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subject design study are compelling enough to justify further investigation of the use of treadmill training with this patient population, including extending the treatment time beyond the 3 weeks during which we were able to implement treatment.
Physical Therapy/Volume 70, Number 9/September 1990
T a b l e 3 . Autocorrelation Coefficients (r) for Each Variable and Phase Phasea Variable
A-l
B
A--ll
Walking velocity
.393
.005
.468
Cadence
.064
.146
.468
research is needed to confirm the effects seen in our study, to identify which patients are most likely to benefit from this kind of treatment, and to identify other benefits that may be seen with treadmill training. Acknowledgments
Base of support
.033
.320
.264
Stride length (L)
.556
.022
.375
Stride length (R)
.539
.222
.447
Step length (L)
.441
.022
.066
Step length (R)
.216
.317
.685b
We thank Vilborg Gudmundsdottir and the staff at Reykjavik City Hospital for their invaluable assistance in conducting the study and Dr Kristjan Thorarinsson for his help with graphical presentation of the data. References
A-I = baseline phase; B = treatment phase; A-II = treatment-withdrawal phase. b
P < .05.
T a b l e 4 . Z Scores for C Statistics for Measured Gait Variables
Variable
Baseline Phase (A-l)
Treatment Phase (B)
Treatment Effect (A-l + B)
TreatmentWithdrawal Effect (A-II + B)
Walking velocity
2.517a
Cadence
1.225
0.445
...
0.867
1.255
1.519
1.598 a
Base of support
0.845
0.816
2.372
Stride length (L)
2.776a
0.241
...
0.118
1.593
Stride length (R)
2.780a
0.560
...
0.080
Step length (L)
1.361
0.039
0.682
0.263
Step length (R)
1.576
0.850
2.520a
2.113b
a
Z > 1.64; P < .05.
b
Z>2.18;P
Effects of Treadmill Training on Gait in a Hemiparetic Patient
JÓnina Waagfjörd Pamela K Levangie Catherine ME Certo
The purpose of this study was to investigate the effects of treadmill training on temporal-distance gait variables. An A-B-A treatment-withdrawal, single-subject experimental design was used on a hemiparetic patient who was 3 years postinjury. The inked footprint method was used to obtain the variables of walking velocity, cadence, base of support, stride length, and step length. Treatment was a maximum of 10 minutes on a motorized treadmill without elevation at a comfortable walking speed. Data collection for all three phases (A-B-A) and treadmill training during the treatment phase were performed three times per week for 3 weeks. Data were analyzed using a celeration line approach and a C statistic. Treatment was found to affect the base of support and right step length. An increase in symmetry between right and left step length was apparent after treadmill training. There was no effect on right or left stride length, left step length, cadence, or walking velocity. The results indicate improvement in some aspects of gait with treadmill training in the patient studied. Further research is needed to confirm the generalizability of these findings and to identify which patients might benefit from treadmill training. [Waagfjord f, Levangie PK, Certo CME. Effects of treadmill training on gait in a hemiparetic patient. Phys Ther. 1990;70:549-560] K e y Words: Cerebrovascular accident; Gait; Hemiplegia, Tests and measurements, functional; Treadmill.
Individuals who experience cerebrovascular accidents (CVAs) go through extensive treatment programs designed to restore the patient's previous functional capabilities. The most
frequently stated functional goal of patients who have experienced a CVA is restoration of the ability to walk.1 Gait training, therefore, is an important part of treatment programs, with
J Waagfjord, MS, PT, is Staff Physical Therapist, Braintree Hospital, 250 Pond St, Braintree, MA 02184. She was a student in the master's degree program, Department of Physical Therapy, Sargent College of Allied Health Professions, Boston University, Boston, MA, when this study was conducted in partial fulfillment of her degree requirements. P Levangie, MS, PT, is Assistant Professor and Coordinator of Entry-level Programs, Sargent College of Allied Health Professions, Boston University, 1 University Rd, Boston, MA 02215. Address all correspondence to Ms Levangie. C Certo, ScD, PT, is Associate Professor and Chair, Sargent College of Allied Health Professions, Boston University. This study was approved by the Human Subject Research Review Committee of Boston University's Sargent College of Allied Health Professions. This article was submitted October 4, 1989, and was accepted May 22, 1990.
a substantial amount of rehabilitation time devoted to restoring optimal gait. Many of those who achieve functional ambulation, however, continue to demonstrate gait patterns that deviate from normal.2 In order to reduce the gait deviations seen in patients who are functional ambulators, new treatment strategies for gait training continue to be sought. Nelson3 used the Kinetron®* for retraining reciprocal stepping motion. The treatment group showed greater improvement in ambulation velocity than did the comparison group receiving conventional physical therapy. Brown and DeBacher4 used a bicycle ergometer together with electromyographic (EMG) feedback to treat muscle hypertonia in patients
*Cybex, Div of Lumex Inc, 2100 Smithtown Ave, Ronkonkoma, NY 11779.
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with spastic hemiparesis. After treatment, improvements in gait were observed, including absence of hip circumduction, decreased trunk flexion during swing-through, and increased hip extension in the stance phase. In view of positive effects on gait that have been shown when exercises promote reciprocal movements of the legs, devices such as the treadmill warrant investigation. The treadmill has been used in hospital settings for many years for testing patients with cardiac and pulmonary disorders. It has become a standard pan of these patients' rehabilitation programs, used to increase both strength and endurance.5 The potential musculoskeletal or neuromuscular benefits of the treadmill on patients' performance are just beginning to receive the attention of investigators. Baker6 used a treadmill to rehabilitate one group of patients following femoral neck fracture, while a control group walked on a level surface. Results indicated that the treadmill group was superior to the control group on all temporal-distance (TD) gait variables measured, including velocity, cadence, stride length, and amount of time spent in doublesupport phases of stance. Baker6 recommended the treadmill as an effective training device for practicing functionally improved gait patterns. He noted that speed and distance walked can be adapted to the patient's requirements and that cardiovascular monitoring during exercise was simple. However, practicing on a treadmill can only be expected to lead to functional gains in patients with lower extremity dysfunction if it approximates the requirements of functional ambulation. Many studies have demonstrated the similarities between treadmill walking and walking on a level surface. Murray and associates7 found that lower extremity EMG activity and kinematics did not differ markedly between treadmill and floor walking. Ralston8 found that in healthy subjects no significant difference existed in energy cost between treadmill and
floor walking. Although the energy cost of walking among hemiparetic patients has been shown to be greater than that in healthy subjects at similar speeds, both hemiparetic patients and healthy subjects who walk at selfdetermined, comfortable speeds have similar energy consumption levels.9 Consequently, it is reasonable to assume that a hemiparetic patient walking on a treadmill at a selfselected, comfortable walking speed will consume the same amount of energy in level-surface walking and will approximate the kinetic and kinematic requirements of walking on a level surface. Evidence of therapeutic benefits from treadmill walking can be demonstrated by improvement in objectively measured variables. Gait variables such as TD measures have been shown to be indicators of improvement in gait1011 and can be accurately and reliably measured using the ink footprint method of gait analysis.1213 Although the footprint method of gait assessment can be used to document change, its use in a sample of hemiparetic patients can pose problems, given the high variability in gait among hemiplegic patients.1415 Because these patients, as a group, are heterogeneous, changes in TD gait characteristics over time would . be hard to document. A single-subject design, however, prevents individual variation from being masked by the average performance of the group. Sex, age, diagnosis, onset of disease, and level of disability are also kept constant. By statistically analyzing the measured variables in a single-subject study, even a small treatment effect can be detected. The purpose of this study, therefore, was to use a single-subject design to determine the effects of treadmill training on TD gait variables in a hemiparetic patient. These variables included right and left stride length, right and left step length, base of support, cadence, and walking velocity. We hypothesized that training on a treadmill would improve measured TD gait values. Results of this study
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may provide evidence to clinicians of an alternative method of gait training applicable to selected patients with gait deviations secondary to hemiparesis.
Method An A-B-A treatment-withdrawal, singlesubject design was used in this study. The designation A-B-A refers to a three-phase design that identifies the way the intervention is offered. In this design, the study is initiated by recording the measured variables at baseline (A) without any intervention. The measured variables are then recorded during the period when the intervention is applied (B). In the final phase, the variables are measured when the intervention is removed. This phase is a return to baseline (A), which can also be designated as the treatment-withdrawal phase. The subject for the study was chosen based on having a diagnosis of unilateral hemiparesis after a CVA, with onset at least 6 months prior to participation in the study. The recovery interval was selected to ensure the medical stability of the patient and to minimize functional gains independent of the intervention. The subject had to be able to walk independently with no assistive devices and to be capable of using a treadmill without relying on the railing. Patients with unstable medical conditions or other major pathological conditions were excluded from the study, as were patients with major perceptual disorders, marked cognitive disturbances, apraxia, receptive aphasia, or decreased attention span. The subject had to be sufficiently informed and motivated to complete the study. A physician at the Reykjavik City Hospital (Reykjavik, Iceland) identified a potential subject after reviewing the selection criteria. We relied on the judgment of the physician and the patient's physical therapist relative to inclusion and exclusion criteria. The subject was a 40-year-old woman who had suffered a CVA, resulting in leftsided hemiparesis, 3 years prior to
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the beginning of the study. Her angiogram showed a thrombus in the right middle cerebral artery. The subject had begun her rehabilitation as an inpatient. After discharge from the hospital, she continued physical therapy twice weekly for about a year. Concentration in treatment was on reducing spasticity and muscle tightness in the left lower extremity. In ambulation, this spasticity and muscle tightness were manifested by the subject's difficulty in advancing her left limb because of inadequate knee flexion and by her strong foot grasp with weight bearing. Thirteen months before her recruitment into the study, the subject returned to physical therapy for a 5-week period, receiving treatment three times weekly. In summary, the subject received physical therapy for 1 year post-CVA and again for one 5-week period in the second year after her CVA. She did not undergo any physical therapy for the 12-month period preceding her agreement to participate in the study. The subject signed an informed consent statement.
Procedure The study took place at Reykjavik City Hospital in the Rehabilitation Department. Footprint data were collected three times per week for 3 weeks during each of the three study phases (A-B-A) (27 trials over 9 weeks). Data collection took place at the same time of day for all trials, and the subject wore the same shoes for all trials. During the baseline (A-I) and treatment-withdrawal (A-II) phases, the subject came in solely for collection of footprint data. During the treatment phase (B), treadmill training and collection of footprint data were both included in the visit. Treatment during phase B consisted of training three times weekly for 3 weeks on a motor-driven Burdick® treadmill,‡ which was kept level. Before the treatment period started,
the subject performed one practice trial on the treadmill to familiarize herself with the device and the procedure. At the start of each treatment, the treadmill speed was slowly increased by the principal investigator (JW) to what the subject identified as a comfortable level. The subject was not allowed to grasp the rails of the treadmill except while reaching her chosen gait speed and while decelerating at the end of the session. The maximum speed of the treadmill was recorded for each session. Heart rate and blood pressure measurements were taken before each treatment, 5 minutes into the treatment, and at the end of treatment. The Borg scale and Karvonen's formula were used as safety guidelines for treatment time. Treadmill training was to continue for 10 minutes unless the subject exceeded set limits for perceived exertion or heart rate. The perceived exertion limit was an indication of more than 12 on the Borg scale. A Borg scale value of 12 is considered to be approximately 60% of maximal oxygen consumption.1617 The recommended training pulse rate calculated by Karvonen's formula was used to establish the target heart rate for training.18 If the subject exceeded the calculated value, treatment was stopped. Footprint data collection for each session of the baseline, treatment, and treatment-withdrawal phases was conducted similarly, with the exception that footprint data were collected both before and after treadmill training during the treatment phase to permit assessment of both immediate and longer-term effects. Strips of moleskin were applied to the soles of the subject's shoes, one strip across the greatest width of the sole of the shoe and another along the length of the shoe from the midpoint of the heel along a line approximating the
†
Burdick® Model TMS-400, The Burdick Corp, Milton, WI 53563.
longitudinal axis of the second metatarsal. The subject performed one practice trial on a 9-m paper pathway before ink was applied to the moleskin. The moleskin was then inked with water-based ink, the right foot in red and the left foot in blue. The subject was instructed to walk down the length of the paper pathway at what she felt was a comfortable walking speed. The pathway was marked with lines 1.5 m from either end, leaving a central 6-m area in which data should be unaffected by any changes attributable to initial acceleration or concluding deceleration. Using a digital stopwatch,‡ ambulation time was measured as the time between the first foot contact inside the central area and the first foot contact outside the central area. Cadence was determined by the number of steps taken during the measured ambulation time and recorded as steps per minute. Walking velocity was the distance covered divided by the measured ambulation time, recorded in meters per second. Using the footprints included in the calculation of cadence, lines of progression were drawn from the reference point of one footprint to the reference point of the next ipsilateral footprint. The reference point for each foot was the intersection of the two moleskin strips. Base of support, stride length, and step length were determined referencing the lines of progression (Fig. 1). All data were reduced by the principal investigator. To ascertain intrarater reliability of the measured footprint variables (ie, step length, stride length, and base of support), data from one trial were reduced twice. Intraclass correlation coefficients (ICC [1,1]) were calculated on these two series of measurements.19 Intrarater reliability of walking velocity and cadence measurements could not be assessed because the timing of the trial could not be repeated. An ICC value of .90 or better was considered acceptable. The ICCs obtained are presented in Table 1.
‡
Aristo Model, Frank DePrisco Inc, Boston, MA 02108.
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were plotted and analyzed both visually and statistically. A “split-middle," or celeration line, approach was used. The celeration line divides the data of each phase into equal halves, with 50% of the data points above the line and 50% below. The effect of treatment is visually evaluated by assessing change in level or trend of the celeration lines in the baseline and treatment phases. A similar assessment can indicate the effect of treatment withdrawal by comparing the celeration lines for the treatment and treatmentwithdrawal phases. A change in level of the celeration line from one phase to the next indicates variation in the average performance on the measured variable, while a change in trend would indicate acceleration or deceleration of effect. The slope of the celeration line and the mean variable value for a phase were also calculated. Figure 1 - Schematic drawing of ink footprint record and measurement of gait variables. Base of support - perpendicular distance (in centimeters) from line of progression to reference point of contralateral footprint; stride length = distance (in centimeters) from one reference point to next ipsilateral reference point; step length = distance (in centimeters) between reference point of one footprint and reference point of next contralateral footprint. Data Analysis Footprint data were measured for each trial. Because each trial consisted of a series of steps, strides, and bases of support, mean values for these variables for each trial were calculated and used in subsequent analyses. For walking velocity and cadence, only one mean value was obtained per trial. Data were assessed for serial dependency by computing an autocorrelation coefficient.20 Data that demonstrate statistically significant coefficients may complicate visual analysis and interfere with further statistical interpretation. The presence of serial dependency in data, therefore, suggests that conclusions about those data should be made cautiously. The values obtained for each variable from each trial across all three phases
T a b l e 1 • Intrarater Reliability for Footprint Variables Variablea
df
Walking velocity Cadence Base of support
.9994
8,9
Stride length (R)
.9995
3,4
Stride length (L)
.9994
4,5
Step length (R)
.9923
3,4
Step length (L)
.9908
4,5
a
Intrarater reliability could not be assessed for walking velocity and cadence because the investigator could not time the same trial twice.
b
ICC = intraclass correlation coefficient (1,1).
has been a treatment effect (a change between baseline and treatment phases). If the C statistic is applied to the treatment data and those data are found to be stable, treatment and treatment-withdrawal data can be combined and analyzed with the C statistic. A significant result would indicate a change in performance after termination of treatment (treatment-withdrawal effect). When a significant trend exists in the initial data, usefulness of the C statistic to assess treatment effect or treatmentwithdrawal effect is more limited.2021 In such instances, we chose to rely on
Statistical analysis of single-subject data can serve as an adjunct to visual analysis. The C statistic is one procedure that can be used on small data sets and is sensitive both to the overall variability of the data and to possible trends in the data.20 The C statistic is first used to assess baseline data. If no trend exists in these data, the baseline and treatment phase data are combined and the C statistic is again computed. A statistically significant test result would indicate that there
Table 2.
ICCb
Means and Standard Errors for Each
Variable
Phasea A-l Variable
Walking velocity (m/sec) Cadence (steps/min)
X
B SE
A-ll
X
SE
X
SE
0.76
0.02
0.82
0.01
0.79
0.02
94.87
1.98
94.22
1.40
95.89
1.34
Base of support (cm)
14.33
0.37
11.89
0.42
11.89
0.35
Stride length (L) (cm)
105.56
1.13
111.67
1.08
108.67
1.30
Stride length (R) (cm)
105.78
0.97
111.44
1.18
108.00
1.14
Step length (L) (cm)
57.44
0.69
58.44
0.58
57.33
0.85
Step length (R) (cm)
48.00
1.01
53.22
0.70
50.33
0.58
“A-I = baseline phase; B = treatment phase; A-II = treatment-withdrawal phase.
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visual analysis alone. The statistical significance of the C statistic is computed using a Z score.20 A probability value of .05 or less was accepted as statistically significant. Results The patient completed all trials in all phases without exceeding heart rate or perceived exertion limits. Footprint data were reduced by the principal investigator and the mean values for each variable for each trial were ascertained. Table 2 presents the mean values and the standard errors for each variable for each phase. Data and celeration lines for each variable are shown in Figures 2 through 8. The mean variable values for each phase and the slopes of the celeration lines are also indicated (Figs. 2-8).
Figure 2 . Graphical presentation of walking velocity data for each trial and phase. Phase A-I = baseline, phase B = treatment; phase A-II = treatment withdrawal.
Table 3 presents the autocorrelation coefficients for each variable. Data demonstrated no serial dependency with the exception of right step length in the treatment-withdrawal phase. Both visual and statistical analyses of a variable can be affected by serial dependency, so a significant correlation should be taken into consideration in interpretation of results for that phase. Table 4 reports the 2 scores for the C statistics computed on baseline and treatment phases and on both treatment and treatmentwithdrawal effects. Discussion There was an observed trend in the direction of treatment effect seen in the baseline data for all variables. Although sufficient time should have been accorded to permit stabilization of baseline data, time constraints prevented extension of the baseline phase. The C statistic was used to augment visual analysis by indicating where trends in baseline or treatment data were significant and where treatment and treatment-withdrawal effects could be validly assessed. Visual inspection revealed a substantial accelerating trend in the baseline
Figure 3. Graphical presentation of cadence data for each trial and phase. Phase A-I = baseline; phase B = treatment; phase A-II = treatment withdrawal. phase for walking velocity (Fig. 2). Because the C statistic confirmed a significant trend in the baseline phase, the data from the baseline and treatment phases could not be combined to assess treatment effects using the C statistic (Tab. 4). Extension of the baseline celeration line into the
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treatment phase would lead to the conclusion that there was a decrease in velocity with treatment (all but one data point fell below the extended celeration line). For cadence, the slight trends seen in the baseline and treatment phases
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(Fig. 3) were not found to be significant using the C statistic. No significant treatment effects of treadmill training were evident when baseline and treatment data were combined. The visual trends seen for base of support (Fig. 4) in the baseline and treatment phases were not of sufficient magnitude to be statistically significant. When data from the baseline and treatment phases were combined, a significant decrease in base of support with treatment was supported. Because base of support increases with the need for increased stability, a decrease in base of support would appear to be consistent with improvement in gait. Both left and right stride lengths had significant trends in the baseline phase (Figs. 5, 6), preventing assessment of treatment effect using the C statistic. Extension of the baseline celeration line into the treatment phase shows the treatment phase data points about evenly split above and below the line. This would be consistent with no treatment effect.
Figure 4 . Graphical presentation of base-of-support data for each trial and phase. Phase A-I — baseline; phase B = treatment; phase A-II = treatment withdrawal.
For right step length (Fig. 7), the trends seen visually within phases were not found to be significant. The C-statistic analysis showed evidence of both treatment and treatmentwithdrawal effects. Of the variables for which the effects of treatment withdrawal could be assessed, only the C statistic for right step length was statistically significant. The trends seen in left step length (Fig. 8) were similar to those seen for right step length (Fig. 7) and were not found to be significant using the C statistic. Combining baseline and treatment phase data did not show evidence of a significant treatment effect. It should be noted that treatmentwithdrawal data on right step length did exhibit serial dependency. Tryon21 supports the use of the C statistic with serial dependent data and concludes that the dependency does not affect the results of the statistic. That is, right step length improved with use
Figure 5. Graphical presentation of right stride-length data for each trial and phase. Phase A-I = baseline; phase B = treatment; phase A-II = treatment withdrawal. of the treadmill and deteriorated when training was withdrawn. The increase in right step length during treatment brought the right step length closer to that of the contralateral limb, improving the symmetry of step length. A post hoc analysis of step symmetry was conducted as another
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way of assessing improvement in step symmetry. Data for both right and left step lengths for each phase were plotted on the same graph (Fig. 9). The Pearson product-moment correlation coefficients between these variables were computed for each phase. Also corn-
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The increase in right step length and resulting improved step symmetry shown in our study indicate improved function in the subject's hemiparetic left limb. The larger right step can be accomplished only if there is an increase in stance time on the affected limb. Because decreased stance time on the affected limb is a prominent factor in hemiplegic gait,15 improvements in this gait variable are particularly desirable. The increase in stance time on the affected limb may well account for the decrease in walking velocity seen with treatment. This diminished velocity may, to some extent, suggest improved rather than diminished function. Both the increase in stance symmetry and the decrease in velocity also are in accordance with the decrease in base of support, which would imply a Figure 6- Graphical presentation of left stride-length data for each trial and phase. diminished need for stability during ambulation. Phase A-I = baseline; phase B = treatment; phase A-II = treatment withdrawal. Considering visual inspection, celeration line assessment, and C-statistic analysis, positive effects of treatment are suggested for right step length and base of support. For a number of measured variables, however, there are apparent decreases in function during the treatment phase. Some of this decrease may have been explained by the improvement in step symmetry. Another component of the decrease may be due to a perceived loss of motivation by the subject. Initially, the principal investigator perceived the patient to be very eager to participate. In the last 3 weeks of the study, her enthusiasm appeared to wane as she complained about the necessity of frequent visits to the physical therapy department. Data in this study were collected from a Figure 7. Graphical presentation of right step-length data for each trial and phase. patient who was 3 years postinjury. The gait training on the treadmill was Phase A-I = baseline, phase B = treatment; phase A-II = treatment withdrawal. the only treatment she had received in over a year. She was also a fullputed was the difference between the tations are shown in Table 5. Analyses time ambulator who should have staarea under the curve of the right stepof step lengths support improvement bilized her gait pattern by this point length data and the area under the in step-length symmetry during treatin her recovery. The data analyses curve of the left step-length data for ment, with the effect diminishing supporting a treatment effect with each phase. Symmetrical steps would somewhat when treatment was treadmill training seem to be valid yield a difference of zero, whereas withdrawn. given this patient's background. The large values indicate increased asympatient also reported experiencing metry. Results of both sets of compurelief during treatment from a persisPhysical Therapy/Volume 70, Number 9/September 1990 Downloaded from https://academic.oup.com/ptj/article-abstract/70/9/549/2728687 by Frankfurt Univesity Library user on 22 January 2018
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tent pain in her paretic leg, resulting in more flexibility in her gait. She reported that the pain returned shortly after the treatment phase ended. Clinical Implications The conclusions drawn from this study are based on the results from only one subject and are valid for this single subject only. Generalization of findings from such an investigation is a controversial matter22 and customarily necessitates replication of intervention effects. The careful choice of subjects based on type and severity of injury would be important in subsequent studies, as previous studies have demonstrated varied results for patients with different functional abilities and etiology.12 The treatment effect seen with our patient in this study was small, but could be clinically relevant. Presuming this same treatment effect can be demonstrated in other hemiparetic patients or a subgroup of hemiparetic patients, small gains may mean the difference between independent ambulation or more limited mobility. One of the benefits of a single-subject design is the ability to detect small, but potentially important, treatment effects. Conventional studies would require very large sample sizes to detect such small effects. Small gains may result in the ability to ambulate greater distances or in reduced energy expenditure. Improved treatment effectiveness over a large number of patients may result in a substantial reduction in the costs of rehabilitative care through earlier discharge from the hospital or physical therapy. It is also possible that greater improvements may be found when treadmill training is extended beyond the 3-week training period we were able to implement. The evaluation tools used in this study were chosen for their simplicity and clinical applicability. More sensitive instrumentation might produce different results. Measurement of additional variables such as muscle activity through use of electromyogra-
Figure 8 . Graphical presentation of left step-length data for each trial and phase. Phase A-I = baseline; phase B = treatment; phase A-II = treatment withdrawal.
Figure 9 . Graphical presentation of right and left step-length data showing differences between the two sets of data. Phase A-I = baseline; phase B — treatment; phase A-II = treatment withdrawal. phy might demonstrate effects in muscle performance that could not be identified in our study. Similarly, measurement of physiological variables may show evidence of effects of treadmill training on endurance and on other cardiovascular variables in hemiparetic patients. Results of our single-
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subject design study are compelling enough to justify further investigation of the use of treadmill training with this patient population, including extending the treatment time beyond the 3 weeks during which we were able to implement treatment.
Physical Therapy/Volume 70, Number 9/September 1990
T a b l e 3 . Autocorrelation Coefficients (r) for Each Variable and Phase Phasea Variable
A-l
B
A--ll
Walking velocity
.393
.005
.468
Cadence
.064
.146
.468
research is needed to confirm the effects seen in our study, to identify which patients are most likely to benefit from this kind of treatment, and to identify other benefits that may be seen with treadmill training. Acknowledgments
Base of support
.033
.320
.264
Stride length (L)
.556
.022
.375
Stride length (R)
.539
.222
.447
Step length (L)
.441
.022
.066
Step length (R)
.216
.317
.685b
We thank Vilborg Gudmundsdottir and the staff at Reykjavik City Hospital for their invaluable assistance in conducting the study and Dr Kristjan Thorarinsson for his help with graphical presentation of the data. References
A-I = baseline phase; B = treatment phase; A-II = treatment-withdrawal phase. b
P < .05.
T a b l e 4 . Z Scores for C Statistics for Measured Gait Variables
Variable
Baseline Phase (A-l)
Treatment Phase (B)
Treatment Effect (A-l + B)
TreatmentWithdrawal Effect (A-II + B)
Walking velocity
2.517a
Cadence
1.225
0.445
...
0.867
1.255
1.519
1.598 a
Base of support
0.845
0.816
2.372
Stride length (L)
2.776a
0.241
...
0.118
1.593
Stride length (R)
2.780a
0.560
...
0.080
Step length (L)
1.361
0.039
0.682
0.263
Step length (R)
1.576
0.850
2.520a
2.113b
a
Z > 1.64; P < .05.
b
Z>2.18;P
