Archives of Physical Medicine and Rehabilitation
Volume 87, Issue 4 , Pages 482-489, April 2006

Oxygen Consumption During Machine-Assisted and Unassisted Walking: A Pilot Study in Hemiplegic and Healthy Humans

  • Delphine David, BSc(PT)

      Affiliations

    • Departments of Rehabilitation and Physiology-Functional Testing, Raymond Poincaré Teaching Hospital, AP-HP, Garches, France
    • ,
  • Jean-Philippe Regnaux, BSc(PT)

      Affiliations

    • Departments of Rehabilitation and Physiology-Functional Testing, Raymond Poincaré Teaching Hospital, AP-HP, Garches, France
    • ,
  • Michèle Lejaille, AAS

      Affiliations

    • Departments of Rehabilitation and Physiology-Functional Testing, Raymond Poincaré Teaching Hospital, AP-HP, Garches, France
    • ,
  • Alain Louis, AAS

      Affiliations

    • Departments of Rehabilitation and Physiology-Functional Testing, Raymond Poincaré Teaching Hospital, AP-HP, Garches, France
    • ,
  • Bernard Bussel, MD

      Affiliations

    • Departments of Rehabilitation and Physiology-Functional Testing, Raymond Poincaré Teaching Hospital, AP-HP, Garches, France
    • ,
  • Frédéric Lofaso, MD, PhD

      Affiliations

    • Departments of Rehabilitation and Physiology-Functional Testing, Raymond Poincaré Teaching Hospital, AP-HP, Garches, France
    • INSERM Research Unit 492, Créteil, France
    • Corresponding Author InformationCorrespondence to Frédéric Lofaso, MD, PhD, Service de Physiologie-Explorations Fonctionnelles, Hôpital Raymond Poincaré, 92380 Garches, France. Reprints are not available from the author.

Article Outline

Abstract 

David D, Regnaux J-P, Lejaille M, Louis A, Bussel B, Lofaso F. Oxygen consumption during machine-assisted and unassisted walking: a pilot study in hemiplegic and healthy humans.

Objective

To determine whether a gait-training (GT) machine influenced walking time duration and oxygen consumption in hemiplegic patients.

Design

Repeated measures with comparison of 2 groups.

Setting

Physiology laboratories in a rehabilitation hospital.

Participants

Seven patients with stroke-related hemiplegia (2 men, 5 women; age, 46±11y; time since stroke, 12±9wk) and 7 healthy subjects (3 men, 4 women; age, 30±7y).

Interventions

Floor walking (FW) and GT-assisted walking with and without 50% body-weight support (BWS).

Main Outcome Measures

Walking time duration, oxygen consumption (V̇o2), minute ventilation (V̇e), and heart rate.

Results

When the condition effect was analyzed independently from the group, mean V̇o2 was higher during FW than during the GT tests (post hoc analysis: FW vs GT, P=.017; FW vs GT+BWS, P<.002). When the groups were compared independently of the condition, the group with hemiplegia had a significantly shorter walking time duration (analysis of variance [ANOVA], P<.001) and a significantly higher V̇o2 as a percentage of baseline (ANOVA, P=.03), compared with the controls. Walking time duration was influenced by walking condition (ANOVA, P<.001; post hoc analysis: FW vs GT, P<.001; FW vs GT+BWS, P<.001). V̇e was influenced by walking condition (ANOVA, P=.043; not significant in the post hoc analysis) and was higher in the group with hemiplegia (ANOVA, P=.02). Heart rate was not influenced by walking condition (P=.11). A group effect was found with heart rate in cycles per minute (P=.035) but not as a percentage of baseline. No interaction was found between the ANOVA group-effect factor and the ANOVA walking-condition effect factor.

Conclusions

Compared with FW, GT assistance increased walking time duration and reduced V̇o2 in patients with severe hemiplegia.

Key Words:  Oxygen consumption , Rehabilitation , Stroke , Walking

 

STROKE SURVIVORS OFTEN have a physically inactive lifestyle that limits their performance during activities of daily living, increases their risk of falling, and possibly contributes to increase their risk of recurrent stroke and cardiovascular disease. Therefore, patients with stroke may benefit from interventions aimed at increasing their level of physical activity. Although many patients with stroke recover some ambulation, their walking distance is often reduced by spasticity, poor balance, impairment of plantarflexion, and impairment of motor control of the affected lower extremity. The pattern of walking recovery is variable. In a study by Wade et al,1 only 22% of 45 patients who were unable to walk during the first days after a stroke recovered normal walking within the next 3 months. Thus, walking performance improvement is a major objective of rehabilitation therapy after stroke. Several methods are available for reaching this objective. Conventional rehabilitation consists of daily sessions of physical therapy (PT), kinesiotherapy, and occupational therapy.2 PT may include overground walking, not only forward,2, 3, 4, 5 but also backward, sideways, and up and down stairs.4 To increase step length, visual cues can be supplied in the form of footprints placed at intervals appropriate for the patient’s height.4 When step length is normal or nearly normal, patients are encouraged to walk faster.4, 5 Alternatively, treadmill training may allow patients to practice a task that is closely similar to normal walking, which is not the case with cycle-ergometer training.6 In addition, faster cadence and better gait symmetry were observed with treadmill walking than with overground walking.3 With a treadmill, exercise intensity is easy to adjust, and the patient can use the handrail for support. In patients with severe neurologic deficits, however, other methods may be needed. Finch and Barbeau7 suggested treadmill training with the patient suspended in a modified climbing harness to control weight shifting, balance, and stepping. This partial body-weight support (BWS) has been reported to help improve walking and postural abilities in patients with stroke.8 However, because treadmill training with BWS requires 2 therapists to assist the movement of nonambulatory hemiparetic subjects,9 attention has turned to gait-training (GT) machines, which can be used with only 1 therapist.9 Gait trainers enable patients recovering from spinal cord injury (SCI) or stroke to practice a gait-like movement with minimal assistance from therapists. Using the Lokomat,10,a a computer-controlled motorized robotic orthosis mounted on a treadmill and used to test normal subjects, Dietz et al11 found that lower-extremity muscle activity decreased with body unloading and that no activity was detectable with 100% unloading, suggesting that input from load receptors may play a key role in generating locomotor activity associated with robot-assisted GT. In addition, electromyographic activity in lower-extremity muscles during unilateral motion was bilateral in healthy participants but was restricted to the moving side in patients with SCI,11 indicating that interlimb coordination required supraspinal input. A study of another gait trainerb in patients with stroke9 showed that the rhythmic electromyographic activity of partially weight-bearing lower-limb muscles was similar in terms of pattern and amount to that observed with a treadmill. However, although GT-induced motion and lower-extremity muscle electromyographic activity were synchronized, the tibialis anterior electromyographic activity on the unaffected side was less active and the biceps femoris electromyographic activity on the affected side more active with the gait trainer than with the treadmill.9

Finally, these studies did not provide a global and quantitative index of effort, and it was unclear whether using a gait trainer resulted in a reduction or increase in expenditure during ambulation training in people with stroke. To investigate this point, we evaluated oxygen consumption (V̇o2) and cardiopulmonary responses in subjects with stroke during floor walking (FW), GT walking without BWS, and GT walking with 50% BWS. In an earlier study,12 paraplegic patients had less lower-extremity electromyographic activity than did healthy subjects when using the same gait trainer at the same speed. However, electromyographic activity was measured in 1 or 2 lower-extremity muscles, which may not have been representative of the activity of all other muscles and, therefore, of the walking energy cost. Because the changes in V̇o2 between baseline and walking can be used as a global index of walking-induced effort, we sought to determine whether V̇o2 was also decreased in patients with stroke compared with young healthy subjects.

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Methods 

Participants 

The study protocol was approved by our institutional review board, and informed consent was obtained from each study participant. Over a 4-month period between March and June 2004, we studied 7 consecutive patients with stroke admitted to the rehabilitation department of the Raymond Poincaré Teaching Hospital, Garches, France, for walking performance improvement. Inclusion criteria for the patients were (1) a 10-meter walking test13 (10MWT) time greater than 30 seconds, (2) a Functional Ambulation Category (FAC) Scale14 score no greater than 3 (needs assistance), and (3) sufficient cognitive function to participate in the study. We excluded patients with comorbidities or disabilities other than stroke that might interfere with gait. All patients underwent cerebral magnetic resonance imaging or computed tomography to confirm the diagnosis. We also studied 7 healthy subjects (controls). Table 1 lists the main features of the patients and controls.

Table 1. Characteristics of the 7 Patients With Stroke and 7 Healthy Controls
ParticipantsSexAge (y)Weight (kg)Height (cm)Diagnosis10MWT Velocity (km/h)FAC ScoreTime Since Stroke (wk)
1⁎F5366165Left HS.2729
2⁎F5952159Right MCAO.4514
3⁎F3466166Left MCAO.6528
4⁎F5872153Right MCAO.6135
5⁎F5050160Right MCAO.33229
6⁎M3065175Left HS.44220
7⁎M4060163Right MCAO.9539
8†F2357170Normal NA
9†F2459169Normal NA
10†F2555166Normal NA
11†M3785175Normal NA
12†M3475175Normal NA
13†M4074180Normal NA
14†M2682183Normal NA

Abbreviations: F, female; HS, hemorrhagic stroke; M, male; MCAO, middle cerebral artery occlusion; NA, not applicable.

⁎ Stroke subjects.

† Controls.

Experimental Set-Up 

The gait trainerb is shown in figure 1. The feet are secured to footplates that automatically simulate a gait-like motion. The 2 footplates move alternately backward and forward on an arc-like base. The backward movement replicates the stance phase and the forward movement the swing phase of the gait cycle, with a stance/swing ratio of 60/40.15 A servo-controlled motor assists the gait movement; the rotation speed of the gear system is constant, and the vertical and horizontal movements of the center of mass are controlled in a phase-dependent manner by ropes attached to the harness and connected to the gear system. For safety reasons, a defined overload was programmed so that the motor stopped when the patient was unable to follow the movement of the machine. The speed of the simulated gait could be set between 0 and 2.5km/h and stride length between 34 and 48cm. The gait trainer was equipped with a pulley for providing partial BWS if desired.

Each study participant wore a nose-clip and breathed via a mouthpiece during testing. Expired gas was analyzed using open-circuit spirometry with a metabolic measurement cart.c Volume and gases were calibrated before each test. Minute ventilation (V̇e) and V̇o2 were computed breath-by-breath16 and averaged over 20-second intervals.17 A 3-lead electrocardiogram provided continuous monitoring of heart rate,c which was averaged over 20-second intervals.17

Experimental Protocol 

In preparation for the exercise test, we asked study participants to refrain from eating and smoking during the 2 hours before testing18 and to avoid strenuous exertion during the 12 hours before testing. Before each test, baseline data were obtained with the study participant seated on a stool, back unsupported, until V̇o2 was stable for 3 minutes. The patients with stroke were asked to walk on the floor at their own speed, with 1 person providing the least possible assistance. Study participants walked along a corridor that was 30m long and 1.5m wide, with a handrail on each of the side walls. The patient was able to hold a handrail on one side and to receive assistance from a person walking on the other side. This person also checked the speed of the patient every 10m.

We conducted the three walking tests on 3 different days, in random order: FW, GT walking without BWS (GT), and GT walking with 50% BWS (GT+BWS). For each patient with stroke, the GT and FW tests were done at the speed recorded during the 10MWT (0.3−0.9km/h). Because the patients with stroke were unable to reach V̇o2max, or at least the anaerobic threshold, it was impossible to compare normal subjects and patients at the same percentage of V̇o2max. Therefore, the healthy controls performed the tests at the same mean speed as the patient group (10m in 72s). Similarly Brown and Kautz19 compared the mechanical work of the limbs in controls and patients with stroke at the same cycle-ergometer work load and speed. During the FW tests, the controls were told their walking speed every 10m so that they could adjust as needed; without this feedback, controls walked faster than the mean FW speed in the patients. The patients with stroke received help from a second person in turning at the end of the corridor and switching the holding hand to the other handrail in preparation for the next 30-m stretch. The study participants performed as many turns as needed until the end of the task.

All study participants received familiarization with the gait trainer before the test sessions. Subjects in both groups were instructed to hold the handrail with 1 hand during the FW test, if possible without bearing weight on it. Each test was preceded by a 6-minute rest period in the sitting position and was continued until exhaustion or until 6 minutes had elapsed, whichever occurred first. Exhaustion or fatigue was defined as an inability to continue the test.20 Thus, the GT tests ended when the motor switched off because the participant was unable to follow the movement, when the participant asked to stop, or when 6 minutes had elapsed.

Data Analysis 

The last 3 minutes of stable values in the seated position before each test were taken as the baseline values. During the tests, V̇e, V̇o2, and heart rate over the last three 20-second intervals were averaged to correspond to the last minute of the walking tests, which was either the sixth minute or the last minute before exhaustion.

Statistics 

Descriptive data are reported as means and standard deviations (SDs). Test data were expressed in absolute values and in percentages of baseline. Baseline data and test data were evaluated by repeated-measures analysis of variance (ANOVA) with the group (stroke, control) as the between-subjects factor and the walking condition (FW, GT, GT+BWS) as the within-subjects factor (repeated measures). An interaction between these 2 factors was looked for routinely. When ANOVA showed a statistically significant difference in the within-subjects factor, the Bonferroni a posteriori test was used for pairwise comparisons.

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Results 

Baseline Conditions 

Baseline data recorded before the 3 tests are reported in figure 2. No differences were found for V̇o2 (condition effect, P=.38; group effect, P=.09). In contrast, V̇e differed across the 3 walking conditions (ANOVA, P=.046; post hoc: FW vs GT, P<.17; FW vs GT+BWS, P<.24; GT vs GT+BWS, P=.85), whereas the between-group difference was not statistically significant (P=.10). Heart rate differed across the 3 walking conditions (ANOVA, P=.02; post hoc analysis: FW vs GT, P<.60; FW vs GT+BWS, P<.44; GT vs GT+BWS, P=.81), whereas the between-group difference was not statistically significant (P=.32). Finally, none of the post hoc analysis results were significant. In addition, no interactions were identified between walking condition and group for V̇o2, V̇e, or heart rate.

  • View full-size image.
  • Fig 2. 

    Values of (A) V̇o2, (B) V̇e, and (C) heart rate recorded at rest in the sitting position before the 3 tests (left panels) (FW, GT, GT+BWS) in patients with stroke (hatched bars) and in healthy subjects (solid bars). NOTE. Values are mean ± SD.

Walking Test Duration 

For the FW test, mean time to exhaustion was 151±35 seconds in the patients, with a mean speed of .51±.09km/h. The 7 controls and 1 of the patients were able to walk for 6 minutes during this test. In both GT conditions, all participants were able to simulate walking for 6 minutes. ANOVA showed a group effect (P<.001) and a condition effect (P<.001) on walking time duration (post hoc analysis: FW vs GT, P<.001; FW vs GT+BWS, P<.001; GT vs GT+BWS, P=1.00). No interactions were found between walking condition and group.

V̇o2 During Walking 

Mean V̇o2 during walking is reported in figure 3. When V̇o2 was expressed in mL·kg−1·min−1, there was a statistically significant difference across the 3 conditions (ANOVA, P<.001; post hoc analysis: FW vs GT, P=.017; FW vs GT+BWS, P<.002; but GT vs GT+BWS, P=.38). In contrast, no significant difference was found between the patients and controls (P>0.2). However, when V̇o2 was expressed as a percentage of the baseline value (see fig 3 right panels), it was significantly higher in the patients than in the controls (ANOVA, P=.03). No interaction was noted between the 2 ANOVA factors.

  • View full-size image.
  • Fig 3. 

    Values of (A) V̇o2, (B) V̇e, and (C) heart rate recorded during the 3 tests (FW, GT, GT+BWS) in patients with stroke (hatched bars) and in healthy subjects (solid bars). The left panel shows measured values and the right panel the data expressed as a percentage of values in the baseline seated condition. NOTE. Values are mean ± SD.

V̇e During Walking 

Mean V̇e values recorded during walking are reported in figure 3. There was a significant difference across the 3 conditions (ANOVA, P=.043, post hoc analysis: FW vs GT, P<.94; FW vs GT+BWS, P<.17; GT vs GT+BWS, P=.20). In addition, V̇e was higher in the patients than in the controls (ANOVA, group effect, P<.02). No interaction was identified between walking condition and group.

Heart Rate During Walking 

Mean heart rate data during walking are given in figure 2 (right panels). No significant differences were found across the 3 conditions (P=.11). A significant group effect was identified when heart rate was expressed in cycles per minute (P=.035) but not when heart rate was expressed as a percentage of the baseline value. No interaction was noted between walking condition and group.

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Discussion 

This study provides the first data on V̇o2 during a gait-like movement assisted by a gait trainer. V̇o2 expressed as a percentage of the baseline value was greater in patients than in controls under all walking conditions. In addition, V̇o2 was lower during GT-assisted walking than during FW, a fact that may explain the longer exercise duration with GT-assisted walking in the patients. Similar results were obtained for V̇e, although the between-group differences were not statistically significant and the effect on exercise duration was less marked. In contrast, heart rate was not affected by the walking condition. Post hoc analysis failed to find any difference between the 2 GT conditions.

The electromechanic gait trainer developed by Hesse et al15 is designed to simulate gait.9 As with a treadmill, walking speed is controlled by the machine. However, whereas the treadmill allows patients to control their walking parameters, the gait trainer controls step length and stance and swing phase durations, which can be set according to each patient’s needs. Accordingly, patients with stroke walked asymmetrically on the treadmill, with a typically shortened stance and increased swing duration of the affected limb,21 whereas movement on the gait trainer footplates was symmetric.3 Thus, patients can practice a symmetric, balanced, gait-like movement on the gait trainer. However, Hesse et al3 pointed out that simulation of the swing phase was far from perfect. The replication of gait-like movement is probably improved with a Lokomat-type device10 made up of length-adjustable leg braces mounted on a treadmill and driven by a computer-based real-time system that maintains the angles of the hip and knee joints within the ranges found in healthy subjects.10 However, the most important factor for improving walking performance is weight-bearing training of the affected limb during its stance phase.3

No significant differences in V̇o2 were found in our study between GT alone and GT+BWS. This may be due to the fact that weight bearing was reduced by only 50% in the BWS condition. A similar result was obtained in healthy subjects who used only 15% of BWS.22 In addition, because the study participants were allowed to hold the gait trainer handrail with 1 hand, the weight-bearing difference between GT and GT+BWS may have been less than 50%; using a handrail has been shown to reduce heart rate and V̇o2 at a given workload during treadmill walking.23 Nevertheless, our main objective was to compare GT with FW, and we estimated that keeping 1 hand on the rail was intermediate between minimal FW assistance and 50% BWS.

Gait Velocity 

Empirical data have shown that gait velocity in patients with stroke of varying severity ranges from approximately 0.18 to 1.03m/s.1, 21, 24, 25, 26 The speed of most of our patients was below this range (between .07 and .27m/s). This fact is ascribable to the severity of impairments in our study patients, who were recruited at a hospital department that provides rehabilitation to patients requiring prolonged hospitalization. Therefore, the results of this study need to be confirmed in patients with less severe hemiplegia.

Comparison of the Walking Conditions 

The gait-cycle motion is provided by the gait trainer, in theory with very little input from the patient. Interestingly, this situation shares similarities with controlled mechanical ventilation, in which the work of breathing is transferred from the patient to the machine; continued inspiratory muscle contraction occurs throughout machine-delivered breaths but requires less respiratory effort than during spontaneous breathing.27 With the gait trainer, and in a population similar to ours, Hesse et al9 found that the rhythmic activity of the weight-bearing lower-limb muscles was similar in terms of pattern and amount to that observed with a treadmill. However, it was unclear whether GT walking was associated with meaningful energy expenditure by the patient. We addressed this issue and found that GT decreased V̇o2 during walking, compared with FW, but that V̇o2 increased by more than 200% during GT walking compared with resting in the seated position.

Heart rate was not dependent on the exercise condition. Figure 2 suggests that this result may be ascribable to the higher heart rate in the patients during GT-assisted walking, as compared with FW. On the heart rate, the feet are secured to the machine and must follow the footplates, without assistance from another person. This may result in stress in some patients, leading to an increase in heart rate (see also below).

Passive movements activate afferents28 that stimulate breathing, leading to an abrupt increase in V̇e.29, 30, 31 The small effect of gait trainer use on V̇e in our study is in agreement with the literature and extends the observation of V̇e augmentation during passive bicycle exercising in healthy subjects30, 31 to GT walking in both healthy and hemiplegic subjects.

Comparison of Groups 

V̇o2, V̇e, and heart rate are the most pertinent indices for evaluating exercise, and they are usually related to both V̇e-V̇o2 and heart rate–V̇o2. These relationships have been considered to be linear during exertion below the anaerobic threshold (ie, when heart rate is <75% of the maximal predicted heart rate).32 Oddly, in our study, under baseline conditions, heart rate and V̇e in the patients were higher before the GT tests than before the FW test. In contrast, heart rate and V̇e were similar before the 3 tests in the healthy controls. The differences in the patients’ heart rate and V̇e under baseline conditions may be ascribable to stress or a modification in metabolism. Because no significant difference in V̇o2 was observed across the 3 conditions, a change in metabolism is unlikely. Furthermore, Delistraty et al33 demonstrated that mental stress influenced heart rate and V̇e independently from V̇o2. Again, this result may be ascribable to stress in the patients related to older age and to apprehension about having to follow the machine; the healthy controls, in contrast, enjoyed using the gait trainer at a speed far lower than their usual walking speed.

The V̇o2 result in our patients during FW corroborates studies in similar populations, including patients with severe stroke.2, 34, 35 In hemiplegic patients, the oxygen cost of walking varies with the degree of weakness, spasticity, and training, but is usually elevated compared with healthy subjects.36 Surprisingly, oxygen cost was similar in the patients and controls in our study. However, when oxygen cost measured under dynamic conditions was expressed as a percentage of the baseline value, the increase was significantly greater in the patients than in the controls, although speed of walking was the same in the 2 groups. The age difference between patients with hemiplegia and controls probably influenced our results. Nevertheless, previous studies examining the influence of aging on V̇o2 during submaximal and maximal exercise showed an inverse correlation between age and V̇o2 dynamics at exercise onset or V̇o2 at the anaerobic threshold37, 38 and at the V̇o2max.39 Therefore, including older healthy subjects would probably increase the differences that we found between patients with hemiplegia and healthy controls. These differences confirm that the same walking speed represented a greater effort in the patients than in the controls, who were younger and more physically fit. However, the controls walked more slowly than their normal and most efficient speed. Nevertheless, oxygen cost was lower with the gait trainer than during FW in both groups.

Walking Time Duration 

Only 1 hemiplegic patient completed the 6-minute FW test. The other patients were able to walk over the floor with or without assistance for 90 to 140 seconds. Hemiplegic patients make short steps because they cannot simultaneously extend the knee and flex the hip and ankle in the late swing phase.40 Walking requires both a high degree of central coordination and substantial peripheral effort in patients with hemiplegia. However, the V̇o2, heart rate, and V̇e values in the patients were far smaller than the theoretical maximal values. This suggests that cardiopulmonary fitness was not the limiting factor; although V̇o2 decreased significantly with the gait trainer, this effect was not large enough to fully explain the considerable increase in walking time duration.

General or central fatigue is a well-recognized problem in people with stroke.20, 36 In accordance with our cardiorespiratory results, in a study of patients similar to ours, Macko et al41 found that treadmill exercise termination was more often due to generalized fatigue than to cardiopulmonary intolerance or to hemiparetic lower-extremity fatigue. The longer walking time during the GT tests than the FW test in our study may be ascribable to limitation by central fatigue of FW, which is a voluntary activity; in contrast, walking with the gait trainer may produce an automatic activity, probably by activating the central pattern generator, as reported previously in nonprimate mammals.42 Other factors that may explain the shorter walking time during FW include decreased motor control, decreased range of motion, sensory impairments that interfered with floor walking, fear of falling, lack of confidence in the ability to walk, and lack of motivation.

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Conclusions 

The gait trainer increased walking time duration in hemiplegic patients and reduced the oxygen cost of walking, which remained, however, far greater than the oxygen cost of sitting. Further studies are warranted to compare GT and conventional therapy in patients at the subacute phase of stroke recovery.

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Suppliers 

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References 

  1. Wade DT , Wood VA , Heller A , Maggs J , Langton Hewer R . Walking after stroke. Measurement and recovery over the first 3 months . Scand J Rehabil Med . 1987;19:25–30
  2. da Cunha IT , Lim PA , Qureshy H , Henson H , Monga T , Protas EJ . Gait outcomes after acute stroke rehabilitation with supported treadmill ambulation training (a randomized controlled pilot study) . Arch Phys Med Rehabil . 2002;83:1258–1265
  3. Hesse S , Konrad M , Uhlenbrock D . Treadmill walking with partial body weight support versus floor walking in hemiparetic subjects . Arch Phys Med Rehabil . 1999;80:421–427
  4. Ada L , Dean CM , Hall JM , Bampton J , Crompton S . A treadmill and overground walking program improves walking in persons residing in the community after stroke (a placebo-controlled, randomized trial) . Arch Phys Med Rehabil . 2003;84:1486–1491
  5. Lamontagne A , Fung J . Faster is better (implications for speed-intensive gait training after stroke) . Stroke . 2004;35:2543–2548
  6. Brinkmann JR , Hoskins TA . Physical conditioning and altered self-concept in rehabilitated hemiplegic patients . Phys Ther . 1979;59:859–865
  7. Finch L , Barbeau H . Hemiplegic gait (new treatment strategies) . Physiother Can . 1986;38:36–41
  8. Barbeau H , Visintin M . Optimal outcomes obtained with body-weight support combined with treadmill training in stroke subjects . Arch Phys Med Rehabil . 2003;84:1458–1465
  9. Hesse S , Uhlenbrock D , Sarkodie-Gyan T . Gait pattern of severely disabled hemiparetic subjects on a new controlled gait trainer as compared to assisted treadmill walking with partial body weight support . Clin Rehabil . 1999;13:401–410
  10. Colombo G , Joerg M , Schreier R , Dietz V . Treadmill training of paraplegic patients using a robotic orthosis . J Rehabil Res Dev . 2000;37:693–700
  11. Dietz V , Muller R , Colombo G . Locomotor activity in spinal man (significance of afferent input from joint and load receptors) . Brain . 2002;125:2626–2634
  12. Dietz V , Colombo G , Jensen L . Locomotor activity in spinal man . Lancet . 1994;344:1260–1263
  13. Rossier P , Wade DT . Validity and reliability comparison of 4 mobility measures in patients presenting with neurologic impairment . Arch Phys Med Rehabil . 2001;82:9–13
  14. Collen FM , Wade DT , Bradshaw CM . Mobility after stroke (reliability of measures of impairment and disability) . Int Disabil Stud . 1990;12:6–9
  15. Hesse S , Sarkodie-Gyan T , Uhlenbrock D . Development of an advanced mechanised gait trainer, controlling movement of the centre of mass, for restoring gait in non-ambulant subjects . Biomed Tech (Berl) . 1999;44:194–201
  16. Beaver WL , Wasserman K , Whipp BJ . On-line computer analysis and breath-by-breath graphical display of exercise function tests . J Appl Physiol . 1973;34:128–132
  17. Teixeira da Cunha-Filho I , Henson H , Qureshy H , Williams AL , Holmes SA , Protas EJ . Differential responses to measures of gait performance among healthy and neurologically impaired individuals . Arch Phys Med Rehabil . 2003;84:1774–1779
  18. Fletcher GF , Balady GJ , Amsterdam EA , et al.   Exercise standards for testing and training (a statement for healthcare professionals from the American Heart Association) . Circulation . 2001;104:1694–1740
  19. Brown DA , Kautz SA . Increased workload enhances force output during pedaling exercise in persons with poststroke hemiplegia . Stroke . 1998;29:598–606
  20. Chaudhuri A , Behan PO . Fatigue in neurological disorders . Lancet . 2004;363:978–988
  21. Brandstater ME , de Bruin H , Gowland C , Clark BM . Hemiplegic gait (analysis of temporal variables) . Arch Phys Med Rehabil . 1983;64:583–587
  22. MacKay-Lyons M , Makrides L , Speth S . Effect of 15% body weight support on exercise capacity of adults without impairments . Phys Ther . 2001;81:1790–1800
  23. Christman SK , Fish AF , Bernhard L , Frid DJ , Smith BA , Mitchell L . Continuous handrail support, oxygen uptake, and heart rate in women during submaximal step treadmill exercise . Res Nurs Health . 2000;23:35–42
  24. Knutsson E , Richards C . Different types of disturbed motor control in gait of hemiparetic patients . Brain . 1979;102:405–430
  25. Olney SJ , Colborne GR , Martin CS . Joint angle feedback and biomechanical gait analysis in stroke patients (a case report) . Phys Ther . 1989;69:863–870
  26. Ng SS , Hui-Chan CW . The timed up & go test (its reliability and association with lower-limb impairments and locomotor capacities in people with chronic stroke) . Arch Phys Med Rehabil . 2005;86:1641–1647
  27. Ward ME , Corbeil C , Gibbons W , Newman S , Macklem PT . Optimization of respiratory muscle relaxation during mechanical ventilation . Anesthesiology . 1988;69:29–35
  28. Kaufman MP , Longhurst JC , Rybicki KJ , Wallach JH , Mitchell JH . Effects of static muscular contraction on impulse activity of groups III and IV afferents in cats . J Appl Physiol . 1983;55:105–112
  29. Ishida K , Takaishi T , Miyamura M . Ventilatory responses at the onset of passive movement and voluntary exercise with arms and legs . Acta Physiol Scand . 1994;151:343–352
  30. Bell HJ , Duffin J . CO2 does not affect passive exercise ventilatory decline . J Appl Physiol . 2003;95:322–329
  31. Bell HJ , Ramsaroop DM , Duffin J . The respiratory effects of two modes of passive exercise . Eur J Appl Physiol . 2003;88:544–552
  32. Soucie LP , Carey C , Woodend AK , Tang AS . Correlation of the heart rate-minute ventilation relationship with clinical data (relevance to rate-adaptive pacing) . Pacing Clin Electrophysiol . 1997;20:1913–1918
  33. Delistraty DA , Greene WA , Carlberg KA , Raver KK . Use of graded exercise to evaluate physiological hyperreactivity to mental stress . Med Sci Sports Exerc . 1991;23:476–481
  34. Teixeira-Salmela LF , Nadeau S , McBride I , Olney SJ . Effects of muscle strengthening and physical conditioning training on temporal, kinematic and kinetic variables during gait in chronic stroke survivors . J Rehabil Med . 2001;33:53–60
  35. Hash D . Energetics of wheelchair propulsion and walking in stroke patients . Orthop Clin North Am . 1978;9:372–374
  36. Gordon NF , Gulanick M , Costa F , et al.   Physical activity and exercise recommendations for stroke survivorsan American Heart Association scientific statement from the Council on Clinical Cardiology, Subcommittee on Exercise, Cardiac Rehabilitation, and Prevention; the Council on Cardiovascular Nursing; the Council on Nutrition, Physical Activity, and Metabolism; and the Stroke Council . Circulation . 2004;109:2031–2041
  37. Babcock MA , Paterson DH , Cunningham DA , Dickinson JR . Exercise on-transient gas exchange kinetics are slowed as a function of age . Med Sci Sports Exerc . 1994;26:440–446
  38. Bell C , Paterson DH , Kowalchuk JM , Cunningham DA . Oxygen uptake kinetics of older humans are slowed with age but are unaffected by hyperoxia . Exp Physiol . 1999;84:747–759
  39. Johnson PJ , Winter EM , Paterson DH , Koval JJ , Nevill AM , Cunningham DA . Modelling the influence of age, body size and sex on maximum oxygen uptake in older humans . Exp Physiol . 2000;85:219–225
  40. Perry J . The mechanics of walking in hemiplegia . Clin Orthop Relat Res . 1969;Mar-Apr(63):23–31
  41. Macko RF , Katzel LI , Yataco A , et al.   Low-velocity graded treadmill stress testing in hemiparetic stroke patients . Stroke . 1997;28:988–992
  42. Barbeau H , Rossignol S . Recovery of locomotion after chronic spinalization in the adult cat . Brain Res . 1987;412:84–95
  • a Hocoma AG, Industriestr 4b, CH-8604 Volketswil, Switzerland.
  • b Gait Trainer; Reha-Stim, Kastanienalle 32, 14050 Berlin, Germany.
  • c Vmax Horizon System; Sensormedics Inc, 22705 Savi Ranch Pkwy, Yorba Linda, CA 92887.

 Supported by the Garches Foundation.No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit upon the authors or upon any organization with which the authors are associated.

PII: S0003-9993(05)01496-6

doi:10.1016/j.apmr.2005.11.034

Archives of Physical Medicine and Rehabilitation
Volume 87, Issue 4 , Pages 482-489, April 2006

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