Next Article in Journal
Study Protocol for the Evaluation of Multidisciplinary Medication Reconciliation Service in Adult Patients Undergoing Thoracic and Cardiovascular Surgery (The MERITS Study): A Single-Center Controlled before-and-after Study
Previous Article in Journal
Use of Digital Healthcare Communication to Improve Urologists’ Surveillance of Lithiasis Patients Treated with Internal Urinary Drainage Pre- and Post-COVID-19 Period
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Healthcare
Volume 11
Issue 12
10.3390/healthcare11121777
healthcare-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Effects of Curved-Path Gait Training on Gait Ability in Middle-Aged Patients with Stroke: Protocol for a Randomized Controlled Trial

by
Youngmi Jin
1,†,
Yubin Lee
2,†,
Seiyoun Park
3,
Sangbin Lee
4,*,‡ and
Chaegil Lim
5,*,‡
1
Department of Special Education of Graduate School, Dankook University, Yongin 16890, Republic of Korea
2
Department of Health Science, Gachon University Graduate School, Incheon 21936, Republic of Korea
3
Department of Physical Therapy, Wonkwang Health Science University, Iksan 54538, Republic of Korea
4
Department of Physical Therapy, Namseoul University, Cheonan 31020, Republic of Korea
5
Department of Physical Therapy, Gachon University, Incheon 21936, Republic of Korea
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work as first author.
‡
These authors contributed equally to this work as corresponding authors.
Healthcare 2023, 11(12), 1777; https://doi.org/10.3390/healthcare11121777
Submission received: 12 April 2023 / Revised: 22 May 2023 / Accepted: 15 June 2023 / Published: 16 June 2023
Browse Figures
Review Reports Versions Notes

Abstract

:
(1) Introduction: This study aimed to investigate the effects of curved-path stride gait training on the gait ability of patients with stroke. (2) Materials and Methods: Thirty patients with stroke were randomly assigned to curved-path stride gait training (n = 15) and general gait training groups (n = 15). Both groups underwent training for 30 min five times a week for 8 weeks. The gait ability of each was assessed using the Dynamic Gait Index (DGI), Timed-Up-and-Go (TUG) test, 10-meter walk test, and Figure-of-8 walk test (F8WT). (3) Results: The curved-path gait training group showed significant differences in the DGI, TUG test, 10-m walk test, and F8WT pre- versus post- intervention (p < 0.05). The general gait training group showed no significant difference in F8WT pre- versus post-intervention (p > 0.05). Additionally, there was a statistically significant intergroup difference in gait ability (p < 0.05). (4) Conclusions: Curved-path gait training resulted in greater improvement in gait ability than general gait training. Therefore, curved-path gait training can be a meaningful intervention for improving the gait ability of patients with stroke.

1. Introduction

Gait, an interaction between the body and central nervous system, is a complex technique involving intentional movements that quickly adapt to changing circumstances [1,2,3]. Gait has various forms, including straight- and curved-path strides. In a straight gait, body movements occur symmetrically, with the weight load and weight shifting balanced between the feet [4]. However, a curved-path gait requires kinetic asymmetry. A curved-path gait is accomplished by increasing the mediolateral ground reaction forces throughout the stance phase to propel the body in the desired direction. The lateral impulse is greater on the outside limb and lesser on the inside limb during a curved versus straight gait [5,6]. In addition, during curved-path walking, the mediolateral displacement of the body mass shifts inward toward the inner leg [7].
Patients with stroke show gait disorders resulting from damage to the motor and sensory pathways [8,9]. These patients show lower-limb asymmetry due to a lack of appropriate muscle contraction, which impedes their ability to assume a normal gait [10]. Patients with stroke fail to bear sufficient weight on the affected inner leg and adopt a reduced speed while walking along a curved path toward the affected side [11]. Thus, the kinematics and muscular components engaged during a curved-path gait toward the affected direction should be considered to improve its performance [12].
Common gait training attempts to achieve a normal range of motion in the joints and inhibit abnormal movements. In patients with stroke, gait training involves teaching weight loading and using sensory stimuli to move the load to the affected lower extremities [13]. Several studies have examined curved-path gait training. Kim et al. (2012) [14] found that eight-way curved-path gait training has a significant effect on balance and ambulation in patients with stroke. Additionally, Richard (2010) [15] reported that patients with stroke who undergo training that changes the center of gravity and rotates the pelvis show improved curved-path gait performance through improved adaptability of motor control on the affected side, which improves their ability to provide eccentric sensory information to the feet, move weight to the lower extremities, and support the body when walking along a curved path.
Moreover, to successfully assume a curved gait, the head and eyes must first move along the curved path [4,7]. In other words, the concentric sensory input of the neck and vestibular system, including the eye, provides information about movement and position, resulting in a normal rotational gait.
However, patients with stroke have limited information about their body position owing to poor joint stability and proprioceptive senses on the affected side, which reduces efficacy and efficiency during movement and reduces stride and gait speed during walking [16]. These patients also avoid weight loading and visually check the position of their feet on the affected side, thereby relying more on visual information [17]. Lamontagne et al. (2007) [18] suggested that to enhance the proprioceptive sensibility of patients with stroke, a shift in gaze and head position in the direction of the curve’s center should be performed, while ground reaction force, vestibular sense, and proprioceptive sense input to the affected foot are necessary. Gdowski et al. (2000) [19] reported that rotating the body along a curve activates sensory inputs to the neck and vestibular organs, stimulates the vestibular nucleus of the brainstem, and can contribute to leg muscle activation.
As shown above, a curved-path gait enhances the proprioception of patients with stroke, giving them a more efficient gait ability. Regarding the effect of curved-path walking, Kim et al. (2012) [14] reported a significant increase in static and dynamic balance in patients with stroke after 4 weeks of figure 8 versus straight-path walking. It is difficult to attribute this effect solely to the curved-path gait training because the figure 8 walking also included straight sections. Previous studies focused on directional change-related research but did not address the effects of complete rotational gait training. Therefore, this study aimed to compare the efficacy of complete curved-path gait training (without any straight sections) and general gait training at improving gait ability in middle-aged stroke patients with hemiplegia after an 8-week intervention. We also aimed to provide basic clinical data for the development of rotational walking training programs for patients with central nervous system lesions (e.g., stroke).

2. Materials and Methods

2.1. Participants

The study participants were recruited from the Gyeonggi K Hospital. A total of 34 middle-aged patients who were diagnosed with hemiplegia caused by middle cerebral artery stroke more than 6 months prior and agreed to participate in the study were included. Informed consent was obtained from all participants. The training period was 8 weeks long. The inclusion criteria were as follows: first stroke, ability to walk at least 6 m independently without assistance [20], Mini-Mental State Examination—Korean version score ≥24, willingness to participate in the study [14], no vision deficits or vestibular system abnormalities, and no orthopedic disease in the body or lower limbs [21]. The study was conducted in accordance with the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board of the Gachon University (1044396-202103-HR-063-01) and Clinical Research Information Service (CRIS) (no. KCT0008171).

2.2. Procedures and Intervention

Of the 34 participants, 1 did not meet the inclusion criteria, and 3 were excluded for personal reasons; thus, a total of 30 participants were included in the study. To minimize bias, the 30 included patients were randomly assigned to the curved-path stride gait training (n = 15) and general gait training groups (n = 15). Both groups received gait training for 30 min five times a week for 8 weeks (Figure 1). The randomization was performed by a nonparticipating researcher using Microsoft Excel for Windows (Microsoft Corporation, Redmond, WA, USA), and each patient was randomly assigned a number between 1 and 30. Participants with even numbers were assigned to the curved-path stride gait training group, whereas those with odd numbers were assigned to the general gait training group. The assignment was recorded in a password-protected document by the researcher who performed the randomization. The participants were blinded to information regarding the group to which they did not belong, types and differences in the intervention programs, and variables being compared between the groups. All data were collected before and at the end of the 8-week intervention period by the same physical therapist who did not participate in the study. All walking times during each measurement were measured using a stopwatch, and all length measurements were performed using a ruler. The exercise programs were conducted under the supervision of a therapist. To prevent falls, safety protective equipment, such as corner protection and mattresses, were placed nearby. If the participants experienced dizziness during any exercise phase, they rested on a chair with a backrest for at least 1 min.

2.2.1. Curved-Path Gait Training Program

The curved-path gait training program was created by adjusting the stride in the shape of a ladder on a circular gait path [22,23]. The circle path consisted of three circles: large (total length: 12.6 m; radius: 2 m; curvature: 0.5 m), medium (total length: 6.3 m; radius: 1 m; curvature: 1 m), and small (total length: 3.1 m; radius: 0.5 m; curvature: 2 m) (Figure 2). The outer curves of all circles are marked with dotted lines. A solid line was used to mark the inner curve, which was 60 cm away from the outer curve [22,23]. A ladder was marked between the two curves at the participants’ average stride (31 cm). A 1.7 cm wide black tape was used for all markings (Figure 2). The curved-path training program consisted of the following steps. First, the patients moved along the curved path to the right, sat in a chair, rested for 1 min, and then followed the path again to the left. As the curvature increased in the order of the large, medium, and small circles, the task became more challenging for the smaller circles. If a participant was unable to perform the task in a large circle (e.g., lost balance, needed continuous assistance, or had a slow walking speed), we did not proceed with the middle circle intervention. The same rule was applied to the middle and small circles.
The starting position of the training was first directed at the curve marked with white tape in the direction of the eyes and head. The participants were then asked to walk as close to the white tape as possible using one foot at a time. The participants then placed their feet on a black ladder. Before the participants stepped on the left foot, they placed their right foot next to the left foot to support the weight. In the first stage, the patients could use their gaze and head position to reorient themselves when they rotated along a curved path [7,24,25]. The curved-path training program consisted of a warm-up (5 min), main exercise (20 min), and cool-down (5 min) performed for 30 min five times a week for 8 weeks.

2.2.2. General Gait Training Program

The general gait training program was a 45 m round trip training program performed for 30 min five times a week for 8 weeks. The gait training program consisted of a warm-up (5 min), main exercise (20 min), and cool-down (5 min). During this program, participants maintained a forward gaze, focusing on the front. If the participant adapted to the program without losing their balance and showed improved walking speed compared to the initial speed, the walking speed was gradually increased, and the assistance was reduced.

2.3. Outcome Measurements

2.3.1. Ten-Meter Walk Test

The 10-meter walk test, which is commonly used to assess the gait ability of patients with neurological impairments [26,27,28], involves measuring the time required for a patient to walk 10 m in a straight line, excluding the acceleration and deceleration sections of 2 m each at the start and end. After a 10 m walkway was created between the two points, the walking time was measured [29]. It was conducted at the self-selected walking speed, and a total of 3 trials were made to obtain the average value, which was used as data [27,28]. The interrater reliability of this test is 0.87 [30]. For this study, it was measured three times, and the mean value was used for the analysis.

2.3.2. Dynamic Gait Index

The Dynamic Gait Index (DGI) is a tool that was developed to assess an individual’s stability and risk of falling during walking [26,31,32,33]. The DGI consists of eight categories: marching on a flat surface, changing gait speed, gait with horizontal movements (rotation) of the head, gait with vertical movements (rotation) of the head, marching and turning on one’s own body axis (pivot), marching over an obstacle, bypassing obstacles, and marching up and down stairs [34]. Each item is scored on a 4-point scale of 0–3, with 0 representing the lowest level of function, and 3 representing the highest for a total possible score of 24 points [35]. A score ≥22 indicates that the patient can move safely, while a score ≤19 indicates a risk of falling. The test–retest reliability of the DGI was 0.96, while the interrater reliability was 0.96 [31].

2.3.3. Figure-of-8 Walk Test

The Figure-of-8 walk test (F8WT) was used to assess curved walking ability [36,37,38,39]. In this test, the participants walked clockwise and counterclockwise around two cones. The measurable parameters for this test were time, number of steps, accuracy, and natural movement. The test begins with the patient walking between the two cones and stops when the patient returns to their starting position. We performed this test thrice, obtained average values, and used only the time and number of steps obtained in the analysis. Accuracy was indicated by a “yes” if the patient did not deviate from the cones and “no” if the patient deviated away from them. The natural movement item has a total score of 3 points, the subitems of which are given 0 points for difficulties related to pauses, hesitations, and changes in speed and 1 point if no difficulty is noted. The test–retest, intrarater, and interrater reliabilities were 0.98 each [38].

2.3.4. Timed-Up-and-Go Test

The Timed-Up-and-Go (TUG) test is used to assess the mobility, balance, and motor ability of stroke patients [40,41]. In the TUG test, the time required for the participant to turn around a point 3 m away from the chair and return to his/her location was measured three times to obtain an average value. A time of <10 s indicated independent walking, <20 s indicated that some assistance is required, and >30 s indicated that considerable assistance is required for walking. The intrarater and interrater reliabilities of the TUG test were 0.99, 0.98, and 0.98, respectively [42].

2.4. Sample Size Estimation

This study used a single-blind randomized controlled trial design. G power 3.1.9.2 software (Heinrich Heine University Düsseldorf, Düsseldorf, Germany) [43] was used to determine the sample size [44]. An effect size of d = 1.34 was used to calculate the sample size based on the result of the F8WT (time and steps) in a prior pilot test [45]. Twenty-six participants were required to detect statistical significance when a clinically significant difference was observed between two independent means, with an effect size of d = 1.34, significance level of 0.05, and power of 0.90 [43]. An additional 30% quantity of patients was recruited to account for unanticipated dropouts.

2.5. Statistical Analysis

The statistical analysis was performed using the Statistical Package for the Social Sciences software (version 23.0; IBM, Armonk, NY, USA). All measured values are presented as mean and standard deviation. The Levene’s homogeneity of variance test was conducted to test the general characteristics and homogeneity of the participants before the experiment. A paired t-test was performed to analyze the differences between the dependent variables according to the measurement period (before and after the experiment), while an independent t-test was used to compare the effects of gait training on gait ability between the two groups.
The effect size was calculated to explain the arbitration effect more objectively. The significance level was set at p < 0.05.

3. Results

The DGI, TUG test, 10-meter walk test, and F8WT were used to measure participant gait ability. No significant intergroup differences were found (p > 0.05) in general characteristics (Table 1).
The dynamic gait ability results with curved-path versus general gait training in patients with stroke are shown in Table 2 and Table 3. The curved-path gait training group showed significant differences in all variables pre- versus post-training after 8 weeks, whereas the general gait training group showed no significant differences in the F8WT (speed and steps) (Table 2). The intergroup differences based on the differences in pre- and post-intervention after 8 weeks showed significant results for all variables (Table 3). The effect size was greater than 0.5 (Cohen’s d = 0.5) for DGI, F8WT speed, and F8WT steps.

4. Discussion

This study aimed to determine the effect of a curved-path gait training program on walking in patients with stroke. Significant improvements were observed in both curved-path gait training and general gait training pre- and post-intervention after the 8-week intervention; however, the curved-path gait training showed a significant improvement in gait ability compared to the general gait training group. Both training methods improved weight load, weight shifting, and speed changes on the affected side. It is important to note the significantly greater increase in walking speed observed after the intervention, particularly in the curved-path gait training group. This improvement in walking speed indicates enhanced muscle activation on the affected side, improved weight shifting and bearing, increased stance time on the affected side, and ultimately results in a more balanced walking pattern compared to general gait training. Eng et al. (2008) [46] also reported that curved-path gait training, in which eye and head movements occur first when walking, stimulates the affected side and shifts the body’s center of gravity, which can result in segmentation movements. Kwon et al. (2013) [47] reported that walking through gaze-oriented movements effectively improves gait ability. Based on these findings, patients with stroke require curved-path gait training, which includes changes in direction, as the body center is biased toward the unaffected side, the affected side is neglected, balance becomes difficult, and walking control decreases.
On the TUG test, the curved-path gait training group showed statistically significant improvements compared with the general gait training group. Consistent with the results of this study, Kim et al. (2012) [14] noted that curved-path gait training groups showed significant improvements in dynamic balance compared with general straight gait training groups. These results suggest that the concentric sensory information of the foot is improved by increasing the weight-shifting ability and weight load on both legs through curved-path gait training in patients with stroke.
The 10-meter walk test results for both groups showed statistically significant improvements in gait speed after training. The curved-path gait training group showed statistically significant improvements compared to the general walking training group. In a similar study, Lee et al. (2003) [13] reported that the greater the weight support on the affected foot, the faster the walking speed; specifically, if the affected foot was close to the curve in a curved-path gait, the weight support increased and the walking speed was improved. Therefore, the results of this study showed that curved-path gait training was more effective than general straight walking training in terms of weight support training on the affected side.
On the F8WT, the curved-path gait training group demonstrated improved gait speed and stride compared with the general gait training group. Similar to the results of this study, Kim et al. (2012) [14] reported that stroke patients who performed curved walking training in both directions on a figure-8-shaped track showed improved weight support and weight shifting in both legs. Ko et al. (2015) [48] also reported that exercise programs that improve proprioception on the affected side effectively improved gait ability and speed in stroke patients. Gdowski et al. (2000) [19] also noted that a rotating gait in a curved direction contributes to selective leg muscle activation by proprioceptive stimulation of the neck and vestibular nucleus of the brain. Therefore, walking along a curved path is believed to increase proprioceptive stimulation by changing gaze and head direction during walking, resulting in improved gait ability.
Chen et al. (2014) [12] reported that stroke patients require more time for turning compared to healthy individuals. This slow turning leads to poor balance ability and temporal gait asymmetry. The study also found that knee extensor muscle activation is dependent on speed and stroke patients had lower activation of the knee extensor muscles on the affected side compared to healthy individuals, regardless of the turning direction. This is related to the slower turning speed in patients with stroke. Bland et al. (2019) [49] stated that greater spatial variability and smaller temporal variability are associated with improved curved-path gait ability. Specifically, they highlighted the relationship between spatial variability and both step length and step width. Lee JH (2022) [50] investigated the spatiotemporal characteristics of the curvilinear gait compared to the rectilinear gait in hemiplegic stroke patients using surface electromyography. From a spatial motor module perspective, it was indicated that during the curvilinear gait, the weighting of knee extensor muscles decreased in the early stance phase of the gait cycle, suggesting difficulty in weight acceptance. In the early swing phase, a pattern of simultaneous activation of hip flexor muscles and knee extensor muscles was reported. In summary, during the curvilinear gait, this implies incomplete weight support on the affected side and an increase in swing time. Next, from a temporal motor module perspective, it was observed that during the curvilinear gait, the activation peak timing in the terminal stance phase was delayed, which was associated with slower gait speed.
Our study showed that the curved-path gait training improved overall gait ability compared to general gait training. The decreased number of steps observed in the F8WT after curve-path gait training may be related to an increase in step length and a decrease in step width. These changes in step length and width resulted in improved gait speed compared to the general gait training. The increased gait speed indicates an improvement in the activation of knee extensor muscles on the affected side, ultimately resulting in a longer stance time on the affected side and an increased swing phase time on the unaffected side. The prolonged swing time helps to compensate for the difference in stride length between both legs, leading to a more symmetrical movement between both sides. In other words, it is considered positive that the curved-path walking training has resulted in an increase in walking speed compared to general walking training, as it creates more symmetrical movements through spatial and temporal changes such as increased weight acceptance on the affected side, increased step length and swing time, and decreased step width.
This study had some limitations. First, it included only participants with chronic middle cerebral artery stroke. It would be necessary to verify the effectiveness of various stroke cases as well, as the remaining function and prognosis of patients may differ depending on the damaged blood vessels (e.g., anterior cerebral artery and posterior cerebral artery). Second, one-sided focus training on the affected side was not performed during gait training. Third, we failed to measure the relationship between vestibular sense and proprioception or between muscle activity and improved walking ability. Fourth, we compared only curved-path gait training and general gait groups; no control group was included. Although there may be ethical issues with including a group of patients with stroke who receive no intervention, it could serve as an important control group. Fifth, the study did not consider upper limb movements, such as the trunk and shoulder, in relation to the gait ability of patients with stroke.

5. Conclusions

This study investigated the effects of curved-path gait training on gait ability in stroke patients with hemiplegia. Curved-path gait training resulted in significantly improved gait ability compared with general gait training. This improvement ultimately results in a more balanced walking pattern compared to general gait training. These results suggest that curved-path gait training can be a meaningful intervention for improving the asymmetrical gait ability of stroke patients with hemiplegia. However, the neurological effects of this type of training have not been clearly defined. Further research is needed to investigate the effects of curved-path gait training on other neurological patients with gait impairment and other related neurological conditions.

Author Contributions

Conceptualization, Y.J. and C.L.; methodology, Y.J.; software, S.P., S.L. and C.L.; validation, Y.L. and C.L.; formal analysis, Y.J., Y.L., S.L. and C.L.; investigation, Y.J. and S.P.; resources, Y.J., S.P., S.L. and C.L.; data curation, Y.J. and Y.L.; writing—original draft preparation, Y.J., Y.L., S.L. and C.L.; writing—review and editing, Y.J., Y.L., S.L. and C.L.; visualization, Y.J., Y.L. and C.L.; supervision, S.L. and C.L.; project administration, S.L. and C.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board of the Gachon University (1044396-202103-HR-063-01) and CRIS system (number KCT0008171).

Informed Consent Statement

Informed consent was obtained from all study participants.

Data Availability Statement

The data used in this study are available upon request from the corresponding author. The data are not publicly available due to privacy or ethical considerations.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Capaday, C. The special nature of human walking and its neural control. Trends Neurosci. 2002, 25, 370–376. [Google Scholar] [CrossRef] [PubMed]
  2. Osoba, M.Y.; Rao, A.K.; Agrawal, S.K.; Lalwani, A.K. Balance and gait in the elderly: A contemporary review. Laryngoscope Investig. Otolaryngol. 2019, 4, 143–153. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. Pirker, W.; Katzenschlager, R. Gait disorders in adults and the elderly: A clinical guide. Wien. Klin. Wochenschr. 2017, 129, 81–95. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Duval, K.; Luttin, K.; Lam, T. Neuromuscular strategies in the paretic leg during curved walking in individuals post-stroke. J. Neurophysiol. 2011, 106, 280–290. [Google Scholar] [CrossRef] [PubMed]
  5. Orendurff, M.S.; Segal, A.D.; Berge, J.S.; Flick, K.C.; Spanier, D.; Klute, G.K. The kinematics and kinetics of turning: Limb asymmetries associated with walking a circular path. Gait Posture 2006, 23, 106–111. [Google Scholar] [CrossRef] [PubMed]
  6. Cheng, F.-Y.; Yang, Y.-R.; Wu, Y.-R.; Cheng, S.-J.; Wang, R.-Y. Effects of curved-walking training on curved-walking performance and freezing of gait in individuals with Parkinson’s disease: A randomized controlled trial. Park. Relat. Disord. 2017, 43, 20–26. [Google Scholar] [CrossRef] [PubMed]
  7. Courtine, G.; Schieppati, M. Human walking along a curved path. II. Gait features and EMG patterns. Eur. J. Neurosci. 2003, 18, 191–205. [Google Scholar] [CrossRef]
  8. Jung, T.; Lee, D.; Charalambous, C.; Vrongistinos, K. The influence of applying additional weight to the affected leg on gait patterns during aquatic treadmill walking in people poststroke. Arch. Phys. Med. Rehabil. 2010, 91, 129–136. [Google Scholar] [CrossRef]
  9. O’Sullivan, S.B.; Schmitz, T.J. Improving Functional Outcomes in Physical Rehabilitation; F.A. Davis: Philadelphia, PA, USA, 2016. [Google Scholar]
  10. Von Schroeder, H.P.; Coutts, R.D.; Lyden, P.D.; Billings, E.; Nickel, V.L. Gait parameters following stroke: A practical assessment. J. Rehabil. Res. Dev. 1995, 32, 25–31. [Google Scholar]
  11. Lam, T.; Luttmann, K. Turning capacity in ambulatory individuals poststroke. Am. J. Phys. Med. Rehabil. 2009, 88, 873–883. [Google Scholar] [CrossRef]
  12. Chen, I.-H.; Yang, Y.-R.; Cheng, S.-J.; Chan, R.-C.; Wang, R.-Y. Neuromuscular and biomechanical strategies of turning in ambulatory individuals post-stroke. Chin. J. Physiol. 2014, 57, 128–136. [Google Scholar] [CrossRef] [PubMed]
  13. Lee, K.M.; Han, S.H.; Kim, Y.S. Effects of Asymmetrical Weight Bearing during Straight and Circular Walking in Hemiplegic Patients. J. Korean Acad. Rehabil. Med. 2003, 27, 173–177. [Google Scholar]
  14. Kim, M.-G.; Kim, J.-H.; Park, J.-W. The effect of turning training on figure of 8 tract on stoke patients’ balance and walking. J. Korean Phys. Ther. 2012, 24, 143–150. [Google Scholar]
  15. Snell, R.S. Clinical Neuroanatomy; Lippincott Williams & Wilkins: Philadelphia, PA, USA, 2010. [Google Scholar]
  16. Sekir, U.; Yildiz, Y.; Hazneci, B.; Ors, F.; Saka, T.; Aydin, T. Reliability of a functional test battery evaluating functionality, proprioception, and strength in recreational athletes with functional ankle instability. Eur. J. Phys. Rehabil. Med. 2008, 44, 407–415. [Google Scholar] [PubMed]
  17. Kim, T.-W.; Cha, Y.-J. Effects of a Real-time Plantar Pressure Feedback during Gait Training on the Weight Distribution of the Paralyzed Side and Gait Function in Stroke Patients. Korean Soc. Phys. Med. 2022, 17, 53–62. [Google Scholar] [CrossRef]
  18. Lamontagne, A.; Paquette, C.; Fung, J. Stroke Affects the Coordination of Gaze and Posture During Preplanned Turns While Walking. Neurorehabilit. Neural Repair 2007, 21, 62–67. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  19. Gdowski, G.T.; Boyle, R.; McCrea, R.A. Sensory processing in the vestibular nuclei during active head movements. Arch. Ital. Biol. 2000, 138, 15–28. [Google Scholar]
  20. Byrne, C.A.; O’Keeffe, D.T.; Donnelly, A.E.; Lyons, G.M. Effect of walking speed changes on tibialis anterior EMG during healthy gait for FES envelope design in drop foot correction. J. Electromyogr. Kinesiol. 2007, 17, 605–616. [Google Scholar] [CrossRef]
  21. Patil, P.; Rao, S. Effects of Thera-Band® elastic resistance-assisted gait training in stroke patients: A pilot study. Eur. J. Phys. Rehabil. Med. 2011, 47, 427–433. [Google Scholar]
  22. Jin, Y.; Song, B. The effects of curved path stride gait training on the lower extremity muscle activity and gait ability of patients with stroke. Korean J. Phys. Mult. Health Disabil. 2017, 60, 141–168. [Google Scholar]
  23. Jung, S.-Y.; Lee, H.-L.; Lee, S.-K. The Effect of Sensorimotor Training through Using the Ladder Exercise on Brain Function Related Hormones, Dynamic Balance in Male Undergraduate Students. Korean J. Sport 2021, 19, 567–576. [Google Scholar] [CrossRef]
  24. Grasso, R.; Glasauer, S.; Takei, Y.; Berthoz, A. The predictive brain: Anticipatory control of head direction for the steering of locomotion. Neuroreport 1996, 7, 1170–1174. [Google Scholar] [CrossRef]
  25. Hollands, M.A.; Marple-Horvat, D.E. Coordination of eye and leg movements during visually guided stepping. J. Mot. Behav. 2001, 33, 205–216. [Google Scholar] [CrossRef]
  26. Anne, S.-C.; Marjorie, H. Motor control: Theory and practical applications. Medicina 2010, 46, 382. [Google Scholar]
  27. Dalgas, U.; Severinsen, K.; Overgaard, K. Relations between 6 minute walking distance and 10 meter walking speed in patients with multiple sclerosis and stroke. Arch. Phys. Med. Rehabil. 2012, 93, 1167–1172. [Google Scholar] [CrossRef] [PubMed]
  28. Taylor, D.; Stretton, C.M.; Mudge, S.; Garrett, N. Does clinic-measured gait speed differ from gait speed measured in the community in people with stroke? Clin. Rehabil. 2006, 20, 438–444. [Google Scholar] [CrossRef]
  29. Suzuki, K.; Imada, G.; Iwaya, T.; Handa, T.; Kurogo, H. Determinants and predictors of the maximum walking speed during computer-assisted gait training in hemiparetic stroke patients. Arch. Phys. Med. Rehabil. 1999, 80, 179–182. [Google Scholar] [CrossRef]
  30. Green, J.; Forster, A.; Young, J. Reliability of gait speed measured by a timed walking test in patients one year after stroke. Clin. Rehabil. 2002, 16, 306–314. [Google Scholar] [CrossRef] [PubMed]
  31. Jonsdottir, J.; Cattaneo, D. Reliability and validity of the dynamic gait index in persons with chronic stroke. Arch. Phys. Med. Rehabil. 2007, 88, 1410–1415. [Google Scholar] [CrossRef] [PubMed]
  32. Shumway-Cook, A.; Woollacott, M.H. Motor Control—Theory and Practical Applications; Lippincott Williams & Wilkins: Philadelphia, PA, USA, 1995; pp. 89–90. [Google Scholar]
  33. Shumway-Cook, A.; Brauer, S.; Woollacott, M. Predicting the probability for falls in community-dwelling older adults using the Timed Up & Go Test. Phys. Ther. 2000, 80, 896–903. [Google Scholar]
  34. Whitney, S.; Wrisley, D.; Furman, J. Concurrent validity of the Berg Balance Scale and the Dynamic Gait Index in people with vestibular dysfunction. Physiother. Res. Int. 2003, 8, 178–186. [Google Scholar] [CrossRef]
  35. Marchetti, G.F.; Whitney, S.L.; Blatt, P.J.; Morris, L.O.; Vance, J.M. Temporal and spatial characteristics of gait during performance of the Dynamic Gait Index in people with and people without balance or vestibular disorders. Phys. Ther. 2008, 88, 640–651. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  36. Hess, R.J.; Brach, J.S.; Piva, S.R.; VanSwearingen, J.M. Walking skill can be assessed in older adults: Validity of the Figure-of-8 Walk Test. Phys. Ther. 2010, 90, 89–99. [Google Scholar] [CrossRef] [PubMed]
  37. Jan, M.-H.; Lin, C.-H.; Lin, Y.-F.; Lin, J.-J.; Lin, D.-H. Effects of weight-bearing versus nonweight-bearing exercise on function, walking speed, and position sense in participants with knee osteoarthritis: A randomized controlled trial. Arch. Phys. Med. Rehabil. 2009, 90, 897–904. [Google Scholar] [CrossRef] [PubMed]
  38. Kim, Y.-H.; Lim, J.-H. The reliability and validity of figure-of-8 walk test in patients with stroke. J. Korean Acad. Clin. Electrophysiol. 2012, 10, 29–37. [Google Scholar] [CrossRef] [Green Version]
  39. Wong, S.S.; Yam, M.-S.; Ng, S.S. The Figure-of-Eight Walk test: Reliability and associations with stroke-specific impairments. Disabil. Rehabil. 2013, 35, 1896–1902. [Google Scholar] [CrossRef]
  40. Faria, C.D.; Teixeira-Salmela, L.F.; Nadeau, S. Predicting levels of basic functional mobility, as assessed by the Timed “Up and Go” test, for individuals with stroke: Discriminant analyses. Disabil. Rehabil. 2013, 35, 146–152. [Google Scholar] [CrossRef]
  41. Hafsteinsdottir, T.B.; Rensink, M.; Schuurmans, M. Clinimetric properties of the Timed Up and Go Test for patients with stroke: A systematic review. Top. Stroke Rehabil. 2014, 21, 197–210. [Google Scholar] [CrossRef] [Green Version]
  42. Podsiadlo, D.; Richardson, S. The timed “Up & Go”: A test of basic functional mobility for frail elderly persons. J. Am. Geriatr. Soc. 1991, 39, 142–148. [Google Scholar]
  43. Faul, F.; Erdfelder, E.; Lang, A.-G.; Buchner, A. G* Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav. Res. Methods 2007, 39, 175–191. [Google Scholar] [CrossRef]
  44. Cohen, L.J. The Probable and the Provable; Oxford Academic: Oxford, UK, 1977. [Google Scholar]
  45. Park, H.-R.; Kim, J.-M.; Lee, M.-K.; Oh, D.-W. Clinical feasibility of action observation training for walking function of patients with post-stroke hemiparesis: A randomized controlled trial. Clin. Rehabil. 2014, 28, 794–803. [Google Scholar] [CrossRef] [PubMed]
  46. Eng, J.J.; Pang, M.Y.; Ashe, M.C. Balance, falls, and bone health: Role of exercise in reducing fracture risk after stroke. J. Rehabil. Res. Dev. 2008, 45, 297. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. Kwon, H.-R.; Shin, W.-S. The effects of visual direction control on balance and gait speed in patients with stroke. J. Korean Soc. Phys. Med. 2013, 8, 425–431. [Google Scholar] [CrossRef] [Green Version]
  48. Ko, K.-H.; Choi, J.-D.; Kim, M.-S. The Effects of Multi Joint-Joint Position Sense Training Using Functional Task on Joint Position Sense, Balance, Walking Ability in Patients with Post-Stroke Hemiplegia. Phys. Ther. Korea 2015, 22, 33–40. [Google Scholar] [CrossRef]
  49. Bland, K.; Lowry, K.; Krajek, A.; Woods, T.; VanSwearingen, J. Spatiotemporal variability underlying skill in curved-path walking. Gait Posture 2019, 67, 137–141. [Google Scholar] [CrossRef] [PubMed]
  50. LEE, J.-H. Spatial and Temporal Features of Motor Modules in an individual with Hemiparesis During the Curvilinear Gait: A Pilot Single-Case Study. J. Wellbeing Manag. Appl. Psychol. 2022, 5, 1–7. [Google Scholar]
Healthcare 11 01777 g001 550
Figure 1. Experimental procedures.
Figure 1. Experimental procedures.
Healthcare 11 01777 g001
Healthcare 11 01777 g002 550
Figure 2. Curved-path gait training program: ① large circle; ② medium circle; ③ small circle.
Figure 2. Curved-path gait training program: ① large circle; ② medium circle; ③ small circle.
Healthcare 11 01777 g002
Table
Table 1. General characteristics of the study participants and homogeneity test results (N = 30).
Table 1. General characteristics of the study participants and homogeneity test results (N = 30).
CategoryEG (n = 15)CG (n = 15)p
Sex (male/female)9/68/70.705 a
Age (years)54.38 ± 5.6354.07 ± 7.600.905 b
Height (cm)162.84 ± 8.66165.50 ± 9.170.448 b
Weight (kg)63.76 ± 10.0664.42 ± 9.500.862 b
Stroke type
(hemorrhagic/embolism)		6/95/80.716 a
Paretic side (right/left)7/87/81.000 a
Post-stroke duration (months)6.23 ± 0.726.00 ± 0.670.401 b
DGI (score)16.40 ± 2.0215.00 ± 3.540.104 b
TUG (s)19.37 ± 6.6019.51 ± 7.470.504 b
10 m walking (s)18.10 ± 6.4518.09 ± 8.510.242 b
F8WT speed (s)21.47 ± 7.3621.48 ± 9.020.311 b
F8WT steps (number)23.80 ± 7.2723.80 ± 9.190.260 b
Data are expressed as mean ± SD or n. CG, control group (general gait training); DGI, Dynamic Gait Index; EG, experimental group (curved-path gait training); F8WT, Figure-of-8 walk test; TUG, Timed-Up-and-Go test. a Obtained using the χ2 test. b Obtained using an independent t-test.
Table
Table 2. Gait ability of patients with stroke by group before and after the 8-week intervention (N = 30).
Table 2. Gait ability of patients with stroke by group before and after the 8-week intervention (N = 30).
EG (n = 15) CG (n = 15)
VariablePrePostp *EPrePostpE
DGI (score)16.400 ± 2.02822.733 ± 1.6240.0000.88615.000 ± 3.54515.800 ± 3.3420.001 *0.728
TUG (s)19.373 ± 6.60315.246 ± 5.5180.0000.71519.516 ± 7.47319.033 ± 7.3640.000 *0.492
10 m walk (s)18.106 ± 6.45715.428 ± 6.2270.0010.54718.097 ± 8.51217.581 ± 8.3060.001 *0.276
F8WT speed (s)21.473 ± 7.36716.976 ± 6.6560.0000.77021.484 ± 9.02521.600 ± 8.9410.3370.631
F8WT steps (number)23.800 ± 7.27218.400 ± 6.9360.0000.82023.800 ± 9.19024.133 ± 9.0300.0960.705
Data are expressed as mean ± standard deviation. CG, control group (general gait training); DGI, dynamic gait index; E, effect size; EG, experimental group (curved-path gait training); F8WT, Figure-of-8 walk test; TUG, Timed-Up-and-Go test. * p < 0.05.
Table
Table 3. Differences in gait ability of patients with stroke by group before and after the 8-week intervention.
Table 3. Differences in gait ability of patients with stroke by group before and after the 8-week intervention.
EG (n = 15)CG (n = 15)
VariableDifference
(Post–Pre)		Difference
(Post–Pre)		p *
DGI (score)6.333 ± 2.3500.800 ± 0.7740.001
TUG test (s)−4.127 ± 2.696−0.483 ± 0.2590.000
10 m walk test (s)−2.678 ± 2.521−0.516 ± 0.4590.003
F8WT speed (s)−4.496 ± 2.5040.115 ± 0.4490.000
F8WT steps (number)−5.400 ± 2.6130.333 ± 0.7230.000
Data are expressed as mean ± standard deviation or n (%). CG, control group (general gait training); DGI, Dynamic Gait Index; E, effect size; EG, experimental group (curved-path gait training); F8WT, Figure-of-8 walk test; TUG, Timed-Up-and-Go test. * p < 0.05.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Jin, Y.; Lee, Y.; Park, S.; Lee, S.; Lim, C. Effects of Curved-Path Gait Training on Gait Ability in Middle-Aged Patients with Stroke: Protocol for a Randomized Controlled Trial. Healthcare 2023, 11, 1777. https://doi.org/10.3390/healthcare11121777

AMA Style

Jin Y, Lee Y, Park S, Lee S, Lim C. Effects of Curved-Path Gait Training on Gait Ability in Middle-Aged Patients with Stroke: Protocol for a Randomized Controlled Trial. Healthcare. 2023; 11(12):1777. https://doi.org/10.3390/healthcare11121777

Chicago/Turabian Style

Jin, Youngmi, Yubin Lee, Seiyoun Park, Sangbin Lee, and Chaegil Lim. 2023. "Effects of Curved-Path Gait Training on Gait Ability in Middle-Aged Patients with Stroke: Protocol for a Randomized Controlled Trial" Healthcare 11, no. 12: 1777. https://doi.org/10.3390/healthcare11121777

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop