概要

Motor Dual-Tasks for Gait Analysis and Evaluation in Post-Stroke Patients

Published: March 11, 2021
doi:

概要

This paper presents a protocol specifically for dual motor task gait analysis in stroke patients with motor control deficits.

Abstract

Eighteen stroke patients were recruited for this study involving the evaluation of cognition and walking ability and multitask gait analysis. Multitask gait analysis consisted of a single walking task (Task 0), a simple motor dual-task (water-holding, Task 1), and a complex motor dual-task (crossing obstacles, Task 2). The task of crossing obstacles was considered to be equivalent to the combination of a simple walking task and a complex motor task as it involved more nervous system, skeletal movement, and cognitive resources. To eliminate heterogeneity in the results of the gait analysis of the stroke patients, the dual-task gait cost values were calculated for various kinematic parameters. The major differences were observed in the proximal joint angles, especially in the angles of the trunk, pelvis, and hip joints, which were significantly larger in the dual motor tasks than in the single walking task. This research protocol aims to provide a basis for the clinical diagnosis of gait function and an in-depth study of motor control in stroke patients with motor control deficits through the analyses of dual-motor walking tasks.

Introduction

The restoration of independent walking function is one of the requisites for the participation of post-stroke patients in community life1. The recovery of walking ability requires not only the interaction of the perception and cognitive systems, but also motor control2,3,4. Furthermore, in real community life, people require higher abilities such as performing two or more tasks at the same time (e.g., walking while holding objects or crossing obstacles). Therefore, studies have begun to focus on the interference of dual-tasks in gait performance5,6. Previous dual-task studies were mostly targeted to elderly and cognitively impaired patients owing to the difficulty in motor performance and heterogeneity in stroke patients; the gait function in stroke patients was mostly evaluated by a single walking task7,8,9. However, further research on dual-task gait analysis, especially motor dual-tasks related to motor control, is required.

This study introduces a methodology for dual motor task gait analysis and evaluation. This protocol not only includes clinical assessment of the walking ability in stroke patients, but also focuses on two dual-motor tasks: the holding-water-and-walking task (a simple dual motor task) and the crossing-obstacle walking task (a complex dual motor task). The aim of this study was to explore the effects of dual motor tasks on the gait of stroke patients and to employ the dual-task gait cost (DTC) values10 of dual-task parameters (the difference between a single task and dual-task) to exclude the heterogeneity among stroke patients. The design of the experimental tasks facilitated an in-depth discussion of the motor control function of stroke patients, which provided new ideas for the clinical diagnosis and evaluation of the gait function of stroke patients.

Protocol

NOTE: The clinical study was approved by the Medical Ethics Association of the Fifth Affiliated Hospital of Guangzhou Medical University (NO. KY01-2019-02-27) and has been registered at the China Clinical Trial Registration Center (No. ChiCTR1800017487 and entitled, "The multiple modal tasks on gait control and motor cognition after stroke").

1. Recruitment

  1. Recruit stroke patients with the following inclusion criteria: patients meeting the diagnostic criteria for cerebrovascular disease of the Neurological Branch of the Chinese Medical Association (2005); cerebral infarction confirmed by computed tomography or magnetic resonance imaging; damage to the unilateral cortex or with a subcortical lesion; ability to walk independently, Brunnstrom stage ≥ 4 stages; Modified Ashworth Scale11 ≤ 2 points; meeting the requirements of three-dimensional (3D) gait analysis and the ability to tolerate the whole process; and the ability to give informed consent.
  2. Ensure the following exclusion criteria are met: congestive heart failure, deep vein thrombosis of the lower extremities, malignant progressive hypertension, respiratory failure or other diseases, and serious risk of falling.
  3. Obtain written informed consent from all patients before beginning the study.

2. Clinical evaluation

  1. Record the demographic characteristics of the patient including the name, gender, date of birth, level of education, chief complaint, current medical history, past history, medical treatment, and current medications.
  2. Cognitive function assessment
    1. Ask the patient to complete the Mini-Mental State Examination (MMSE)12 record the patient's responses to a 30-question scale with a total score of 30 points for cognition evaluation, which involves the following seven aspects: time orientation, position orientation, instant memory, attention and computing power, delayed memory, language, and visual space.
      ​NOTE: The scores of MMSE are closely related to the level of education. The normal cognitive standard is illiteracy > 17 points, primary school > 20 points, and junior high school > 24 points13.
    2. Ask the patient to complete the Montreal Cognitive Assessment (MoCA)14 record the patient's responses to an 11-question scale with a total score of 30 points for cognition evaluation, which involves the following eight aspects: attention and concentration, executive function, memory, language, visual structure skills, abstract thinking, calculation, and orientation.
      ​NOTE: The normal cognitive standard is ≥ 26 points. If the subject has been educated for less than 12 years, they should add 1 point to the score15.
  3. Walking ability assessment
    1. Conduct the 10-m walk test (10 MWT)16. Ask the patient to perform three consecutive trials at a self-selected pace for safety, comfort, and higher speed, respectively. Record the time taken to walk to the middle 6 m in each trial (to exclude acceleration and deceleration effects).
    2. Conduct the timed up and go test (TUGT)17. Ask the patient to perform three consecutive TUG trials (stand up, walk 3 m, turn, walk back, and sit down) at a self-selected pace for safety and comfort18.

3. 3D gait analysis

  1. Patient preparation
    1. Inform the patient about the precautions and the purpose of the experiment.
    2. Ask the patient to wear tight underwear to fully expose the neck, shoulders, waist, and lower limbs.
    3. Record the values of various anthropometric indicators including height, weight, bilateral width of the ankle joints, bilateral knee diameter, pelvic width, bilateral pelvic depth, and bilateral leg length.
    4. Place 22 markers on key points of the patient based on the Davis protocol19: three markers on the trunk (7th cervical vertebrae, shoulders on both sides); three markers on the pelvis (both sides of the anterior superior iliac spine and ankle joint); six markers on the thigh (bilateral femoral greater trochanter, femoral condyle, and middle point of femoral greater trochanter and femoral condyle on the same side); six markers on the calf (bilateral humeral head, lateral ankle joint, and middle point of humeral head and lateral ankle joint on the same side); four markers on the foot (the fifth metatarsal head and the heel on both sides) (Figure 1).
    5. Click on the Start button of the 3D gait analysis system, and make a new profile for the patient.
    6. Enter basic patient information and previously measured parameters.
  2. Standing data acquisition
    1. Instruct the patient to maintain an upright position on the force plate for at least 3-5 s to gather the baseline data.
    2. Click on the Proc_Davis_Standing button to quickly check the position of the marker.
  3. Walking task data acquisition
    1. Determine the random order of three walking tasks by drawing lots.
    2. Ask the patient to walk on the walking pass for five trials at a self-selected comfortable speed, which is marked as Task 0 (consider the single walking task as the Baseline task).
    3. Ask the patient to walk while holding a bottle of water on the walking pass for five trials at a self-selected comfortable speed, which is marked as Task 1 (simple dual-motor task).
      NOTE: Ask the patient to hold a 550 mL bottle of water in the unaffected hand while holding the arm position of the shoulder joint at 0° and elbow flexion at 90°.
    4. Ask the patient to walk across the line in the middle of the walking pass for five trials at a self-selected comfortable speed, which is marked as Task 2 (complex dual-motor task).
      ​NOTE: Place a soft ruler in the middle of the walking pass before Task 2 data acquisition.

4. Data processing and analysis

  1. Select the middle three trials of each walking task to be processed to ensure the patient is stable.
  2. Identify each gait cycle with two consecutive heel stride points on the same side.
  3. Mark the toe-off point in each gait cycle20.
  4. Click on the Proc_DavisHeel+GI_AE button to compute the kinematic parameters of gait, as well as the computation of the Gait Performance Score (GPS) index.

5. Data extraction and statistical analysis of interest

  1. Select region of interest parameters from the processed data, which include special-temporary parameters (stance phase, swing phase, single stance, double stance, cadence), joint angle parameters (trunk obliquity (frontal plane), trunk tilt (sagittal plane), trunk rotation (transversal plane), pelvic obliquity (frontal plane), pelvic tilt (sagittal plane), pelvic rotation (transversal plane), hip flex-extension, hip ab-adduction, hip rotation, knee flex-extension, ankle dorsi-plantarflexion, and GPS index.
  2. Calculate DTC values based on the following formula[10]:
    ([single-task gait velocity – dual-task gait velocity]/ single-task gait velocity) × 100 (1)
  3. Perform the statistical analysis (see the Table of Materials) using the methodology described previously20,21.
    1. Present parametric data as means and standard deviation if normally distributed or as medians if not.
    2. Use the paired t-test to compare the differences in kinematic parameters between patients in Task 1 and Task 2 conditions.
    3. Use one-way analysis of variance to compare three different tasks (Task 0, Task 1, and Task 2) of the kinematic parameters. Set statistical significance at P < 0.05.

Representative Results

Eighteen patients with hemiplegia after stroke were recruited in this study. The average age of the participants was 51.61 ± 12.97 years; all were males. The proportion of left and right hemiplegia was 10/8; the average Brunnstrom stage was 4.50 ± 0.76. The average of MMSE and MoCA were 26.56 ± 1.67 and 20.06 ± 2.27, respectively. Other demographic characteristics (including stroke type and time of onset) are shown in Table 1. For the original data of gait dual-tasks (Task 1 and Task 2), there was no statistical difference in the spatiotemporal parameters (Table 2). However, in the joint angle parameters, the bilateral trunk rotation (transversal plane) was larger in Task 2 than in Task 1 (left side: Task 1, 18.40 ± 5.76 vs. Task 2, 26.35 ± 14.92, P = 0.004; right side: Task 1, 18.39 ± 7.04 vs. Task 2, 24.08 ± 18.18, P = 0.001). Bilateral pelvic rotation (transversal plane) was larger in Task 2 than in Task 1 (left side: Task 1, 20.71 ± 7.97 vs. Task 2, 21.31 ± 6.96, P = 0.024; right side: Task 1, 27.56 ± 9.71 vs. Task 2, 29.264 ± 11.17, P = 0.006). The differences were statistically significant (Table 3).

For the DTC values of gait dual-tasks (Task 1 and Task 2), the bilateral trunk obliquity (frontal plane) was higher in Task 2 than in Task 1 (left side: Task 1, 2.60 ± 36.38 vs. Task 2, -23.4 ± 40.62, P = 0.006; right side: Task 1, -10.82 ± 47.58 vs. Task 2, -11.42 ± 30.10, P = 0.013). The bilateral pelvic rotation (transversal plane) was higher in Task 2 than in Task 1 (left side: Task 1, -2.75 ± 36.20 vs. Task 2, -23 ± 40.36, P = 0.011; right side: Task 1, 1.66 ± 43.72 vs. Task 2, -31.89 ± 58.50, P = 0.006). All differences were statistically significant (Table 4 and Figure 2). At the same time, the right Cadence was significantly decreased in Task 2 relative to that in Task 1 (right side: Task 1, 18.40 ± 5.76 vs. Task 2, 26.35 ± 14.92, P = 0.044), and the right GPS was significantly decreased in Task 2 relative to that in Task 1 (right side: Task 1, 20.71 ± 4.87 vs. Task 2, 24.24 ± 10.33, P = 0.047) (Table 5 and Figure 3).

Figure 1
Figure 1: The gait analysis settings are based on the Davis protocol. Please click here to view a larger version of this figure.

Figure 2
Figure 2: Comparing the DTC values of trunk and joint angle parameters of the simple motor dual-task (Task 1) and complex motor dual-task (Task 2). (A) Trunk obliquity (frontal plane); (B) trunk rotation (transversal plane); (C) pelvic rotation (transversal plane). Abbreviation: DTC = dual-task gait cost. Please click here to view a larger version of this figure.

Figure 3
Figure 3: Comparing the DTC values of spatiotemporary parameters of the simple motor dual-task (Task 1) and the complex motor dual-task (Task 2). Percentages of (A) stance phase and (B) swing phase are shown for one gait cycle. Percentages of (C) single stance phase and (D) double stance phase are shown for one gait cycle. (E) The cadence and (F) GPS index are shown. Abbreviations: DTC = dual-task gait cost; GPS = Gait Performance Score. Please click here to view a larger version of this figure.

Subject Sex Age (years) Hemorrhage/infarct Hemiplegic side Stroke onset (months) Brunnstrom-stage (LE) MMSE MoCA 10MWT (customized speed) 10MWT (fast speed) TUGT (s)
001 male 30 Hemorrhage right 29 5 25 18 0.52 0.62 26
002 male 59 Infarct left 26 6 30 23 0.43 0.52 36
003 male 27 Infarct left 26 5 24 19 0.46 0.48 48
004 male 54 Hemorrhage right 23 5 26 18 0.56 0.61 58
005 male 63 Infarct left 23 4 29 23 0.62 0.72 28
006 male 45 Infarct left 23 5 25 19 0.56 0.63 33
007 male 67 Hemorrhage left 22 4 28 17 0.59 0.67 45
008 male 42 Infarct left 21 3 29 23 0.67 0.73 27
009 male 38 Infarct right 18 4 28 20 0.52 0.67 26
010 male 70 Infarct left 31 4 26 23 0.64 0.68 30
011 male 49 Hemorrhage left 17 4 24 20 0.46 0.53 45
012 male 42 Infarct left 19 3 27 16 0.43 0.56 49
013 male 45 Infarct right 26 5 26 24 0.56 0.74 29
014 male 45 Hemorrhage right 28 4 26 19 0.64 0.73 27
015 male 54 Infarct right 18 5 25 21 0.52 0.65 33
016 male 68 Infarct right 14 5 27 20 0.57 0.59 42
017 male 69 Infarct left 15 5 26 18 0.52 0.63 38
018 male 62 Infarct right 24 5 27 20 0.61 0.72 31
mean±SD 51.61±12.97 NA NA 22.39±4.70 4.50±0.76 26.56±1.67 20.06±2.27 0.55±0.07 0.64±0.08 36.17±9.29

Table 1: Basic characteristics of study subjects. Values are presented as a number or mean ± standard deviation. Abbreviations: MMSE = Mini-Mental State Examination; MoCA = Montreal Cognitive Assessment; 10MWT = 10-meter walk test; TUGT = timed up and go test; SD = standard deviation; LE = lower extremity; s = second.

Left side Right side
Task 1 Task 2 Difference P value Task 1 Task 2 Difference P value
Stance phase (%) 20.71±7.97 21.31±6.96 0.60±10.58 0.916 18.02±4.86 20.66±7.41 2.64±8.86 0.254
Swing phase (%) 27.56±9.71 29.26±11.17 1.70±14.80 0.285 23.68±6.74 29.88±12.19 6.20±13.93 0.916
Single stance (%)  26.91±5.41 31.09±11.67 4.18±12.86 0.519 31.16±9.27 27.80±10.67  -3.36±14.13 0.583
Double stance (%) 24.72±7.10 31.31±5.99 6.59±9.29 0.291 37.55±17.79 44.10±12.60 6.55±21.80 0.369
Cadence (steps/min) 18.40±5.76 26.35±14.92 7.95±15.99 0.521 18.39±7.04 24.08±18.18 5.79±19.50 0.720
GPS (scores) 17.91±7.24 23.09±9.49 5.18±11.94 0.580 20.71±4.87 24.24±10.33 3.53±11.42 0.058

Table 2: Differences in spatiotemporary parameters of the simple motor dual-task (Task 1) and complex motor dual-task (Task 2). Values are presented as a number or mean ± standard deviation. Statistical significance was set as P < 0.05 and marked in bold. Abbreviations: GPS = Gait Performance Score; min = minute.

Left side Right side
Task 1 Task 2 Difference P value Task 1 Task 2 Difference P value
Trunk Obliquity (Frontal plane) 27.86±7.45 24.63±4.08 -3.23±8.49 0.263 37.91±4.76 48.89±7.56 10.98±8.93 0.114
Trunk Tilt (Sagittal plane) 31.43±12.69 34.25±12.69 2.82±17.95 0.238 24.64±7.53 29.85±16.93 5.21±18.53 0.582
Trunk Rotation (Transversal plane) 18.40±5.76 26.35±14.92 7.95±15.99 0.004 18.39±7.04 24.08±18.18 5.69±19.50 0.001
Plevic Obliquity (Frontal plane) 16.99±6.07 25.05±15.43 8.06±16.58 0.277 20.66±7.41 18.02±4.86 -2.64±8.86 0.937
Plevic Tilt (Sagittal plane) 23.68±6.74 29.88±12.19 6.20±13.93 0.282 34.94±18.29 39.31±12.86 4.37±22.36 0.689
Plevic Rotation (Transversal plane) 20.71±7.97 21.31±6.96 0.60±10.58 0.024 27.56±9.71 29.26±11.17 1.70±14.80 0.006
Hip Ab-Adduction 20.71±4.87 24.24±10.33 3.53±11.42 0.148 17.91±7.24 23.09±9.49 5.18±11.94 0.238
Hip Flex-Extension 37.55±17.79 44.10±21.60 6.55±27.98 0.544 13.00±2.59 19.87±10.16 6.87±10.48 0.531
Hip Rotation 27.69±11.17 28.27±13.78 0.58±17.74 0.323 31.16±9.27 27.80±10.67 -3.36±14.13 0.006
Knee Flex-Extension 26.91±5.41 31.09±11.67 4.18±12.86 0.475 23.37±7.75 29.16±18.66 5.79±20.21 0.791
Ankle Dors-Plantarflex 21.75±11.07 27.54±13.41 5.79±17.39 0.213 25.87±10.71 25.87±11.50 0±15.71 0.112

Table 3: Differences in trunk and joint angle parameters of the simple motor dual-task (Task 1) and complex motor dual-task (Task 2). Values are presented as a number or mean ± standard deviation. Statistical significance was set as P < 0.05 and marked in bold.

Left side Right side
Task 1 Task 2 Difference P value Task 1 Task 2 Difference P value
Trunk Obliquity (Frontal plane) 2.60±36.38 -23.4±40.62 -26.00±54.53 0.006 -10.82±47.58 -11.42±30.10 -0.60±56.30 0.013
Trunk Tilt (Sagittal plane) 15.34±7.74 13.40±8.22 -1.94±11.29 0.260 16.28±5.12 36.62±5.20 20.34±7.30 0.489
Trunk Rotation (Transversal plane) -8.15±26.55 -18.56±29.54 -10.41±39.72 0.004 2.75±36.20 -23.00±40.36 -25.75±54.22 0.001
Pelvic Obliquity (Frontal plane) 15.34±7.74 13.40±8.22 -1.94±11.29 0.153 62.51±4.53 64.40±6.19 1.89±7.67 0.962
Pelvic Tilt (Sagittal plane) 37.49±6.36 37.60±6.19 0.11±8.88 0.097 12.89±6.36 14.32±3.79 1.43±7.43 0.510
Pelvic Rotation (Transversal plane) -2.75±36.20 -23±40.36 -20.25±54.22 0.011 1.66±43.72 -31.89±58.50 -30.23±73.03 0.006
Hip Ab-Adduction 83.15±7.21 78.49±5.91 -4.66±9.32 0.125 84.18±8.81 92.56±6.51 8.38±10.95 0.242
Hip Flex-Extension 37.49±6.36 37.60±6.19 0.11±8.88 0.392 12.89±6.36 14.32±3.79 1.43±7.40 0.583
Hip Rotation 37.64±6.87 36.98±6.21 -0.66±9.26 0.549 49.6±8.52 56.52±4.52 6.92±9.65 0.004
Knee Flex-Extension 50.68±4.89 67.63±4.87 16.95±6.90 0.343 78.54±7.92 57.95±7.16 -20.59±10.68 0.673
Ankle Dors-Plantarflex 27.86±7.45 24.63±4.08 -3.23±8.50 0.263 37.91±4.76 48.89±7.56 10.98±8.93 0.114

Table 4: Differences in dual-task gait cost values of trunk and joint angle parameters of the simple motor dual-task (Task 1) and complex motor dual-task (Task 2). Values are presented as a number or mean ± standard deviation. Statistical significance was set as P < 0.05 and marked in bold.

Left side Right side
Task 1 Task 2 Difference P value Task 1 Task 2 Difference P value
Stance phase (%) 74.44±31.37 79.08±16.36 4.64±35.38 0.916 63.24±7.60 36.76±5.84 -26.48±9.58 0.236
Swing phase (%) 35.15±7.74 15.34±4.53 -19.81±8.97 0.980 63.24±7.61 52.28±4.36 -10.96±8.77 0.654
Single stance (%) 62.51±6.19 62.40±6.36 -0.11±8.88 0.348 37.49±6.19 37.60±6.36 0.11±8.88 0.671
Double stance (%) 37.78±14.71 39.19±8.05 1.41±16.77 0.164 37.03±15.55 39.19±8.05 2.16±17.51 0.406
Cadence (steps/min) 2.53±55.72 12.13±43.62 9.60±70.76 0.087 18.40±5.76 26.35±14.92 7.95±15.99 0.044
GPS (scores) 11.1±34.86 9.65±37.01 -1.45±50.84 0.681 20.71±4.87 24.24±10.33 3.53±11.42 0.047

Table 5: Differences in dual-task gait cost values of spatiotemporary parameters of the simple motor dual-task (Task 1) and complex motor dual-task (Task 2). Values are presented as a number or mean ± standard deviation. Statistical significance was set as P < 0.05 and marked in bold. Abbreviations: GPS = Gait Performance Score; min = minute.

Supplementary Table 1: Differences in trunk and joint angle parameters of single motor tasks (Task 0), simple motor dual-task (Task 1), and complex motor dual-task (Task 2) (degree). Values are presented as a number or mean ± standard deviation. Statistical significance was set as P < 0.05 and marked in bold. Please click here to download this Table.

Supplementary Table 2: Differences in spatiotemporary parameters of single motor tasks (Task 0), simple motor dual-task (Task 1), and complex motor dual-task (Task 2). Values are presented as a number or mean ± standard deviation. Statistical significance was set as P < 0.05 and marked in bold. Abbreviations: GPS = Gait Performance Score; min = minute. Please click here to download this Table.

Discussion

This study describes a protocol for the clinical assessment of dual motor task gait analysis in stroke patients with motor control deficits. The design of this protocol was based on two main points. First, most previous studies used a single walking task to assess the gait function of stroke patients, and the related discussions on motor control were inadequate, especially because the principles of complex motor movements were rarely involved22,23. Therefore, in this study, in addition to the single walking task as the baseline, the authors mainly focused on the comparison of two dual-tasks of motor performance and walking, including the task of water-holding (simple motor dual-task) and the task of crossing obstacles (complex motor dual-task)24. The water-holding task was identified as being equivalent to a combination of a simple walking task and a simple motor task.

Because the cross-obstacle walking task involvedmore nervous system, skeletal muscle movement, and cognitive resources in participating in motor control (including motor planning, motor coordination, and motor feedback) than the simple motor dual-task of holding water while walking, it was identified as being equivalent to a combination of a simple walking task and a complex motor task. Thus, the motor control function deficit after stroke could be closely examined based on this experimental task design. Previous dual-task gait analyses in the elderly and in patients with cognitive impairment have reported decreased velocity and cadence in dual-task walking compared with single-task walking25.

However, the results of this study in stroke patients show that there were no significant differences in spatiotemporal parameters in dual motor tasks compared with those of the single motor task. The major changes were only observed in the proximal joint angles, especially the angles of the trunk, pelvis, and hip joints, which were significantly larger in dual motor tasks than in single walking tasks. This might be related to the obvious motor deficit of recruited stroke patients compared with the elderly or cognitively impaired patients (their basic motor function is preserved). There might be similar difficulties while performing a simple motor task and a complex motor task in stroke patients with existing impaired motor function, which could explain why the spatiotemporal parameters and distal joint angle were not sensitive parameters for the comparison between single and dual motor tasks in stroke patients. Additionally, these results suggest that rehabilitation training to increase trunk and large joint control might help stroke patients improve their ability to perform complex daily motor activities.

The heterogeneity of stroke patients has always been the main obstacle in many investigations26. A previous study had explored the use of the DTC value (the dual-task consumption ratio as the difference between a single task and double tasks) to eliminate the heterogeneity between stroke patients10. Indeed, the representative results demonstrate that the bilateral joint angle parameters of the large proximal joints in the complex dual walking task are significantly larger than those in the simple motor dual-task, indicating the advantages of using the DTC values in dual-task gait assessment for stroke patients.

This study has three main limitations. First, as this study is mainly a methodological demonstration of dual-motor tasks, the representative data only included data of 18 male stroke patients. In addition, previous studies have suggested that both gender and age impact gait and balance function. For example, as age increases, the ability to control posture decreases, and women are more affected than men. Moreover, the lack of significant difference in spatiotemporal parameters found in this study might be simply because of the sample size. Hence, further studies are needed to increase the sample size and include female subjects to extend the clinical application of this assessment. In conclusion, through dual-motor walking tasks and the calculation of DTC values, this research protocol aims to provide a basis for the clinical diagnosis of gait function and an in-depth study of motor control in stroke patients.

開示

The authors have nothing to disclose.

Acknowledgements

We thank Anniwaer Yilifate for proofreading our manuscript. This study was supported by the National Science Foundation under Grant No. 81902281 and No. 82072544, the General Guidance Project of Guangzhou Health and Family Planning Commission under Grant No. 20191A011091 and No. 20211A011106, the Guangzhou Key Laboratory Fund under Grant No. 201905010004 and Guangdong Basic and Applied Basic Research Foundation under Grant No.2020A1515010578.

Materials

BTS Smart DX system Bioengineering Technology System, Milan, Italy 1 Temporospatial data collection
BTS SMART-Clinic software Bioengineering Technology System, Milan, Italy 2 Data processing
SPSS software (version 25.0) IBM Crop., Armonk, NY, USA Statistical analysis

参考文献

  1. Cho, K. H., Kim, M. K., Lee, H. -. J., Lee, W. H. Virtual reality training with cognitive load improves walking function in chronic stroke patients. The Tohoku Journal of Experimental Medicine. 236 (4), 273-280 (2015).
  2. Delavaran, H., et al. Cognitive function in stroke survivors: A 10-year follow-up study. Acta Neurologica Scandinavica. 136 (3), 187-194 (2017).
  3. Zhang, W., et al. The effects of transcranial direct current stimulation versus electroacupuncture on working memory in healthy subjects. Journal of Alternative and Complementary Medicine. 25 (6), 637-642 (2019).
  4. Pin-Barre, C., Laurin, J. Physical exercise as a diagnostic, rehabilitation, and preventive tool: influence on neuroplasticity and motor recovery after stroke. Neural Plasticity. 2015, 608581 (2015).
  5. Auvinet, B., Touzard, C., Montestruc, F., Delafond, A., Goeb, V. Gait disorders in the elderly and dual task gait analysis: a new approach for identifying motor phenotypes. Journal of Neuroengineering and Rehabilitation. 14 (1), 7 (2017).
  6. Tramontano, M., et al. Maintaining gait stability during dual walking task: effects of age and neurological disorders. European Journal of Physical and Rehabilitation Medicine. 53 (1), 7-13 (2017).
  7. Sakurai, R., Bartha, R., Montero-Odasso, M. Entorhinal cortex volume is associated with dual-task gait cost among older adults with MCI: results from the gait and brain study. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences. 74 (5), 698-704 (2019).
  8. Howcroft, J., Lemaire, E. D., Kofman, J., McIlroy, W. E. Dual-task elderly gait of prospective fallers and non-fallers: a wearable-sensor based analysis. Sensors. 18 (4), 1275 (2018).
  9. Fernandez-Gonzalez, P., Molina-Rueda, F., Cuesta-Gomez, A., Carratala-Tejada, M., Miangolarra-Page, J. C. Instrumental gait analysis in stroke patients. Revista de Neurologia. 63 (10), 433-439 (2016).
  10. Montero-Odasso, M. M., et al. Association of dual-task gait with incident dementia in mild cognitive impairment: results from the gait and brain study. JAMA Neurology. 74 (7), 857-865 (2017).
  11. Bohannon, R. W., Smith, M. B. Interrater reliability of a modified Ashworth scale of muscle spasticity. Physical Therapy. 67 (2), 206-207 (1987).
  12. Llamas-Velasco, S., Llorente-Ayuso, L., Contador, I., Bermejo-Pareja, F. Spanish versions of the Minimental State Examination (MMSE). Questions for their use in clinical practice. Revista de Neurologia. 61 (8), 363-371 (2015).
  13. Yoelin, A. B., Saunders, N. W. Score disparity between the MMSE and the SLUMS. American Journal of Alzheimer’s Disease and Other Dementias. 32 (5), 282-288 (2017).
  14. Julayanont, P., Brousseau, M., Chertkow, H., Phillips, N., Nasreddine, Z. S. Montreal Cognitive Assessment Memory Index Score (MoCA-MIS) as a predictor of conversion from mild cognitive impairment to Alzheimer’s disease. Journal of the American Geriatrics Society. 62 (4), 679-684 (2014).
  15. Carson, N., Leach, L., Murphy, K. J. A re-examination of Montreal Cognitive Assessment (MoCA) cutoff scores. International Journal of Geriatric Psychiatry. 33 (2), 379-388 (2018).
  16. Peters, D. M., Fritz, S. L., Krotish, D. E. Assessing the reliability and validity of a shorter walk test compared with the 10-Meter Walk Test for measurements of gait speed in healthy, older adults. Journal of Geriatric Physical Therapy. 36 (1), 24-30 (2013).
  17. Podsiadlo, D., Richardson, S. The timed “Up & Go”: a test of basic functional mobility for frail elderly persons. Journal of the American Geriatrics Society. 39 (2), 142-148 (1991).
  18. Lin, Q., et al. Quantitative static and dynamic assessment of balance control in stroke patients. Journal of Visualized Experiments: JoVE. (159), e60884 (2020).
  19. Davis, R. B., Ounpuu, S., Tyburski, D., Gage, J. R. A gait analysis data collection and reduction technique. Human Movement Science. 10 (5), 575-587 (1991).
  20. Liang, J., et al. The lower body positive pressure treadmill for knee osteoarthritis rehabilitation. Journal of Visualized Experiments: JoVE. (149), e59829 (2019).
  21. Liang, J., et al. The effect of anti-gravity treadmill training for knee osteoarthritis rehabilitation on joint pain, gait, and EMG: Case report. Medicine (Baltimore). 98 (18), 15386 (2019).
  22. Balaban, B., Tok, F. Gait disturbances in patients with stroke. PM & R: The Journal of Injury, Function, and Rehabilitation. 6 (7), 635-642 (2014).
  23. Li, M., Xu, G., Xie, J., Chen, C. A review: Motor rehabilitation after stroke with control based on human intent. Proceedings of the Institute of Mechanical Engineers. Part H, Journal of Engineering in Medicine. 232 (4), 344-360 (2018).
  24. Bloem, B. R., Valkenburg, V. V., Slabbekoorn, M., Willemsen, M. D. The Multiple Tasks Test: development and normal strategies. Gait Posture. 14 (3), 191-202 (2001).
  25. Montero-Odasso, M., Muir, S. W., Speechley, M. Dual-task complexity affects gait in people with mild cognitive impairment: the interplay between gait variability, dual tasking, and risk of falls. Archives of Physical Medicine and Rehabilitation. 93 (2), 293-299 (2012).
  26. Selvaraj, U. M., Poinsatte, K., Torres, V., Ortega, S. B., Stowe, A. M. Heterogeneity of B cell functions in stroke-related risk, prevention, injury, and repair. Neurotherapeutics. 13 (4), 729-747 (2016).

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記事を引用
Ou, H., Lang, S., Zheng, Y., Huang, D., Gao, S., Zheng, M., Zhao, B., Yiming, Z., Qiu, Y., Lin, Q., Liang, J. Motor Dual-Tasks for Gait Analysis and Evaluation in Post-Stroke Patients. J. Vis. Exp. (169), e62302, doi:10.3791/62302 (2021).

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