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

Summary

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 control^2,3,4. 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 performance^5,6. 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 task^7,8,9. 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 (7^th 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 previously^20,21.
   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.

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 ...

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 involved^22,23. Therefore, in ...

Materials

Name	Company	Catalog Number	Comments
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