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

Haining Ou; Shijuan Lang; Yuxin Zheng; Dongqing Huang; Sheng Gao; Meifeng Zheng; Biyi Zhao; Zulipiya Yiming; Yaxian Qiu; Qiang Lin; Junjie Liang

doi:10.3791/62302

JoVE Journal > Neuroscience

Neurosciences

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

Published: March 11, 2021

doi:

10.3791/62302

Haining Ou*^1,2,3,4, Shijuan Lang*^1,2,3, Yuxin Zheng^1,2,3, Dongqing Huang², Sheng Gao¹, Meifeng Zheng^1,2, Biyi Zhao², Zulipiya Yiming², Yaxian Qiu^1,2, Qiang Lin*^1,2,3,4, Junjie Liang*^1,2,3

¹Department of Rehabilitation Medicine,The Fifth Affiliated Hospital of Guangzhou Medical University, ²Department of Rehabilitation Medicine,Guangzhou Medical University, ³Rehabilitation Medicine Lab,Guangzhou Medical University, ⁴Guangzhou Key Laboratory of Enhanced Recovery after Abdominal Surgery,The Fifth Affiliated Hospital of Guangzhou Medical University

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 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

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.
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.
Obtain written informed consent from all patients before beginning the study.

2. Clinical evaluation

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.
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.
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

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.
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.
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

Select the middle three trials of each walking task to be processed to ensure the patient is stable.
Identify each gait cycle with two consecutive heel stride points on the same side.
Mark the toe-off point in each gait cycle²⁰.
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

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.
Calculate DTC values based on the following formula^[10]:
([single-task gait velocity – dual-task gait velocity]/ single-task gait velocity) × 100 (1)
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: The gait analysis settings are based on the Davis protocol. Please click here to view a larger version of this figure.

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: 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.

Divulgations

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

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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).