The effect of robot-assisted gait training on cortical activation in stroke patients: A functional near-infrared spectroscopy study

Abstract

OBJECTIVE:

To investigate the effects of the robot–assisted gait training on cortical activation and functional outcomes in stroke patients.

METHODS:

The patients were randomly assigned: training with Morning Walk® (Morning Walk group; n = 30); conventional physiotherapy (control group; n = 30). Rehabilitation was performed five times a week for 3 weeks. The primary outcome was the cortical activation in the Morning Walk group. The secondary outcomes included gait speed, 10-Meter Walk Test (10MWT), FAC, Motricity Index–Lower (MI–Lower), Modified Barthel Index (MBI), Rivermead Mobility Index (RMI), and Berg Balance Scale (BBS).

RESULTS:

Thirty-six subjects were analyzed, 18 in the Morning Walk group and 18 in the control group. The cortical activation was lower in affected hemisphere than unaffected hemisphere at the beginning of robot rehabilitation. After training, the affected hemisphere achieved a higher increase in cortical activation than the unaffected hemisphere. Consequently, the cortical activation in affected hemisphere was significantly higher than that in unaffected hemisphere (P = 0.036). FAC, MBI, BBS, and RMI scores significantly improved in both groups. The Morning Walk group had significantly greater improvements than the control group in 10MWT (P = 0.017), gait speed (P = 0.043), BBS (P = 0.010), and MI–Lower (P = 0.047) scores.

CONCLUSION:

Robot-assisted gait training not only improved functional outcomes but also increased cortical activation in stroke patients.

Keywords

Stroke stroke rehabilitation robotics gait hospitalization functional connectivity

1 Introduction

Stroke is one of the principal causes of morbidity and mortality among adults in the developed world and the leading cause of disability in all industrialized countries. For stroke patients, ambulation is often limited by muscle weakness, abnormal muscle synergy, and spasticity, which could inhibit selective muscle activation during walking (Lin et al., 2013). After experiencing strokes, patients frequently complain of gait disturbances, and stroke patients have significantly lower mean walking speeds than the general population. This restricted patients in their activities of daily living (Dobkin, 2004), and rehabilitation aims to mitigate these restrictions. Traditional gait rehabilitation therapy for stroke patients is labor-intensive, requiring the therapist to support the patient’s legs and torso (Hwang et al., 2003). To compensate for these shortcomings and treat various patients in need of rehabilitation treatment, robotic rehabilitation treatment has been developed and has been widely applied in recent years. Robotic rehabilitation treatment has been widely demonstrated as comparable to conventional rehabilitation treatment (Hwang et al., 2003; Lo et al., 2017). Morning Walk® is an end-effector–type rehabilitation robot that was developed in Korea in 2014 to perform rehabilitation treatment for patients with gait disturbances.

A previous study (Kim et al., 2019) demonstrated that rehabilitation treatment using the Morning Walk® improved strength and balance in stroke patients. However, no studies have investigated the therapeutic mechanisms of end-effector robots like the Morning Walk®.

Like functional magnetic resonance imaging (fMRI), functional near-infrared spectroscopy (fNIRS) indirectly analyzes brain activation. However, unlike fMRI, fNIRS has the advantage of allowing for real-time brain activation analysis while a subject is performing a dynamic task (Herold et al., 2017; Lee et al., 2020; Mihara & Miyai, 2016; Oh et al., 2018). Although previous studies have confirmed cortical activation among patients undergoing robotic rehabilitation (Herold et al., 2017; Lee et al., 2020; Möller et al., 2019), there are no published reports of studies investigating cortical activation among stroke patients during rehabilitation using an end-effector–type robot. Additionally, despite reports of changes in cortical activation among stroke patients (Herold et al., 2017), but no publications have reported on the changes in cortical activation before and after robot-assisted rehabilitation treatment. Therefore, this study aimed to investigate the effects of robot-assisted gait training via fNIRS assessments of cortical activation and functional outcomes.

2 Methods

2.1 Ethics statements

This was an unblinded, prospective, randomized controlled trial approved by the Asan Medical Center Institutional Review Board (No. 2018-0895) and registered with the Clinical Research Information Service database (KCT0003090). All subjects provided written informed consent. The funding organizations did not participate in, comment on, or influence the analysis or write-up of the paper.

2.2 Participants

A total of 60 patients who were admitted to the Asan Medical Center’s Department of Rehabilitation Medicine between December 2018 and December 2019 were recruited. The inclusion criteria were as follows: within 1 year of stroke onset, a first stroke with hemiparesis, age ≥18 years; previously an independent walker; FAC score ≥2. Patients were excluded for the following reasons: severe communication difficulties due to cognitive disorder (Mini-Mental State Examination score <10) (Han et al., 2008) or aphasia; serious lower-limb musculoskeletal impairment; psychological instability; weighing over 135 kg; over 195 cm in height; severe contracture due to abnormal muscle tone; an open fracture, wound or pressure ulcer; the risk of compression fracture due to severe osteoporosis; or evidence of contact infection.

Participants were randomly assigned to either the experimental group or the control group using a random number table in a 1 : 1 ratio.

2.3 Procedure

All participants received their assigned treatment five times per week for a total of 15 times for 3 weeks.

The Morning Walk group received robot-assisted gait training with the Morning Walk® for 30 minutes per session, plus 1 hour of conventional physiotherapy. The control group received 1.5 hours of conventional physiotherapy. Conventional physiotherapy was based on traditional neurodevelopmental treatment techniques developed by Bobath (Gonzalez et al., 2001). Morning Walk® is an end-effector–type lower limb robot, which was developed at CUREXO Inc. in Korea in 2014 for the rehabilitation of patients with gait disturbances. It has a saddle that can support the patient’s weight. Accompanying virtual reality software allows for interactive training. The device can be used to apply free-walking programs with multiple settings for walking speed, stride length, and various walking motions, such as flat ground and stair-climbing, enabling complex treatment protocol designs (Dobkin et al, 2004).

For robot-assisted rehabilitation, the speed was controlled in terms of cadence (step/minute) and recorded for each trial. the patients started at a cadence of 30–35 steps/minute and a step length of 30–35 cm with ground-level gait. These were adjusted according to the patient’s tolerance. If patients were tolerated, the speed was maintained or increased in the next rehabilitation session.

The following outcome measures were evaluated before the first treatment session and after completion of the treatment program. The primary outcome measure was changes in cortical activation, assessed using fNIRS. Since the purpose of this study was to investigate changes in cerebral cortical activation associated with robot-assisted gait training, only the Morning Walk group underwent fNIRS assessments. The secondary outcome measures were walking ability, lower limb function, active daily living function, and static and dynamic balance. Walking ability was assessed using the Functional Ambulatory Category (FAC) (Mehrholz et al., 2007) score, 10 Meter Walk Test (10MWT) (Wade & Hewer, 1987), and Rivermead Mobility Index (RMI) (Shah et al., 1989). Lower limb function was assessed using the Motricity Index for the lower extremities (MI–Lower). The FAC scale (scored from 1 to 6) is classified in to 6 levels of walking ability based on the physical support required. The FAC is widely used because it can be measured quickly, easily, and simply. The 10MWT is commonly used to estimate gait velocity in stroke patients. In this study, the time (second) taken to walk 10 meters was measured and recorded. The RMI (scored from 0 to 15) test is used to assess functional mobility in gait, balance, and transfers. The MI–Lower (Demeurisse et al., 1980) is a valid tool for assessing muscular coordination and strength. MI–Lower is made up of items from the Motricity Index, which evaluates the lower extremity muscles. Higher Motricity Index scores indicate favorable features (scored from 0 to 100). Active daily living function was assessed using The Modified Barthel Index (MBI), which (scored from 0 to 100) is a reliable index for measuring activities of daily living, with higher scores indicating greater independence (Shah et al., 1989). Static and dynamic balance was measured using the Berg Balance Scale (BBS) (scored from 0 to 56) (Blum & Korner-Bitensky, 2008). Gait speed was measured using the Optogait system (Microgate Corporation, Italy), a measuring device that evaluates the subject’s gait pattern by placing an infrared ray output bar on the floor while the subject walks at a distance of 4 meters. All evaluations were performed by a licensed physiotherapist. During the study, patients were monitored for side-effects or safety issues associated with rehabilitation treatment.

2.3.1 fNIRS data acquisition

A wired continuous-wave fNIRS system was used for dynamic cortical activation change measurements (Möller et al., 2019). fNIRS is a non-invasive, optical neuroimaging technique that measures cerebral hemodynamic responses, records the relative changes in the concentration of oxygenated (oxyHb) and deoxygenated hemoglobin (de-oxyHb) resulting from neural activation. An increase of oxyHb concentration and a decrease of de-oxyHb concentration can usually be observed in response to regional brain activation (Holtzer et al., 2011; Maidan et al., 2016). NIRScout (NIRx Medical Technologies LLC, Germany) was used to record hemodynamic responses. A black elasticized cap was used to reduce interference from ambient light, and to position the optode according to the international 10–20 system (Okamoto et al., 2004). The distance between each optode was 2.0 cm. A total of 12 optodes were used, consisting of eight sources and four detectors, resulting in a total of 12 channels (Fig. 2). Optodes were positioned using a standard optode montage setup template (prfMotor_6×6) provided by the manufacturer (NIRx Medical). Optodes covered the primary motor cortex (BA 4 and 6) in both hemispheres of the brain. Source optodes emitted infrared light at wavelengths of 685, 780, 808, and 830 nm. The laptop computer used for data capture was placed on the table next to the Morning Walk® (Fig. 2A). fNIRS was measured as follows: The patient wore a head cap with an optode, stood with his or her eyes open before starting treatment for the first time, set the value to the baseline, and performed a task (walking rehabilitation with a Morning Walk®) for 20 minutes. Flat walking and stair climbing were performed considering the endurance and functional capacity of each patient. Cortical activation was measured by fNIRS during the first and last treatment sessions.

2.3.2 fNIRS data processing and block average

In this process, the signal quality of each channel of the data measured during the task was assessed to obtain the most significant signal. To maximize reliability, signal errors, such as spikes (in case of sudden deviation from the trend) or discontinuities (in case of signal breaks in a step shape) due to environmental influences were removed from the data. Finally, a bandpass filter was used to remove noise and slow drift. After that, the oxygen change amount was calculated using the Modified Beer–Lambert Law (MBLL) (Delpy et al., 1988) and the hemodynamic model. With this equation, concentration changes can be calculated using the change in observed values for each wavelength. Through signal processing, we converted the observed electrical signal into a value reflecting the changes in oxygen levels. Since this was a relative value, it was assumed that the measurement started at 0 seconds.

2.4 Statistical analysis

SPSS Statistics for Windows, version 25 (IBM Corp., Armonk, NY, USA) was used to analyze the data. Since this was a pilot study, the sample size was not calculated. For baseline characteristics, the Morning Walk group and the control group were compared using the chi-square test and the Mann–Whitney U test, as appropriate. For the primary outcome, fNIRS data, the paired-samples t-test, and the Wilcoxon signed-rank test were used to confirm the difference between the pre- and post-rehabilitation activity levels of the affected and unaffected cerebral hemisphere. For the secondary outcomes, the Wilcoxon signed-rank test was used to evaluate differences between outcomes at baseline, and the Mann–Whitney U test and Wilcoxon signed-rank test were used to assess for differences between the Morning Walk group and the control group. Statistical significance was defined as P < 0.05.

3 Results

From December 2018 to December 2019, a total of 146 patients were admitted to the Department of Rehabilitation Medicine after being diagnosed with stroke. Among them, a total of 60 people who met the eligible criteria were enrolled and randomized; 30 people were assigned to the Morning Walk group, and 30 were assigned to the control group (Fig. 1).

Fig. 1

CONSORT flow diagram.

Fig. 2A

Equipment worn by participants. The cap with 12 optodes is connected to the cable-strain-relief arm assembly and the assembly and laptop computer are connected.

Fig. 2B

Topographical layout of the 12-optode (eight sources and four detectors) placement covering motor cortex resulting in 12 channels.

Twenty-four people dropped out of the study: 15 patients refused or discontinued rehabilitation treatment because they were in poor clinical condition not related to rehabilitation, and eight patients were discharged early. Eighteen out of 24 dropouts were in poor condition and refused the study before conducting pre-evaluation. Eighteen patients in the experimental group and 18 patients in the control group each completed rehabilitation treatment. fNIRS measurements were completed for 15 patients in the Morning Walk groups. There were no adverse events during robot-assisted rehabilitation or conventional rehabilitation.

The robot speed was controlled in terms of cadence (step/minute) and recorded for each trial. Most patients in the Morning Walk group were controlled at a speed of 30–40 steps/min, and the mean value was 36.56 steps/minute.

Finally, in terms of baseline characteristics, the mean gait speed and body mass index were significantly higher in the control group than the Morning Walk group (P = 0.025 and P = 0.046, respectively). Other values, including for FAC, MBI, BBS, and RMI, were not significantly different between the two groups (Table 1).

Table 1

Baseline characteristics of the study population

Characteristics	Morning Walk group	Control group	P-value
	(n = 18)	(n = 18)
Patient demographics
Age (year)	61.22±12.78	60.39±13.59	0.924
Gender (n)
Male	12 (66.7)	9 (50.0)	0.311†
Female	6 (33.3)	9 (50.0)
BMI (kg/m²)	21.8±3.5	23.4±3.2	0.046^*
Weight (kg)	59.9±14.0	66.0±12.5	0.074
Height (cm)	165.3±8.3	167.3±7.2	0.435
MMSE	24.6±5.6	24.3±6.3	0.804
Time post-stroke (months)	3.4±3.6	3.6±5.4	0.351
Stroke etiology (n)
Ischemic	12 (66.7)	13 (72.2)	0.718†
Hemorrhagic	6 (33.3)	5 (27.8)
Initial FAC	3.5±1.1	2.8±0.8	0.060
Initial MBI	69.8±25.8	66.4±22.1	0.448
Initial BBS	37.5±18.2	34.5±13.3	0.255
Initial MI_Lower	71.4±17.3	66.3±11.3	0.315
Initial RMI	7.2±3.2	6.1±2.2	0.237
Initial Gait speed (m/s)	0.8±0.4	0.5±0.2	0.048^*
Initial 10MW (second)	8.7±6.7	9.0±3.0	0.221

Values are presented as mean±SD (standard deviation) or number/percentage. BMI, body mass index; MMSE, Mini-Mental State Examination; FAC, Functional Ambulation Category; 10MWT, 10 Meter Walk Test; MBI, Modified Barthel Index; BBS, Berg Balance Scale; MI, Motricity Index; RMI, Rivermead Mobility Index; ^*p < 0.05. ^†Chi-square test; Mann–Whitney U test for time post-stroke, otherwise independent t-test.

3.1 Primary outcome: fNIRS data

After the first session of rehabilitation, the mean cortical activation level in the unaffected cerebral hemisphere was higher than the affected hemisphere (P = 0.653) After 3 weeks of robotic training, the mean cortical activation levels both hemispheres increased (affected hemisphere, P = 0.194; unaffected hemisphere, P = 0.565)

The mean degree of change was greater in the affected hemisphere than the unaffected hemisphere. As a result, the mean cortical activation level in the affected hemisphere was significantly higher than that of the unaffected hemisphere at the end of training (P = 0.036) (Figs. 3 and 4).

Fig. 3

Mean oxyhemoglobin concentrations (millimolar (mM)) in motor cortex before and after rehabilitation. In the last session, the mean oxyhemoglobin concentration in affected hemisphere was significantly higher than that of unaffected hemisphere (P = 0.036).

Fig. 4

Changes in cortical activation (concentration of oxyhemoglobin in motor area) of the right hemiparesis patient with lesions in the left hemisphere among Morning Walk group patients.

3.2 Secondary outcomes: functional data

In the control group, when comparing pre- and post-rehabilitation treatment, only FAC, K-MBI, BBS, and RMI outcomes significantly improved. However, in the Morning Walk group, all of the secondary outcomes significantly improved after treatment relative to their pre-intervention levels. Additionally, the Morning Walk group had significantly greater improvements than the control group in mean self-selective velocity (10MW_SS, P = 0.037), fastest velocity (10MW_FV, P = 0.017), and gait speed (P = 0.043), as well as mean BBS (P = 0.010), MI–Lower (P = 0.047) scores (Table 2).

Table 2
Secondary outcome measures at baseline and at 3 weeks

Morning Walk group (N = 18) Control (N = 18)

baseline post p-value^* baseline post p-value^* p-value^**

FAC 3.5±1.1 4.4±1.2 0.002 2.8±0.8 3.8±1.2 0.001 0.124

10MW (second) 8.7±6.7 5.5±3.1 0.001 9.0±3.0 8.4±3.8 0.077 0.017

K-MBI 69.8±25.8 84.5±24.1 <0.0001 66.4±22.1 78.5±21.3 0.001 0.259

BBS 37.5±18.1 48.2±14.5 <0.0001 34.5±13.3 41.4±12.7 0.002 0.010

MI_Lower 71.4±17.3 80.5±15.4 0.001 66.3±11.3 71.1±11.6 0.107 0.047

RMI 7.2±3.2 10.1±3.4 0.000 6.1±2.2 8.6±3.1 <.0001 0.100

Gait speed(m/s) 0.8±0.4 1.0±0.3 0.110 0.5±0.2 0.7±0.3 0.117 0.043

	Morning Walk group (N = 18)	Control (N = 18)
FAC	3.5±1.1	4.4±1.2	0.002	2.8±0.8	3.8±1.2	0.001	0.124
10MW (second)	8.7±6.7	5.5±3.1	0.001	9.0±3.0	8.4±3.8	0.077	0.017
K-MBI	69.8±25.8	84.5±24.1	<0.0001	66.4±22.1	78.5±21.3	0.001	0.259
BBS	37.5±18.1	48.2±14.5	<0.0001	34.5±13.3	41.4±12.7	0.002	0.010
MI_Lower	71.4±17.3	80.5±15.4	0.001	66.3±11.3	71.1±11.6	0.107	0.047
RMI	7.2±3.2	10.1±3.4	0.000	6.1±2.2	8.6±3.1	<.0001	0.100
Gait speed(m/s)	0.8±0.4	1.0±0.3	0.110	0.5±0.2	0.7±0.3	0.117	0.043

Values are presented as mean±SD. FAC, Functional Ambulation Category; 10MWT, 10 Meter Walk Test; MBI, Modified Barthel Index; BBS, Berg Balance Scale; MI, Motricity Index; RMI, Rivermead Mobility Index. ^*P < 0.05, by the Wilcoxon signed-rank test, for baseline versus after three weeks. ^**P < 0.05, by the Mann–Whitney U test (Wilcoxon signed-rank test), for the difference (three weeks–baseline) of the morning walk group versus control group.

4 Discussion

This study aimed to confirm changes in cortical activation among stroke patients after rehabilitation and to compare the effects of robot-assisted rehabilitation and conventional physiotherapy. Previous investigations of cortical activation during robotic rehabilitation for stroke patients were confined to just one session of rehabilitation. To the best of our knowledge, this was the first study investigating changes in cortical activation before and after multiple sessions of robotic rehabilitation over 3 weeks among stroke patients. We found that walking ability, activities of daily living, balance, and lower limb function were generally improved after 3 weeks robot-assisted rehabilitation. And compared with the conventional treatment group, the Morning Walk group had significantly greater improvements in gait, lower limb function, and balance. Along with improvements in functional outcomes, we also observed corresponding changes in cortical activation, revealed by fNIRS findings. At the initial assessments, the affected cerebral hemisphere had a lower mean cortical activation level than the unaffected hemisphere. After 3 weeks of rehabilitation treatment, cortical activation was more prominent in both hemispheres, but the mean degree of increase was significantly greater in the affected hemisphere.

After a stroke, brain neurophysiology and tissue changes result in changes to brain activity patterns (Luft et al., 2008). According to previous fNIRS studies, brain oxygenation deficiencies accompany stroke-induced brain injury (Holtzer et al., 2011; Leff et al., 2011; Lo et al., 2017; Takeda et al., 2007). Increased activation of the contralateral hemisphere then compensates for cerebral ischemia in the injured hemisphere. Our findings were consistent with these previous observations. In our study, mean brain oxygenation in the affected hemisphere was lower than that of the unaffected side at the beginning of the rehabilitation.

A previous fMRI study reported increases in cortical activation in the motor cortex associated with improvements in upper limb function among stroke patients (Bergfeldt et al., 2015). In another previous fNIRS study of 20 hemiplegic patients, upper limb function evaluated by Fugl–Meyer assessment was significantly improved, and cortical activation was also significantly increased after conventional upper limb rehabilitation (Mihara et al., 2013). In this regard, it can be thought that functional improvement appears as brain activation increases due to brain reorganization, and the results of our study can be considered to be related to this. However, further research is needed to confirm this mechanism.

In fact, in our study, in the individual fNIRS data, cortical activation levels, which were low in the resting state before the start of robotic rehabilitation treatment, rapidly increased at gait initiation, and high cortical activation levels were maintained during the rehabilitation treatment. This suggested that the final recovery of cortical activation occurs by such repetitive stimuli and training. Other investigators (Dawes et al., 2016; Möller et al., 2019) have observed that cortical activation increases more in association with dual concurrent tasks than with single tasks. In contrast with conventional therapy, which simply involves cycling, the Morning Walk intervention involves a visual stimulus projected through a monitor (virtual reality) in front of the patient. Also, with Morning Walk, there are slopes, such as ascending and descending stairs. We suggest that Morning Walk utilization will effectuate the execution a dual task rather than a simple single task.

In our study, of the 15 patients who underwent fNIRS measurements, six had middle cerebral artery (MCA) infarctions, three had basal ganglia infarctions, two had internal capsule infarctions, 3 had brainstem infarctions, and 1 had a posterior inferior cerebellar artery (PICA) infarction. Since brainstem and PICA lesions are not located in the cerebral cortex, they may be thought of as exerting confounding effects in a cortical activation study. However, in the systematic review by Herold et al. (2017), none of the included studies differentiated between cortical lesions, subcortical lesions, and brainstem lesions. We considered possible explanations for why those studies only measured activation of the motor cortex and not other sites. Perhaps it was because the locomotor network, which actually controls walking and standing, is located in the motor cortex. However, lesions located in the motor cortex may have significant effects on cortical activation. Therefore, it would be helpful to conduct larger-scale studies analyzing the effects of specific anatomical sites of injury on cortical activation.

There were some limitations to this study. First, the sample size was small, as there were only 15 patients who were evaluated by fNIRS. This was a pilot study, so a small number of patients were targeted. Future larger-scale studies are warranted. Second, the participants and the investigator who performed the assessment were not blinded, which may limit the study’s validity. Double-blind studies are warranted. Third, we included patients within 1 year of stroke occurrence. Therefore, both acute- and chronic-stage stroke patients were included, which makes the groups heterogeneous. This study was a follow-up to the previously published Morning Walk robot rehabilitation treatment study. Therefore, like the previous Morning Walk study, the target population comprised patients within 1 year of stroke occurrence. However, in our study, in the Morning Walk group, one patient had a stroke 12 months prior and another patient had a stroke 7 months prior; the other 16 patients were in the subacute phase, having experienced strokes within the previous 4 months. The patient who had experienced a stroke 12 months prior did not undergo fNIRS evaluation, so this patient was not included in the cortical activation analysis. So, it seems that there are a few heterogeneous fragments of fNIRS data. Additionally, patients in the control group were all within 6 months of stroke occurrence except for one patient whose stroke onset was 12 months prior. In the future, separate studies on subacute and chronic stroke patients are needed.

5 Conclusion

After robot-assisted rehabilitation using the Morning Walk® for stroke patients, walking ability, lower limb function, and balance were significantly improved relative to the control group. Furthermore, after robotic rehabilitation, cortical activation measured using fNIRS was increased significantly in both hemispheres, and the degree of increased activation was greater in the affected hemisphere than in the unaffected hemisphere. These results could provide some explanations for the mechanisms of recovery among stroke patients after rehabilitation.

Conflict of interest

The authors declare that no competing interests exist.

Funding

The author(s) disclose receipt of the following financial support for the research, authorship, and/or publication of this article: This research is researcher-led clinical Investigator Initiated Trials (IIT) research. The research funding was supported by Curexo, a Korean medical robot company founded in February 2006.

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	Morning Walk group (N = 18)			Control (N = 18)
	baseline	post	p-value^*	baseline	post	p-value^*	p-value^**
FAC	3.5±1.1	4.4±1.2	0.002	2.8±0.8	3.8±1.2	0.001	0.124
10MW (second)	8.7±6.7	5.5±3.1	0.001	9.0±3.0	8.4±3.8	0.077	0.017
K-MBI	69.8±25.8	84.5±24.1	<0.0001	66.4±22.1	78.5±21.3	0.001	0.259
BBS	37.5±18.1	48.2±14.5	<0.0001	34.5±13.3	41.4±12.7	0.002	0.010
MI_Lower	71.4±17.3	80.5±15.4	0.001	66.3±11.3	71.1±11.6	0.107	0.047
RMI	7.2±3.2	10.1±3.4	0.000	6.1±2.2	8.6±3.1	<.0001	0.100
Gait speed(m/s)	0.8±0.4	1.0±0.3	0.110	0.5±0.2	0.7±0.3	0.117	0.043