Effects of lower limb exoskeleton robot-assisted rehabilitation on motor function, activities of daily living, and electromyography in hemiplegic stroke: a randomized controlled trial

Abstract

Background

Post-stroke lower limb dysfunction affects the quality of life. Previous studies have confirmed that lower limb exoskeleton robots can improve the walking ability of stroke patients. This study aims to explore the impact of the UGO220 exoskeleton rehabilitation robot on the motor function and daily living ability of chronic stroke patients and to observe changes in lower limb muscle activity by surface electromyography before and after treatment.

Methods

Sixty stroke patients with hemiplegia were randomly divided into a conventional (CT, n = 30) group or a robot (RT, n = 30) group. Patients in both groups received 60 min of routine physical therapy and occupational therapy. The robot group received 30 min of lower limb exoskeleton robot-assisted gait training per day, whereas the conventional group received 30 min of physical therapist-assisted gait training per day, six days a week, for three consecutive weeks. The primary outcome was evaluated by Fugl-Meyer assessment-lower extremities (FMA-LE), and the secondary outcomes included the modified Barthel index (MBI) score, Berg balance scale (BBS), and lower extremity muscle surface electromyography (sEMG) of the rectus femoris, biceps femoris, anterior tibialis and medial gastrocnemius muscles, including the integrated EMG (iEMG) and root-mean-square (RMS) values.

Results

The robot group had significantly greater improvements in FMA-LE and MBI compared to the conventional group. The electromyography results indicated that in terms of the activation of the anterior tibial muscle, the robot group performed better than the traditional group.

Conclusions

The UGO220 exoskeleton robot training is superior to conventional training in improving Activities of daily living and lower limb motor function. Moreover, it can better promote the improvement of the ankle dorsiflexion function.

Trial registration

ClinicalTrials.gov (ChiCTR2500096316)(2025-01-21).

Introduction

Stroke is the second most common cause of disability worldwide [1]. Owing to the impairment of motor control and sensory function on the affected side caused by injury to the central nervous system of the brain, two-thirds of stroke patients experience walking impairment, which manifests as a change in gait pattern and an increase in walking energy consumption [2], resulting in a significant decline in their activity ability [3], but only 40% of patients can walk independently after appropriate rehabilitation treatment [4–6]. Walking ability is not only an important factor affecting patients’ activity ability and quality of life [7] but also closely related to patients’ cognitive performance and poststroke psychological state [8, 9]. Restoring the ability to walk is the primary rehabilitation goal for most patients.

Studies have shown that providing early, highly repeatable and high-intensity task-oriented training to stroke patients to induce persistent motor learning and neural remodelling [10, 11] can effectively improve the walking function of stroke patients [12, 13]. However, owing to the lack of manpower and time, stroke patients do not receive enough high-dose, task-specific repetitive gait training in the early stage of recovery [14], resulting in approximately 50% of patients not being able to walk independently upon discharge [15].

In recent years, robot-assisted gait training has become a focus of attention in the field of lower limb rehabilitation after stroke [16]. Studies have shown that the combination of robotic exoskeleton training on the basis of conventional treatment can significantly increase the FIM score of patients with acute and subacute stroke (< 3 months) [17], improve patients’ balance and lower limb strength [18], promote the recovery of more effective walking patterns [19], and improve patients’ daily living ability [20]. Research by Kawamoto and Yoshimoto et al. suggested that exoskeleton robot training can improve the walking and balance functions of patients with chronic stroke [21, 22], but Matthias et al. reported that exoskeleton training does not significantly enhance the walking and balance abilities of patients with chronic stroke compared with conventional walking training [23]. Currently, there is limited clinical evidence regarding the efficacy of lower limb exoskeleton rehabilitation for patients with chronic stroke.

In this study, the UGO220 lower limb rehabilitation robot was selected as the intervention tool. This system has a trunk support function, which can effectively reduce the mechanical load during the patient’s standing process and improve the completion degree and stability of the standing task. The equipment has both active assistance and passive guidance operating modes, supporting the input of standardized gait trajectories and also enabling high repeatability and controllability of walking training. Clinical evidence indicates that the 3–6 months after stroke is the key window period for neural function remodeling, during which patients have stronger potential for motor function compensation and reorganization [24]. Therefore, for stroke patients in the chronic stage who do not yet have the ability to walk independently, conducting structured and high-intensity walking intervention may have significant rehabilitation benefits. However, current research on the application of UGO220 in peripheral nerve rehabilitation mostly focuses on the quantitative improvement of gait spatiotemporal parameters (such as step length, walking speed, and gait symmetry), and has not yet constructed an integrated evaluation system covering multiple levels such as motor control, muscle activation patterns, and neural adaptability. Surface electromyography (sEMG), as a non-invasive electrophysiological detection technology, can capture the electrical activity characteristics of superficial skeletal muscles in real time, objectively representing the timing, intensity, and coordination of muscle recruitment under central drive; introducing sEMG into the evaluation of UGO220 intervention effects can help deeply analyze the internal mechanism of lower limb motor function reconstruction from the perspective of neuromuscular coupling.

This study aims to investigate the effects of the UGO220 exoskeleton rehabilitation robot on the motor function and daily living ability of patients in the chronic stage of stroke, and to observe the changes in lower limb muscle activity before and after treatment through sEMG. The main hypothesis is that patients who receive walking training with the exoskeleton rehabilitation robot will have better functional recovery compared to those who receive conventional treatment.

Methods

Trial design and subjects

This was a single-blind randomized controlled clinical trial based on the CONSORT statement. Patients with stroke who received rehabilitation treatment at the Department of Rehabilitation of Zhongda Hospital Southeast University from 10 October 2022 to 30 September 2024 were chosen in this study. Sixty patients were randomly divided into two groups (conventional group and robot group) at a 1:1 ratio via a simple randomization procedure. The protocol was approved by the Committee of Institutional Ethics (No: 2022ZDSYLL181-P01) and registered at the China Clinical Trial Registration Center (ChiCTR2500096316). All subjects signed a informed consent form.

The patient inclusion criteria were as follows: (i) diagnosis of stroke based on head CT or MRI; (ii) patients aged 18–80 years, clear consciousness, no serious cognitive impairment, and ability to complete the corresponding assessment and treatment; (iii) first onset, unilateral hemiplegia, 1–6 months after the disease, FAC score 0–2 points; (iv) main muscle tone of the lower limbs assessed by the modified Ashworth spasm score less than or equal to Grade 2. The exclusion criteria were as follows: (i) unstable fractures of the lower extremities or skin lesions; (ii) severe depression, anxiety or severe mental illness; (iii) functional disorders such as pain and limited movement of the limbs caused by severe skeletal muscle diseases (such as amputation, arthritis, etc.); (iv) serious diseases of the cardiovascular and cerebrovascular system, digestive system or endocrine system; and (v) posterior cerebral circulation lesions.

Sample size

Sample size calculations were performed using G*Power 3.1.9.2 software. The primary outcome measure of this study was the lower extremity FMA score, with the minimal clinically important difference (MCID) being 6 points. According to previous studies, the standard deviation was approximately 7.5 points [25]. Thus, the effect size Cohen’s d = 0.8 was calculated. With a significance level (α) of 0.1, statistical power (1-β) set at 0.80, and a 1:1 participant allocation ratio between groups, calculations indicated a minimum sample size of 28 patients per group. Considering a 20% follow-up dropout rate, it was finally determined that 35 cases would be included in each group, totaling 70 subjects.

Interventions

Patients in both groups participated in regular rehabilitation treatment (60 min/session, 1 session/day, 6 days/week for three consecutive weeks). This treatment included physical therapy (neuromuscular electrical stimulation, transfers, sit to stand, balance training) and occupational therapy (dressing, eating, etc.).

Patients in the robot group further received 30 min of lower limb exoskeleton robot-assisted gait training. This program comprised: the patient is transferred to the robotic device. In a sitting position, the knee joint is aligned with the axis of the exoskeleton. The length of the connecting rod is adjusted to an appropriate length and locked. The patient is then adjusted to a standing position via an electric device, and the gait parameters (including stride length and pattern) are adjusted (Fig. 1).

Fig. 1.

Lower limb exoskeleton rehabilitation robot-assisted training

In the conventional group, 30 min of physical therapist-assisted gait training was added on the basis of regular rehabilitation treatment, including walking forward and backwards, sideways, walking with crutches, etc.

Lower limb exoskeleton rehabilitation robot equipment

The lower limb exoskeleton robot-assisted system used in this study consists of exoskeleton wearables and special crutches (UGO220, RoboCT Co., Ltd., Hangzhou, China) and was designed for overground walking exercise (Fig. 1). It was developed for patients with gait difficulty to perform gait training at a user-controlled speed via a normal gait pattern consisting of the leg angle of a healthy adult while walking. The device holds both the paretic and nonparetic sides of the calf and thigh. The clinician can alter the step length and height on the basis of the patient’s needs and preferences. The step length is adjusted by the programmed hip and knee range of motion. The clinician can supervise the patient in the correct posture and actively walk during treatment. This exoskeleton device lacks a pelvic strap and support. It assists patients in swaying the pelvis naturally according to normal movements of the lower limb.

Assessments

Assessments were conducted before (T1) and after treatment (T2; at the end of the three-week treatment). The assessors included therapists who were independent of the study and did not participate in the treatment of the study.The assessors were blinded to the group assignments.

Primary outcome

The primary outcome measure was the Fugl-Meyer assessment-lower extremities (FMA-LE). which was used to evaluate lower limb motor function. FMA-LE is comprised of 17 items with a total score of 34 points. The score standard was 0 = completely inactive, 1 = only part of the activities can be completed, and 2 = able to perform activities normally. The higher the score is, the better the motor function.

Secondary outcomes

The secondary outcomes included the modified Barthel index (MBI) score, Berg balance scale (BBS), and surface electromyography (s-EMG). The sEMG observation indices include the integrated EMG (iEMG) and root-mean-square (RMS) values of the rectus femoris, biceps femoris, anterior tibialis and lateral gastrocnemius muscles.

MBI can be applied in evaluating the daily life ability of patients, including 10 functions: toilet control, grooming, using the toilet, eating, transfer, bathing, walking on level ground, dressing, and going up and down the stairs. The total score is 100 points. A higher score reflects better independence, with a lower score reflecting stronger dependence. BBS was used to evaluate the balance function. There were 14 assessment items with a total score of 56 points. Each task is rated on a scale from 0 to 4, with 0 indicating that it cannot be completed and 4 indicating that it can be completed independently.

Surface electromyography (sEMG) (SG-1600B, Zhejiang Tiannuo Company, China; sampling frequency: 1000 Hz; common mode rejection ratio: 110 dB; filtering frequency: 10 to 500 Hz) was used to evaluate the recruitment of motor units during the contraction process of the lower limb muscles. The selected muscles included the rectus femoris, biceps femoris, anterior tibialis, and medial gastrocnemius muscles on the affected side. The specific method was as follows: inform the subjects in advance about the test procedure and precautions, and provide movement guidance; prepare the skin (shaving hair, alcohol cotton swab wiping), with the electrode pads parallel to the muscle fibers direction, the rectus femoris electrode placed at the midpoint of the anterior part of the thigh on the outer side, the biceps femoris electrode placed on the posterior outer side of the thigh, the anterior tibialis electrode placed at the upper 1/3 of the anterior part of the lower leg, the medial head of the gastrocnemius electrode placed at the most prominent part of the posterior inner side of the lower leg; the center of the electrodes was 2 cm apart, and the reference electrode was placed at the outer ankle. All four muscles underwent maximum intensity isometric contractions, each lasting 5 s, with a 1-minute rest between each test, and a total of 3 repetitions. The recorded sEMG signals were rectified (such as full-wave rectification) and filtered (such as Butterworth filter to remove noise), and a stable 3-second muscle electrical signal was extracted through MegaWin signal processing, and the RMS and iEMG values of each muscle were exported. RMS refers to the square root of the average of the instantaneous amplitude square of the muscle electrical signal within a certain period of time, and is related to the number of recruited motor units and the synchrony of muscle fiber discharge [26]. iEMG refers to the total area under the curve within a unit of time, reflecting the number of motor units and the discharge amount of each motor unit during muscle contraction [27].

Statistical analysis

Statistical analysis was conducted using SPSS 23.0 software. The Shapiro-Wilk method was employed to test the normality of all parameters. The main and secondary assessment indicators before the intervention (T1) and 3 weeks after the intervention (T2) were compared through 2*2 variance analysis. For count data that did not follow a normal distribution and had unequal variances, the chi-square test was used, with a significance level set at p < 0.05.

Results

Baseline data

In the RT group, 3 patients failed to complete the treatment due to conflicts with other treatment schedules, and another 7 patients were unable to complete the treatment because they moved away. In the CT group, 5 patients were unable to complete the treatment because they were discharged early, and another 5 patients were unable to complete the treatment because they were transferred to other departments.The final 60 patients completed the full trial.The baseline characteristics of all subjects are presented in Table 1. No significant differences were found between the two group in terms of age, sex, course of disease, stroke type or affected side (p > 0.05).

Table 1.

Demographic and clinical characteristics of treated subjects

Baseline Characteristics	Total, N = 60	Robot group (N = 30)	Conventional group (N = 30)		p Value *
Sex, N (%)
Male	38 (63.3%)	19 (63.3%)		19(63.3%)	1.0
Female	22 (36.7%)	11 (36.7%)		11 (36.7%)
Age, Mean (SD)	60.8(10.7)	61.5(9.7)		60.0(11.7)	0.3
Stroke type, N (%)
Ischemic	40 (66.7%)	17(56.7%)		23(76.7%)	0.1
Hemorrhage	20 (33.3%)	13 (43.3%)		7(23.3%)
Stroke side, N (%)
left	31(51.7%)	18(60.0%)		13(43.3%)	0.2
right	29(48.3%)	12(40.0%)		17(56.7%)
Stroke weeks, Mean (SD)	11.5 (6.7)	11.8(6.7)		11.2(6.7)	1.0
Height(cm)	167.7 (7.5)	167.0 (6.8)		168.3 (8.1)	0.1
Weight(kg)	66.5(9.5)	64.9(9.8)		68.1(9.1)	0.6

SD standard deviation

*Chi-square test for categorical data and independent-samples t test for continuous variables

Outcome measures

The time main effect was significant in all three indicators (FMA-LE, MBI, and BBS) (p < 0.001), indicating that both robot-assisted training and conventional rehabilitation training can effectively improve the lower limb motor function, balance ability, and activities of daily living of stroke patients. In the two indicators of FMA-LE (p < 0.001, η²p = 0.069) and MBI (p < 0.001, η²p = 0.080), the main effect between groups was significant, and the improvement in the robot group was better than that in the conventional group. There was no significant difference in BBS between groups (p > 0.05). Moreover, the interaction effects were not significant (p > 0.05) (Table 2).

Table 2.

The changes of outcome measures between pre- and post-training

	Robot group(n = 30)		Conventional group(n = 30)		Between groups		Interaction effects
	Pre	Post	Pre	Post	F	η²p	F	η²p
MBI	45.13 ± 17.01	69.43 ± 18.53***	37.57 ± 20.93	54.90 ± 19.48***	10.104***	0.080	1.004	0.009
BBS	16.50 ± 12.08	32.20 ± 13.83***	21.03 ± 15.91	29.97 ± 14.94***	0.195	0.002	1.688	0.014
FMA-LE	17.80 ± 6.73	25.80 ± 6.59***	16.00 ± 7.93	19.97 ± 7.17***	8.069***	0.069	2.403	0.020

Data presented as Mean ± SD

FMA-LE Fugl-Meyer assessment-lower extremities, MBI modified Barthel index (MBI) score, BBS Berg balance scale (BBS)

F values and η²p derived from 2 × 2 mixed ANOVA (within factor: time; between factor: group).*** P<0.05 by 2*2 variance analysis between pre- and post-training outcome measures

The electromyographic results indicated that the time main effect was significant in all the RMS and iEMG indicators of the muscles (p < 0.001), suggesting that both robot-assisted training and conventional rehabilitation training could effectively enhance the neural activation level and functional ability of the lower limb muscles in stroke patients. At the same time, the main effect of the group difference in iEMG of the anterior tibialis muscle was significant (F = 4.378, p < 0.05, η²p = 0.036), indicating that the robot group had a better overall functional ability in the dorsiflexion muscle group of the foot than the conventional group. Apart from the iEMG of the anterior tibialis muscle, the main effects of the group differences in RMS and iEMG of other muscles were not significant (Table 3).

Table 3.

The changes of electromyography between pre- and post-training

	Robot group(n = 30)		Conventional group(n = 30)		Between groups		Interaction effects
	Pre	Post	Pre	Post	F	η²p	F	η²p
RMS_rectus femoris	57.45 ± 23.91	94.43 ± 43.84***	60.29 ± 26.14	79.05 ± 39.07***	1.003	0.009	2.119	0.018
RMS_biceps femoris	24.62 ± 13.77	47.72 ± 26.34***	28.44 ± 19.48	41.36 ± 29.03***	0.092	0.001	1.474	0.013
RMS_tibialis anterior	43.07 ± 19.00	66.79 ± 29.70***	45.43 ± 19.98	62.86 ± 35.74***	0.026	0.000	0.407	0.003
RMS_gastrocnemius	19.83 ± 6.98	30.04 ± 8.98***	20.21 ± 9.89	28.53 ± 2.07***	0.104	0.001	0.288	0.002
iEMG_rectus femoris	61.41 ± 35.04	95.96 ± 44.37***	60.98 ± 28.60	81.50 ± 42.65***	0.005	0.000	0.000	0.000
iEMG_biceps femoris	27.14 ± 16.04	41.81 ± 15.84***	26.49 ± 13.13	34.27 ± 14.19***	2.284	0.019	1.618	0.014
iEMG_tibialis anterior	53.59 ± 23.72	68.67 ± 23.94***	52.53 ± 21.11	69.50 ± 25.50***	4.378*	0.036	3.367	0.028
iEMG_gastrocnemius	15.52 ± 5.72	22.86 ± 5.61***	15.80 ± 5.14	21.16 ± 5.96***	0.477	0.004	0.936	0.008

Data presented as Mean ± SD

RMS root mean square, iEMG integrated electromyography

F values and η²p derived from 2 × 2 mixed ANOVA (within factor: time; between factor: group). *** P<0.05 by 2*2 variance analysis between pre- and post-training electromyography; *P<0.05

Discussion

In this pilot study, we combined surface electromyography assessment with a movement assessment system to evaluate the differences in the effects of robot-assisted rehabilitation training and conventional training after a three-week treatment period. The results showed that both groups of patients improved their lower limb motor function after treatment. Among them, the robot group demonstrated better improvement in lower limb motor function, daily living ability, and anterior tibialis muscle activation. These results indicate that exoskeleton robot-assisted walking training can improve the lower limb function of stroke patients and promote changes in neural plasticity.

This study found that the FMA-LE score of the robot group increased from(17.80 ± 6.73)points to༈25.80 ± 6.59༉(an increase of 8.00 points), while that of the conventional group rose from ༈16.00 ± 7.93༉to༈19.97 ± 7.17༉(an increase of 3.97 points). The main effect between the groups was significant (F = 8.069, p < 0.001, η²p = 0.069). This result is consistent with previous studies [28, 29]. The advantages of robot-assisted training may stem from the following mechanisms: First, the robot can provide high-intensity, repetitive, task-oriented exercise training, which helps to promote neural plasticity; second, robot-assisted training can reduce the occurrence of abnormal movement patterns and guide patients to adopt more normal movement strategies; third, the precise force feedback and visual feedback provided by the robot can enhance patients’ movement perception and motor learning ability [30]. Additionally, the effect size of FMA-LE in this study (η²p = 0.069) was small, suggesting that the training method explains the variability of lower limb motor function to a limited extent. This may be due to the fact that the recovery of lower limb function in stroke patients is influenced by multiple factors, including the location of the injury, the severity of the injury, the duration of the disease, and rehabilitation compliance, and future research should further control these confounding factors.

Both groups showed significant improvements in the Berg score, but the main effect between the groups was not significant (F = 0.195, p > 0.05). This indicates that the two training methods have similar effects on improving balance ability, and the robot-assisted training did not show any additional advantages. Possible reasons for this result include: First, conventional physical therapy usually includes targeted balance training (such as standing, center of gravity shift, single-leg support, etc.), and these training methods are more efficient in improving balance function; Second, the Berg scale mainly assesses static and dynamic balance control abilities, while the advantages of robot training may be more prominent in dimensions such as gait quality and walking endurance, which are not fully captured by the Berg scale.

The MBI score analysis showed that both groups had significant improvements, and the robot group was significantly better than the conventional group (F = 10.104, p < 0.001, η²p = 0.080). The improvement in MBI could be partly attributed to the improvement in lower limb motor function and walking ability. When patients could more effectively control their lower limbs and achieve more stable standing and walking, their independence in daily activities such as dressing, using the toilet, transferring, and walking naturally increased. Robot training may have indirectly promoted a greater improvement in MBI by improving the FMA-LE score (an increase of 8 points). Additionally, the visual feedback and task-oriented training provided during the robot training process may have enhanced the patients’ self-efficacy and activity participation, which are also important psychosocial factors for the improvement of MBI [31]. It is noteworthy that the baseline value of MBI in the conventional group (37.57 ± 20.93) had a large standard deviation, suggesting that the baseline heterogeneity of the patients’ daily living activity ability in this group was relatively high, which may affect the accuracy of the comparison between the groups.

The study found that both robot-assisted training and traditional rehabilitation training could significantly improve the RMS and iEMG of stroke patients (time main effect was significant, p < 0.001). This finding is consistent with previous research results and confirms the promoting effect of task-oriented repetitive training on the neural plasticity after stroke [32]. Although the absolute increase in RMS of each muscle in the robot group was greater than that in the traditional group, especially the biceps femoris (36.98 vs. 18.76) and the biceps femoral (23.10 vs. 12.92), the group differences did not reach statistical significance. This result may be related to the following factors: ①The individual muscle signal differences are relatively large [33, 34]; ②Regular rehabilitation training can also effectively activate the lower limb muscles, both intervention measures reached the “effective threshold”, and the group differences may have been compressed; ③The advantage of robot training may be reflected in specific stages of the gait cycle (such as the swing phase), and the RMS measurement in this study may not have fully captured this feature. It is worth noting that the main effect of iEMG of the tibialis anterior muscle between the two groups was significant (F = 4.378, p < 0.05,η²p = 0.036), and the robot group was significantly higher than the traditional group. This may enhance the patient’s more active participation in the dorsiflexion movement through enhanced sensory feedback (visual, auditory, and tactile), thereby more effectively increasing the total work output of the tibialis anterior muscle. iEMG reflects the total discharge amount over a period of time, and compared with RMS, it can better capture the cumulative effect [35], which may be the reason for the existence of group differences in this indicator. The interaction effect of RMS and iEMG of all muscles was not significant (p > 0.05), indicating that the advantages of these two training methods lie in the overall improvement amplitude rather than the trajectory differences over time.

This study has several limitations. Firstly, the intervention period was only 3 weeks, which is a short-term observation and cannot determine the efficacy of the intervention measures over a longer period (such as 8–12 weeks or more). Secondly, the study did not set up a follow-up period after the intervention (such as 1 month or 3 months), so it is impossible to evaluate the long-term effect of the intervention or the sustained improvement in function. Thirdly, the duration of the patients’ illness was quite long (1–6 months after a stroke), and the differences in neural plasticity at different stages might interfere with the estimation of the effect and also limits the ability to conduct stable subgroup analyses for patients in different disease course stages.

Conclusion

Our findings indicate that for stroke patients, the use of RT can better enhance the FMA-LE and MBI scores, and increase the total amount of dorsiflexion work (iEMG) in the foot. However, its effect in improving balance is comparable to that of conventional treatment.

Authors’ contributions

CT, YZhang, TZ, and HW were involved in the conception and design of the study; LZ, CR, YZhu, ZG, YC and YW performed the study and collected materials; RY and PS analysed the results; CT and TZ wrote the manuscript; and WC and HW helped coordinate the study and reviewed the manuscript. All the authors contributed to the article and approved the final manuscript.

Funding

This study was supported by grants from Key Project of Jiangsu Province’s Key Research and Development Program (No.BE2023023-4); Key Project of Jiangsu Province’s Key Research and Development Program(BE2023034); Jiangsu Provincial Medical Key Discipline Cultivation Unit (JSDW202202, ZDXYS202210) and Horizontal Project of Hangzhou Chengtian Technology Development Co., LTD fund (H2021010103).

Data availability

The datasets generated and analysed during the current study are available upon request.

Declarations

Ethics approval and consent to participate

This study involving human participants was approved by the Ethics Committee of Zhongda Hospital Southeast University (No.2022ZDSYLL181-P01), and it also adhered to the Declaration of Helsinki. All participants provided written informed consent prior to any test or assessment.

Consent for publication

Participants gave written informed consent for their personal or clinical details along with any identifying images to be published in this study.

Competing interests

The authors declare no competing interests.