Effects of high-intensity multimodal functional training on motor and cognitive functions in people with multiple sclerosis: A study protocol of a pilot randomized controlled trial

Abstract

Objective

Multiple sclerosis (MS) is a chronic neurological condition causing motor and cognitive impairments. Evidence indicates that multimodal rehabilitation, including high-intensity interval training (HIIT), balance, and strength exercises can improve balance, walking ability, and cognition while reducing fatigue in People with MS (PwMS). This study aims to evaluate the effects of high-intensity multimodal functional training on improvements in balance, walking, and cognitive function and fatigue reduction in PwMS.

Materials and Methods

This pilot randomized controlled, assessor-blinded, multicenter trial will include PwMS with an Expanded Disability Status Scale score ≥ 2 and ≤ 5.5 points. Participants will be randomized to an experimental group receiving high-intensity multimodal training (aerobic HIIT, balance, and strength exercises) or a control group (conventional rehabilitation). The intervention will consist of 16 sessions over 8 weeks. Participants will undergo an extensive evaluation at baseline (T0), post-intervention (T1), and after 2 months at the follow-up (T2). The assessment will include a fatiguing walking test, standing balance evaluation, and cognitive performance tests. Primary outcomes will focus on walking velocity during a fatiguing walking test, while secondary outcomes will evaluate balance, fatigue, and cognitive functions using wearable sensors and clinical scales.

Results

Expected results will be a higher effect on walking (primary outcome), balance, fatigue, and cognition (secondary outcomes) for the experimental group (high-intensity multimodal functional training) compared to the control group (conventional rehabilitation).

Conclusion

This study introduces a time-efficient, high-intensity multimodal rehabilitation protocol targeting motor and non-motor symptoms in PwMS. By promoting neuroplasticity, the intervention could enhance independence, quality of life, and inform future rehabilitation strategies for MS.

Keywords

Neurological rehabilitation multiple sclerosis high-Intensity interval training wearable inertial sensors circuit-based exercise

Introduction

Multiple sclerosis (MS) is a chronic neurological condition characterized by a broad range of motor and cognitive impairments, significantly impacting individuals’ quality of life.^1,2 Among a great variety of symptoms, 80% of People with MS (PwMS) reported fatigue as the most limiting one.³ In addition to fatigue, walking and balance deficits are also common in this population. Seventy per cent of PwMS consider walking and balance problems to be highly challenging deficits impacting daily life activities.^4,5

Managing fatigue and improving mobility have become a primary goal in rehabilitation.⁶ In this context, high-intensity interval training (HIIT) has emerged to be highly efficient compared to continuous moderate-intensity training both for reducing fatigue and improving fitness level.^7,8 Indeed, by maximizing effort during brief intervals, HIIT enables participants to achieve improvements in physical performance within a shorter time frame, and it can be beneficial for managing fatigue in PwMS.⁷

Moreover^4,5, addressing walking and balance deficits is equally critical and several studies have demonstrated the effectiveness of rehabilitation programmes emphasizing the importance of targeting specific interventions to achieve optimal outcomes. Gunn et al.⁹ showed that specific walking, balance, and functional training interventions had the largest effects on balance outcomes compared to any other intervention type. Also, it has been reported that a progressive strength training can improve walking functional capacity in moderately impaired PwMS.¹⁰ Additionally, a recent study by Jonsdottir et al. found that a multimodal treadmill training was highly effective in enhancing balance, walking endurance, and mobility in this population.¹¹

Thus, combining an aerobic HIIT training with balance and strength training within a multimodal programme appears to be effective in managing balance and walking deficits, as supported by a recent review.¹² These data are in line with existing literature reporting that mixed treatments are effective in improving balance in PwMS.^13–15 Concerning the mechanisms of action, there is evidence to suggest that mixed treatments based on variable tasks are more effective than constant practice in achieving real functional gains.¹⁶ According to motor learning theory, identifiable and functional tasks and a higher number of repetitions can lead subjects to achieve their goals and gain new skills.¹⁷ In this context, balance and strength exercises were chosen to specifically target motor control and stability, addressing common symptoms such as impaired coordination and muscle weakness.^18,19

Fatigue, balance, and walking deficits often coexist with cognitive impairments, such as difficulties in working memory and information processing.²⁰ According to Mura et al.²¹ balance and cognitive exercises are a highly adaptable tool for rehabilitation of both cognitive and motor functions in adult populations with neurological disabilities, such as MS.²¹This is confirmed in a recent study by Ozkul et al.²² reporting that combined exercise training has beneficial effects on different cognitive functions in PwMS.

Taken together, these findings emphasize the potential of comprehensive, multimodal rehabilitation strategies to simultaneously address multiple symptoms of MS. Despite the proven benefits of rehabilitation for reducing fatigue, and improving balance and walking functions, no studies integrated treadmill-based HIIT with multimodal balance and functional strength training into a single session aimed at addressing both physical and cognitive outcomes.

Therefore, the aim of this pilot randomized controlled study will be to investigate the effects of high-intensity multimodal functional training on reducing fatigue as well as improving balance, walking, and cognitive functions in PwMS.

Experimental hypotheses

High-intensity multimodal functional training can reduce fatigue, walking and balance dysfunctions, and cognitive impairments.

Methods

Participants, interventions, and outcomes

This pilot study “Effects of high-intensity multimodal Functional trAining on motor and cognitive functionS in people with mulTiple sclerosis” (FAST) has been designed according to SPIRIT 2013 guidelines.²³ This study will be conducted in line with the Declaration of Helsinki, received approval by the ethical committees of the IRCCS Fondazione Don Carlo Gnocchi (Milan; number id: 04_29/03/2023) and the Comitato Etico Territoriale – Liguria (Genoa; number id: 559/2023 - DB id 13567), and it was registered to clinicaltrial.gov with ID number: NCT06219304.

Study design and setting

FAST is a pilot, randomized, controlled, assessor-blinded, and multicentre trial with two parallel arms. The trial work plan is shown in Figure 1.

Figure 1.

FAST work plan.

The study will be conducted in four Italian centres, where all data will be collected: IRCCS Fondazione Don Carlo Gnocchi ONLUS, Santa Maria Nascente, Milan; Neurology Unit Galliera Hospital, Genoa; AISM Rehabilitation Service of Liguria and AISM Rehabilitation Service of Como. Prior to the study initiation, patients will be asked to sign informed consent.

Eligibility criteria

Patients eligible for the trial will meet the following inclusion criteria: (i) Subjects > 18 years old; (ii) Diagnosis of MS (McDonald criteria)²⁴; (iii) Stable disease course without worsening more than one Expanded Disability Status Scale (EDSS) point over the last 3 months; (iv) EDSS ≥ 2 points and ≤ 5.5 points; (v) Able to maintain upright posture without any assistance for 30 s; (vi) Releasing a written informed consent.

Exclusion criteria will be (i) MS relapse within the previous 3 months; (ii) Unable to comprehend the aims of the study and to follow test instructions; (iii) Diagnosis of major depression (DSM-5)²⁵; (iv) Severe joint and/or bone disorders interfering with balance and gait (based upon clinical judgment); (v) Other concomitant cardiovascular and/or neurological disease; (vi) Subjects already performing or having received aerobic or walking training 3 months before the beginning of the study.

Intervention

The assessors will be blind to the randomization list and group assignment. The subjects enrolled in the study will be randomized into two groups (the experimental group and the control group) using a random sequence generated by a software programme. All subjects will be treated for at least 16 sessions by an experienced physical therapist and treatments will be provided by the participating units.

The experimental group (high-intensity multimodal functional training) will perform 40-min high-intensity rehabilitation sessions, conducted 2–3 times per week. Each session will include 20 min of aerobic HIIT training on a treadmill, 10 min of static and dynamic balance exercises, and 10 min of functional strength training, as depicted in Figure 2 and detailed in Supplementary Table 1. No breaks are planned between exercises, except for hydration and transitions. All exercises will be tailored by an experienced physical therapist to match the subject's level of impairment and individual needs.

Figure 2.

Rehabilitation contents of experimental group (high-intensity multimodal functional training). RPE: rate of perceived exertion; EO: eyes open; EC: eyes closed.

In accordance with literature,²⁶ the aerobic HIIT will be carried out on a treadmill without body weight support, but participants will be allowed to use the handrails if needed. It will consist of three bursts of 4 minutes of high-intensity exercise followed by a working rest of 2 minutes. Preferred walking speed will be used for a 2-minute warm-up session; then, walking speed and incline belt will be increased to reach a fatigue measured by the Rate of Perceived Exertion (RPE) scale of 15 points during the burst sessions. Right after the end of the aerobic HIIT participants will perform 10 min of balance exercises and 10 min of functional strength training. The physical therapist will tailor exercises according to the subject's characteristics.

The control group will perform 40 min of conventional rehabilitation sessions three times a week, with the aim of reducing limitations in body function and activity levels. The conventional rehabilitation will be performed with a physiotherapist:patient ratio of 1:1 and should not contain any HIIT parts on treadmill. We will assess adherence to the protocol by monitoring the number of sessions completed, and good adherence is defined as attending at least 80% of treatment sessions. To improve adherence to the treatment, the physical therapists will monitor every training to check for any problem interfering with the protocol.

Clinical and instrumented assessment

Participants will undergo an extensive evaluation at baseline (T0), post-intervention (T1), and after 2 months at the follow-up (T2) (Figure 4). The assessment will include a fatiguing walking test, standing balance evaluation, and cognitive performance tests. Additionally, questionnaires will be used to evaluate perceived fatigue and self-perception of balance and walking ability during daily activities.

Figure 3.

(a) Inertial measurement units position during fatiguing walking test. (b) Inertial measurement units position during static balance tests.

Figure 4.

SPIRIT schedule of enrolment, interventions and assessments in a parallel arm study design. T0: baseline (pre-intervention phase); T1: post-treatment assessment; T2: follow-up assessment (2 months after the end of the treatment). EDSS: expanded disability status scale; BDI-II: back depression inventory; MSWS_12: twelve-item multiple sclerosis walking scale; mDGI: modified dynamic gait index; ABC: activities-specific balance confidence scale; BICAMS: brief international cognitive assessment for multiple scleorsis; MFIS: modified fatigue impact scale; Δvel: velocity at the beginning of the test – velocity at the end of the test [m/s].

In the fatiguing walking test, subjects will be asked to walk overground with comfort velocity plus 15%²⁷ until they will experience complete exhaustion (RPE, ≥ 17 points) according to Borg scale ranging from 6 (not exhausted at all) to 20 points (unable to continue the test).²⁸

To ensure standardization, the test will be administered using standardized sentences. During the test subjects will wear three wireless Inertial Measurement Units (IMUs) (MTx, XSens, Enschede, Netherlands) attached through elastic belts on lower trunk (L5 level) and 1 cm above lateral malleoli (Figure 3A and B). Each IMU contains a tri-axial units accelerometer (±160 m/s² range), a tri-axial gyroscope (±1200 deg/s range), and a tri-axial magnetometer (±1.5 Gauss range). Data will be sampled at a frequency of 75 Hz and transferred wireless to a laptop in real time for processing.

Outcome measures

Primary outcome

The primary outcome measure will be the difference in walking velocity during the fatiguing walking test (velocity at the beginning of the test - velocity at the end of the test, [m/s]). We will measure the velocity at the beginning of the test as the mean velocity of the first minute and the velocity at the end of the test as the mean of the last minute performed during the test.

We chose walking velocity because it is a simple, valid and widely accepted outcome to assess gait and is associated to variables related to energy expenditure, dynamic balance, quality of life and participation.

Secondary outcomes

Instrumented variables

Regarding the instrumented assessment of gait and balance, we will consider IMU-derived metrics chosen as representative of different domains of walking and upright standing.^29,30

In specific for gait, we will analyse gait quality metrics during the entire fatiguing walking test (Table 1).

Table 1.

Description of the IMU-based metrics computed during the fatiguing walking test.

Metric	Description
Gait regularity (unitless)	Quantified by the second peak of the normalized autocorrelation function computed from the trunk acceleration modulus. Increasing values, from 0 to 1, indicate higher stride regularity.³¹
Gait symmetry (%)	Quantified through the improved harmonic ratio.³² Increasing values, from 0 to 100, indicate more symmetrical gait. Gait symmetry will be computed separately on the three components of trunk acceleration (ML, AP, and VT), but only the ML one was used in the subsequent multiple regression analysis.
Gait instability (unitless)	Quantified through the short-term Lyapunov exponent (sLyE) computed on trunk accelerations over the duration of one step.³³ The sLyE reflects the capability of the locomotor system to cope with small perturbations naturally occurring during gait (e.g., external mechanical disturbances or internal motor control errors). Higher values of sLyE indicate a lower ability of the motor system to manage small perturbations, thus reflecting higher gait instability.
Trunk sway (unitless)	Quantified through the root mean square (RMS) value of AP, ML and VT trunk acceleration normalized with respect to the RMS of the trunk acceleration modulus.³⁴

ML: medio-lateral; AP: antero-posterior; VT: vertical; IMU: Inertial Measurement Units.

To objectively measure static balance subjects will be asked to maintain the upright posture wearing IMUs. The balance assessment will consist of 1-min quiet standing trials with open and closed eyes on a firm surface, and 30-s quiet standing trials with open and closed eyes on a foam.

In specific for balance, we will analyse the wearable-sensor-based variables described in Table 2.

Table 2.

Description of the IMU-based metrics computed during the static balance tests.

Metric	Description
Sway amplitude (m/s²)	Root mean square of AP (ML) acceleration signal.³⁵
Sample entropy (unitless)	Sample entropy (SaEn) will be computed on the standardized AP (ML) acceleration obtained by subtracting the mean and dividing by the standard deviation of the signal.²⁹ Low entropy reflects less adaptable and more stereotyped movements, requiring greater conscious control. Higher values of SaEn are thought to indicate greater variability of postural responses, affording a greater repertoire of motor strategies to handle perturbations. On the contrary, a lower value may indicate a restriction to more stereotyped motor strategies, which can limit the ability to deal with perturbations occurring in daily.³⁶

Metric

Description

Sway amplitude (m/s²)

Root mean square of AP (ML) acceleration signal.³⁵

Sample entropy (unitless)

Sample entropy (SaEn) will be computed on the standardized AP (ML) acceleration obtained by subtracting the mean and dividing by the standard deviation of the signal.²⁹ Low entropy reflects less adaptable and more stereotyped movements, requiring greater conscious control. Higher values of SaEn are thought to indicate greater variability of postural responses, affording a greater repertoire of motor strategies to handle perturbations. On the contrary, a lower value may indicate a restriction to more stereotyped motor strategies, which can limit the ability to deal with perturbations occurring in daily.³⁶

ML: medio-lateral; AP: antero-posterior; VT: vertical; IMU: Inertial Measurement Units.

These variables are respectively descriptors of sway intensity and sway complexity, that represent independent aspects of balance.³⁷ In particular, sway intensity means the amplitude and velocity of trunk sway in both ML and AP directions and higher values demonstrate difficulty in maintaining a stable position. Conversely, low sway complexity reflects the loss of complexity and adaptability of the balance control system due to the reduction and/or impairments of its structural components and their interaction.³⁸ So, lower values of sway complexity are indicative of an inefficient balance control, possibly requiring an increased attentional investment.

Other wearable-sensor-based sub-components regarding both walking and balance are described in Supplementary Table 2.

Clinical variables

All clinical scales used for the assessment are shown in Table 3.

Table 3.

Assessment clinical scales.

Domain	Clinical scale(s)
Fatigue	Modified Fatigue Impact Scale (MFIS)
Walking	Twelve-Item Multiple Sclerosis Walking Scale (MSWS_12)
Balance	- Modified Dynamic Gait Index scale (mDGI) - Activities-specific Balance Confidence scale (ABC)
Cognitive functions	Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS)

ABC: activities-specific balance confidence scale.

Regarding fatigue, the Modified Fatigue Impact Scale will be used to assess the perceived impact of fatigue on the physical, cognitive and psychosocial components. It is a self-administered scale that specifically concerns the personal perception of fatigue. The 21-item scale is an assessment of the impact of fatigue on daily life over the past 4 weeks. The score ranges from a minimum of 0 (never) to a maximum of 4 points (almost always). The physical component consists of nine items, while the psychosocial component is assessed by two items, and the cognitive component by 10 items for a maximum total of 84 points. A score of 38 or higher correlates with a state of fatigue due to MS.²⁸

In specific to walking, Twelve-Item Multiple Sclerosis Walking Scale (MSWS_12) will assess the perceived impact of MS on walking in the last 2 weeks. This self-administered scale consists of 12 items scored from 1 (not at all) to 5 points (extremely). Higher scores indicate a great impact of MS on walking.³⁹

Regarding balance, modified dynamic gait index scale (mDGI) will be used to assess the ability to maintain dynamic balance while responding to different task demands, through various dynamic conditions. This performance test evaluates gait pattern, execution time, and level of assistance.⁴⁰ The total mDGI score ranges from 0 (low dynamic balance function) to 64 (optimal dynamic balance function). In particular, a score between 29 to 48 points indicates a medium fall risk and below 29 points indicates that a significant balance deficit is present.⁴¹ Furthermore, the minimal clinically important difference is 7 points on the total score.⁴²

The Activities-specific Balance Confidence Scale (ABC) will be used to assess balance confidence in performing different activities of daily living (ADLs). It is a self-administered scale consisting of 16 items scored from 0 (not at all confident) to 100 (extremely confident). A score less than 67% indicates a high risk of fall.⁴³

Cognitive function will be evaluated using the BICAMS battery,⁴⁴ a validated measure for cognitive assessment in MS. This battery includes three tests assessing the cognitive domains most commonly affected in MS, the Symbol Digit Modalities Test for information processing speed, the California Verbal Learning Test-2, for verbal learning, and the Brief Visuospatial Memory Test-Revised for visuospatial learning.

Descriptive variables

Demographic characteristics (age, sex, body mass index) and clinical disease-related variables, such as MS type, disease duration, EDSS score, as well as presence of depressive symptoms (Beck Depression Inventory⁴⁵) will be used to describe the sample.

Sample size

Given the exploratory nature of the randomized controlled trial, we did not calculate an a-priori sample size. However, the literature recommends a minimum of 12 subjects per group for pilot studies.⁴⁶ Therefore, assuming a dropout rate of 20%, we will recruit 30 subjects, and the results of this pilot study will be used to calculate the number of subjects to be recruited for a future larger randomized controlled trial.

Data collection and management

Data will be collected by blinded examiners/assessors at each time-point of evaluation (T0, T1, T2). A schedule of enrolment, interventions, and assessments is reported in Figure 4.

Statistical analyses

Analysis will be conducted according to the following predefined statistical analysis plan.

Statistical analyses will be performed using dedicated software (MedCalc 20.111, Jamovi 2.2 https://www.jamovi.org). All the variables will be expressed in terms of appropriate descriptive statistics (e.g. frequencies, percentages, means, medians, standard deviations) and summary statistics will be graphically expressed when appropriate. We will code data to maintain group allocation blinding during analysis, and statistical analysis will be independently replicated by one of the investigators. The α level will be set to 5%. According to intention-to-treat procedure participants who will be randomly assigned to a group will be included in the analysis irrespective of their level of compliance with their group assignment. Outcome measures will be analysed with and without imputation and adjustment for descriptive characteristics. The outcome measures will be imputed using the multivariate imputation by chained equations approach under the assumption of missing at random to create 10 imputation datasets under the joint multivariate normal imputation. We will model outcome measures with linear mixed models to compare the change in scores over time at post and follow-up assessment between the two groups. Time, Group, and Time*Group interaction will be the fixed effects while ID will be the random intercept. When the residuals of the models deviated from normality, we used a 1000 times bootstrap for each imputation dataset to obtain confidence intervals.

Sensitivity analysis will be also performed considering subgroups and age, gender and baseline clinical outcomes as covariates in the model.

Discussion

This protocol proposes a high-intensity multimodal rehabilitation approach that combines aerobic HIIT, balance, and strength training into a single and intensive intervention. Integrating these components into one protocol could address the complex needs of PwMS by targeting multiple symptoms within each session. In fact, rehabilitation approaches including a variety of functional tasks have shown to be promising in improving mobility, balance and general fitness in PwMS, as well as providing a time-efficient exercise programme for this population.⁴⁷

Delivering an aerobic HIIT is consistent with recent evidence favouring intensity as a factor in reducing fatigue.⁷ A recent study investigating the effect of aerobic HIIT versus moderate endurance training in PwMS revealed a significant decrease of fatigue in favour of HIIT group, in particular in subjects with elevated baseline fatigue.⁴⁸ This finding confirms previous results demonstrating that subjects with fatigue benefit from aerobic exercise but in a shorter session duration allowing more time to incorporate mobility, balance, or strength training.^49,50 Evidence shows that HIIT can significantly improve both motor and non-motor symptoms in people with neurological conditions. In this context, the benefits of HIIT may include improvements in motor control, physical and cognitive function, and stimulation of neurogenesis and neuro-repair, with a greater dose response than moderate-intensity exercise.^49,51

The balance phase, consisting of task-oriented and progressively challenging exercises, may contribute to improved dynamic stability and gait adaptability.⁵² Task-oriented balance training is grounded in motor relearning principles to both improve static and dynamic balance by promoting brain plasticity.^53,54 Thus, we expect that participants may experience greater functional gains and an increase in physical confidence, helping them to perform ADLs easily and safely, thereby increasing their independence and participation.⁵⁵

Beside aerobic HIIT and task-oriented balance training, functional strengthening exercises are emerging as a popular and effective modality to improve muscle function, functional capacity, and performance.⁵⁶ Two reviews found the potential benefits of strength training for PwMS highlighting its positive effects in improving functional capacity, balance, and reducing fatigue impacting overall health and the quality of life.^57,58

The innovative aspect of this protocol is the integration of balance and strength exercises immediately following the HIIT aerobic phase under fatiguing conditions. This sequence is designed to promote fatigue-specific adaptations that may lead to greater training gains when participants are assessed in a fatigued state (e.g. balance assessment with IMUs after a fatiguing walking test). Furthermore, this combination may improve participation outcomes, such as self-perceived balance during ADLs as measured by the ABC scale, which reflects the real-world challenges that PwMS often face due to fatigue. While a recent study in healthy people found no additional benefits of balance training under fatigue compared to non-fatigued conditions, it highlights the need for further investigation in PwMS, where fatigue plays a more prominent role in daily life.⁵⁹ By exploring this approach, we aim to address gaps in the current literature and assess whether this multimodal protocol can provide specific adaptations that enhance independence, confidence, and participation.

Taken together, aerobic high-intensity, balance, and strength training target multiple domains simultaneously. The multimodal nature of this intervention aims at maximizing improvements in physical, functional, and neurological outcomes exploiting the benefits of each training modality. Indeed, aerobic HIIT contributes to fatigue management, while task-oriented balance exercises improve dynamic stability and confidence in performing ADLs, and strength training also supports muscle function and gait providing a comprehensive rehabilitation programme tailored to the needs of PwMS. In addition, multimodal training may improve cognitive functions as supported by recent evidence finding possible beneficial effect of exercise on cognitive domains.^60–62 Moreover, a recent review on healthy population found that HIIT, compared with moderate-intensity continuous exercise, provides significant cognitive benefits, particularly in improving executive function. Indeed, HIIT appears to better support neuroplasticity, which is the brain's ability to reorganize itself by forming new neural connections. Exercise, particularly high-intensity training, plays a crucial role in promoting this process by enhancing cerebral blood flow, leading to improvements in cognitive flexibility and reaction times.⁶³

Particular strengths of the current trial include the innovative design of the intervention, which integrates aerobic HIIT, balance, and strength exercises into a single, multimodal session targeting both motor and cognitive impairments. The study is further strengthened by its randomized controlled design, assessor blinding, and the use of both clinical and instrumented outcome measures to provide a comprehensive evaluation. Limitations include the potential insufficiency of the strength training component, which may not meet the minimal dose required to induce significant muscular adaptations. Additionally, the small sample size may limit the statistical power and generalizability of the findings.

Conclusion

This pilot study could provide valuable evidence on the impact of multimodal, high-intensity training as an integrated approach to MS rehabilitation and could guide future interventions targeting both motor and non-motor symptoms on a larger cohort of people with MS.

Supplemental Material

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Supplemental material, sj-docx-1-dhj-10.1177_20552076251346694 for Effects of high-intensity multimodal functional training on motor and cognitive functions in people with multiple sclerosis: A study protocol of a pilot randomized controlled trial by Rebecca Cardini, Rita Bertoni, Ilaria Carpinella, Chiara Pegorini, Andrea Tacchino, Erica Grange, Valentina Guidotti, Giampaolo Brichetto, Claudio Solaro, Tommaso Budassi, Tatiana Lanfranco, Marco Rovaris, Davide Cattaneo and Elisa Gervasoni in DIGITAL HEALTH

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Supplemental material, sj-docx-2-dhj-10.1177_20552076251346694 for Effects of high-intensity multimodal functional training on motor and cognitive functions in people with multiple sclerosis: A study protocol of a pilot randomized controlled trial by Rebecca Cardini, Rita Bertoni, Ilaria Carpinella, Chiara Pegorini, Andrea Tacchino, Erica Grange, Valentina Guidotti, Giampaolo Brichetto, Claudio Solaro, Tommaso Budassi, Tatiana Lanfranco, Marco Rovaris, Davide Cattaneo and Elisa Gervasoni in DIGITAL HEALTH

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Supplemental material, sj-pdf-3-dhj-10.1177_20552076251346694 for Effects of high-intensity multimodal functional training on motor and cognitive functions in people with multiple sclerosis: A study protocol of a pilot randomized controlled trial by Rebecca Cardini, Rita Bertoni, Ilaria Carpinella, Chiara Pegorini, Andrea Tacchino, Erica Grange, Valentina Guidotti, Giampaolo Brichetto, Claudio Solaro, Tommaso Budassi, Tatiana Lanfranco, Marco Rovaris, Davide Cattaneo and Elisa Gervasoni in DIGITAL HEALTH

Footnotes

Acknowledgements

We would like to thank Camilla Cardini for her contribution to the creation of the illustrations.

ORCID iD

Ilaria Carpinella

Ethical considerations

This study received IRCCS Fondazione Don Carlo Gnocchi ethical committee (Milan; number id: 04_29/03/2023) and the Comitato Etico Territoriale – Liguria (Genoa; number id: 559/2023 - DB id 13567) approval before study initiation. Participants provided written informed consent to be recruited in the study.

Author contributions

Conceptualization done by RC, EG, RB, DC, and MR; methodology done by IC, EG, DC, AT, GB, and CS; validation conducted by RC, IC, RB, and EG; formal analysis done by IC and DC; investigation done by RC, CP, RB, EG, EGr., AT, VG, TB, TL, and CS; resources by RC, CP, RB, EG, EGr., AT, TB, TL, CS; data curation by RC, CP, RB, EG, EGr., AT, and TB; writing—original draft preparation by RC, EG, RB, IC, and DC; writing—review and editing by all authors; visualization by RC and IC; supervision by EG, AT, CS, and GB; project administration done by EG. All authors have read and agreed to the published version of the manuscript.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: this work was supported by the Italian Multiple Sclerosis Foundation-FISM [FISM Grant 2022/R-Multi/005] and it was partially supported by funding from Promobilia Foundation.

Fondazione Italiana Sclerosi Multipla, Stiftelsen Promobilia, (grant number FISM Grant 2022/R-Multi/005).

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Supplemental material

Supplemental material for this article is available online.

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