BJMB
Brazilian Journal of Motor Behavior
Special issue:
“Control of Gait and Posture: a tribute to Professor Lilian T. B.
Gobbi”
!
David
2023
VOL.17
N.4
146 of 149
Mini-Review: Gait and balance assessment in multiple sclerosis
ANA C. DAVID
1
1
University of Brasilia, Department of Physical Education, Human Movement Analysis Laboratory, Brasilia, Brazil
Correspondence to:!Ana Cristina de David.
email: acdavid@unb.br
https://doi.org/10.20338/bjmb.v17i4.357
HIGHLIGHTS
• Gait and balance deficits are significant concerns for
people with multiple sclerosis (MS).
• People at early stages of MS have subtle postural
balance and gait problems.
• Quantitative and objective measures combined with
clinical assessments are important to assess postural
balance and gait in MS rehabilitation.
• Kinematics, kinetics, spatiotemporal parameters and
posturography appear to be sensitive biomarkers to
detect subtle impairments on gait and postural balance in
MS.
ABBREVIATIONS
EDSS Expanded Disability Status Scale
IMUs Inertial measurement units
MS Multiple Sclerosis
pwMS People with multiple sclerosis
PUBLICATION DATA
Received 01 04 2023
Accepted 26 05 2023
Published 20 06 2023
ABSTRACT
BACKGROUND: Gait and balance deficiencies are significant concerns for people with
multiple sclerosis, resulting in reduced walking capacity, falls and poor quality of life. Issues
caused by sensory loss and the inability to properly reweight sensory information are often
reported. Even at the early stages of the disease, subclinical gait and balance impairments
can be found.
AIM: In this article, we review objective measures used to assess gait and postural balance
impairment in multiple sclerosis patients.
INTERPRETATION: Although scales and clinical tests are important tools for assessing
postural instability and walking performance, they can be insensitive to minor disabilities in
multiple sclerosis. Instrumented measurements, such as kinematics, kinetics, spatiotemporal
gait parameters and center of pressure, play an important role in detecting impairment and
evaluating the effects of interventions in people with mild to moderate multiple sclerosis. Thus,
objective measurements may be more suitable for tracking deficits in gait and postural
balance in multiple sclerosis, contributing to the early detection of disease symptoms, and
therefore allowing for the planning of effective interventions to control the speed of disease
progression.
KEYWORDS: Walking | Disability | Spatiotemporal Parameters | Center of Pressure |
Kinematics | Kinetics
INTRODUCTION
Multiple sclerosis (MS) is characterized by progressive demyelinating deterioration of nervous tissues in the brain and spinal
cord, leading to a disruption in the ability of parts of the central nervous system to transmit signals
1
. Gait and balance deficits are
significant concerns for people with multiple sclerosis (pwMS), and result in reduced walking capacity, risk of falls and poor quality of life
2,3
. Postural instability reflects, in large part, dysfunctional integration of visual, somatosensory, and vestibular sensory cues, as well as
inability to appropriately reweight sensory information. Both issues can affect stability when walking under challenging conditions
4,5
.
Expanded Disability Status Scale (EDSS) is the most frequently used scale to evaluate disability level and disease progression
among pwMS. EDSS scores are determined based on the seven functional systems: visual, brainstem, pyramidal, cerebellar, sensory,
bowel-bladder, cerebral functions, and on walking capacity
6
. In addition to the EDSS, walking capacity and functional balance are
traditionally assessed for clinical and research purposes by various other measures, including patient self-reports, clinical scales,
functional tests and performance measures, such as Patient-Determined Disease Step (measure of mobility disability), Berg Balance
Scale (functional balance assessment), Timed Up and Go test (functional mobility) and 6-Minute Walking Test (walking capacity)
7,8
.
Despite the clinical importance of these measures, it may be that these tools are not sensitive enough to detect subtle deficits at an early
stage of MS (0-3.5)
9
.
People at early stages of MS have subtle balance problems that may affect gait stability
10-12
. MS has a significant effect on gait,
even for those with relatively low scores on EDSS
13
. Furthermore, balance and gait parameters in pwMS with different disease
progression subtypes have great variability within EDSS categories
14
.
Instrumentally assessed gait and postural balance provide sensitive biomarkers for detection of subtle impairments even in the
BJMB! ! ! ! ! ! ! ! !
Brazilian(Journal(of(Motor(Behavior(
(
David
2023
VOL.17
N.4
147 of 149
Special issue:
“Control of Gait and Posture: a tribute to Professor Lilian T. B. Gobbi”
earliest stages of the disease. Posturography is considered the gold standard for objective measure of standing postural control in pwMS.
This is a reliable tool providing quantitative data related to postural instability. Center of pressure (CoP) sway is an appropriate outcome
measure indicating postural balance deterioration in pwMS
10,11
. Minor gait abnormalities may be detected by kinematics and kinetics
variables. These measurements can provide valuable information on the underlying pathomechanisms of gait and postural control and
may represent a complementary tool combined to clinical tests in pwMS
15
.
A growing number of clinical trials have investigated the effectiveness of various postural balance and gait interventions in MS.
Choosing objective and reliable results is crucial to screen for the disease and determine the effectiveness of interventions. Early
detection of disease symptoms in MS, as well as knowledge of gait and postural balance deterioration mechanisms, allow the planning of
effective rehabilitation interventions to control the speed of disease progression. This article reviews objective measures used to assess
gait and postural balance impairment in multiple sclerosis.
BALANCE AND GAIT ASSESSMENT
Clinical tools and instrumental techniques are available for testing balance function, during static and dynamic situations, and
walking performance. There is a growing consensus on the need for quantitative and objective measures combined with clinical
assessments to assess balance and gait in MS rehabilitation.
Postural balance
Integration deficits of sensory inputs lead to inadequate motor responses. A major symptom of pwMS who have mild balance
disability is poor postural control, resulting from slowed spinal somatosensory conduction
5
. The assessment of balance deficits through
disturbances in standing posture with incongruent visual and proprioceptive feedback allows us to increase our knowledge of postural
control. Postural balance impairments are most apparent when vision is removed, and the base of support is reduced. Unstable surfaces
or incorrect visual information are also used to test the sensory systems involved in postural control.
Static posturography involves the electronic evaluation of the CoP oscillations using force platform, measuring parameters
including velocity, path length, and area in different situations such as open/closed eyes and rigid/foam surfaces. Outcomes such as
average sway and average speed of sway calculated from mediolateral sway amplitude have been shown to be the strongest predictors
to discriminate people impaired by MS from healthy subjects
10
. CoP trajectories during quiet stance showed pwMS have considerable
deficits in postural control while standing in comparison to healthy controls
10,11,16
.
Gait
MS has a significant effect on gait, particularly on speed, stride length and asymmetry, even for those with relatively low EDSS.
Great variability can be found in people with the same level of disability on the EDSS or with the same performance on clinical tests. This
effect is amplified when walking at faster speeds or in challenging situations, such as climbing stairs or changing direction while turning,
suggesting that these test conditions may be more beneficial for evaluation and treatment
17,18
.
The most used outcome measures for functional walking ability assessment in MS have been the 6-Minute Walking Test, a
walking capacity measure and the Timed Up and Go test
8
. They are followed by gait spatiotemporal parameters most often used to
inform gait speed, cadence, and step length
8,19
. Moreover, assessment of walking speed with short walking capacity tests such as the
25-Foot Timed Walk or the 10-m Walk Test, and tests for walking an intermediate distance, such as the 2-min Walk Test, have been
suggested in literature
7
.
Walking performance defines the participation of pwMS in many activities of daily life, and dynamic gait stability has been
identified as a key risk factor of falls. To compensate for the dynamic gait stability deficit resulting from the slow gait speed, pwMS adopt
a short step length to shift the center of mass within the area of stability
12
. Changes in spatiotemporal parameters have also been
associated with disability severity according to EDSS level
20
.
Although those tests provide excellent information about walking performance, little is known about the biomechanics of
movement (joint kinematics and kinetics) and possible compensatory movements. Such knowledge would be fundamental in the
elaboration of more efficient treatment plans.
The gait analysis technique can be used to assess the three-dimensional kinematic and kinetic of gait, and allows for a better
understanding of the mechanisms underlying gait deterioration in pwMS
21,22
. Even in the early stage of the disease, the most common
and reported biomechanical alterations in the lower limbs of pwMS are reduced knee and ankle range of motion increased gait variability
and asymmetry along with impaired dynamic stability
21,23
.
BJMB! ! ! ! ! ! ! ! !
Brazilian(Journal(of(Motor(Behavior(
(
David
2023
VOL.17
N.4
148 of 149
Special issue:
“Control of Gait and Posture: a tribute to Professor Lilian T. B. Gobbi”
Most of the propulsive energy for walking is generated around the ankle (plantarflexor power). There is a reduced ankle
dorsiflexor power in pwMS, which can be the result of a reduced ankle angular motion and dorsiflexor moment. The ankle dorsiflexor
power is the main predictor of step length and walking speed; hence, its reduction is likely to explain slow walking speed in most studies
investigating MS related gait deterioration
24
.
Furthermore, compared to health control, pwMS has a lower knee extension moment. Reduced knee extension moment is
associated with low knee flexion power at initiation of the stance, indicating a reduced ability to eccentrically activate the knee extensor
muscles to absorb impact energy at the foot contact point. While reduced knee extensor (quadriceps) strength may explain this, it may
also result from increased knee flexion during initial stance in pwMS due to hamstring spasticity
24
. Results indicate that pwMS with a
spastic-paretic gait pattern have more deterioration with regard clinical walking function
21,22
.
Traditionally, gait analysis uses motion capture systems based on optical cameras and force platforms to measure three-
dimensional kinematics and kinetics. Spatiotemporal parameters can be measured on electronic walkways, in addition to motion capture.
Currently, new solutions have been proposed to measure kinematics and spatiotemporal parameters of gait. One of the most promising
has been wearable technology or inertial measurement units (IMUs). Wearable technology refers to any sensor worn on a person,
making continuous and remote monitoring available to many people with chronic disease, including MS. IMUs are small, light wearable
sensors that allow accurate quantification of balance and gait impairment that can be used in both clinical and research settings
25,26
.
CONCLUSION
More sensitive tools such as posturography can be used to assess postural instability in pwMS, while gait dysfunction can be
detected by kinematics and kinetics variables. These measurements provide ways to objectively assess and interpret disease
progression and treatment effects. The development of new technologies in biomechanics is making these types of measurements
cheaper and more accessible, allowing them to be used more flexibly, in a clinical or real-world environment, in addition to research
laboratories.
REFERENCES
1. Thompson AJ, Baranzini SE, Geurts J, Hemmer B, Ciccarelli O. Multiple sclerosis. Lancet. 2018;391:1622-1636. doi: 10.1016/S0140-
6736(18)30481-1.
2. Cameron MH, Nilsagard Y. Balance, gait, and falls in multiple sclerosis. Handb Clin Neurol. 2018;159:237-250. doi:10.1016/B978-0-444-
63916-5.00015-X.
3. Cattaneo D, Rasova K, Gervasoni E, Dobrovodská G, Montesano A, Jonsdottir J. Falls prevention and balance rehabilitation in multiple
sclerosis: a bi-centre randomised controlled trial. Disabil Rehabil. 2018;40(5):522-526. doi: 10.1080/09638288.2016.1258089.
4. Craig JJ, Bruetsch AP, Lynch SG, Huisinga JM. Altered visual and somatosensory feedback affects gait stability in persons with multiple
sclerosis. Hum Mov Sci. 2019;66:355-362. doi:10.1016/j.humov.2019.05.018.
5. Doty RL, MacGillivray MR, Talab H, Tourbier I, Reish M, Davis S, et al. Balance in multiple sclerosis: relationship to central brain regions. Exp
Brain Res. 2018;236:2739-2750. doi:10.1007/s00221-018-5332-1.
6. Zurawski J, Glanz BI, Chua A, Lokhande H., Rotstein D., Weiner H., et al. Time between expanded disability status scale (EDSS) scores.
Mult Scler Relat Disord. 2019;30:98-103 doi: 10.1016/j.msard.2019.02.007.
7. Soler B, Ramari C, Valet M, Dalgas U, Feys P. Clinical assessment, management, and rehabilitation of walking impairment in MS: an expert
review. Expert Rev Neurother. 2020;20(8):875-886. doi:10.1080/14737175.2020.1801425.
8. Santisteban L, Teremetz M, Irazusta J, Lindberg PG, Rodriguez-Larrad A. Outcome measures used in trials on gait rehabilitation in multiple
sclerosis: A systematic literature review. PLoS One. 2021;16(9):e0257809. doi:10.1371/journal.pone.0257809
9. Carpinella I, Gervasoni E, Anastasi D, Di Giovanni R, Tacchino A, Brichetto G, et al Instrumentally assessed gait quality is more relevant than
gait endurance and velocity to explain patient-reported walking ability in early-stage multiple sclerosis. Eur J Neurol. 2021;28(7):2259-2268.
doi:10.1111/ene.14866.
10. Inojosa H, Schriefer D, Klöditz A, Trentzsch K, Ziemssen T. Balance testing in multiple sclerosis improving neurological assessment with
static posturography? Front Neurol. 2020;11:135. doi:10.3389/fneur.2020.00135.
11. Cimino V, Chisari CG, Raciti G, Pappalardo A, Zappia M, Patti F. Static postural control disturbances among the different multiple sclerosis
phenotypes: A Neurocom Balance Manager® evaluation study. Mult Scler Relat Disord. 2018;26:46-51. doi:10.1016/j.msard.2018.08.024.
12. Lin MW, Liu W, Yang F. Influence of multiple sclerosis on dynamic gait stability. J Biomech. 2020;106:109827.
doi:10.1016/j.jbiomech.2020.109827.
BJMB! ! ! ! ! ! ! ! !
Brazilian(Journal(of(Motor(Behavior(
(
David
2023
VOL.17
N.4
149 of 149
Special issue:
“Control of Gait and Posture: a tribute to Professor Lilian T. B. Gobbi”
13. Liparoti M, Della Corte M, Rucco R, Sorrentino P, Sparaco M, Capuano R, et al. Gait abnormalities in minimally disabled people with Multiple
Sclerosis: A 3D-motion analysis study. Mult Scler Relat Disord. 2019;29:100-107. doi: 10.1016/j.msard.2019.01.028.
14. Zanotto T, Sosnoff, JJ, Ofori E, Golan D, Zarif M, Bumstead B, et al. Variability of objective gait measures across the expanded disability
status scale in people living with multiple sclerosis: A cross-sectional retrospective analysis. Mult Scler Relat Disord. 2022;59:103645 doi:
10.1016/j.msard.2022.103645.
15. Huang SC, Guerrieri S, Dalla Costa G, Pisa M, Leccabue G, Gregoris L, et al. Intensive Neurorehabilitation and Gait Improvement in
Progressive Multiple Sclerosis: Clinical, Kinematic and Electromyographic Analysis. Brain Sci. 2022;12(2):258. doi:
10.1016/j.msard.2018.08.024.
16. Comber L, Galvin R, Coote S. Gait deficits in people with multiple sclerosis: A systematic review and meta-analysis. Gait Posture.
2017;51:25-35. doi: 10.1016/j.gaitpost.2016.09.026.
17. Brandstadter R, Ayeni O, Krieger SC, Harel NY, Escalon MX, Sand IK, et al. Detection of subtle gait disturbance and future fall risk in early
multiple sclerosis. Neurology. 2020;94(13):1395-1406. doi: 10.1212/WNL.0000000000008938.
18. Adusumilli G, Lancia S, Levasseur VA, Amblee V, Orchard M, Wagner JM, et al. Turning is an important marker of balance confidence and
walking limitation in persons with multiple sclerosis. PLoS One. 2018;13(6):e0198178. doi: 10.1371/journal.pone.0198178.
19. Sato SD, Hiroi Y, Zoppo D, Buonaccorsi J, Miehm JD, van Emmerik REA. Spatiotemporal gait changes in people with multiple sclerosis with
different disease progression subtypes. Clin Biomech. 2022;100:105818. doi: 10.1016/j.clinbiomech.2022.105818.
20. Chee JN, Ye B, Gregor S, Berbrayer D, Mihailidis A, Patterson KK. Influence of multiple sclerosis on spatiotemporal gait parameters: A
systematic review and meta-regression. Arch Phys Med Rehabil. 2021;102(9):1801-1815. doi: 10.1016/j.apmr.2020.12.013.
21. Filli L,Sutter T,Easthope CS, Killeen T, Meyer C, Reuter K, et al. Profiling walking dysfunction in multiple sclerosis: characterisation,
classification and progression over time. Scientific Reports. 2018;8(1):4984. doi: 10.1038/s41598-018-22676-0
22. Zörner B, Hostettler P, Meyer C, Killeen T, Gut P, Linnebank M, et al. Prognosis of walking function in multiple sclerosis supported by gait
pattern analysis. Mult Scler Relat Disord. 2022;63:103802. doi:10.1016/j.msard.2022.103802.
23. Massot C, Guyot MA, Donze C, Simoneau E, Gillet C, Leteneur, S. Ankle dysfunction in multiple sclerosis and the effects on walking. Disabil
Rehabil. 2021;43(17):2454-2463. doi: 10.1080/09638288.2019.1702726.
24. Lizama EF, Khan F, Lee PV, Galea MP. The use of laboratory gait analysis for understanding gait deterioration in people with multiple
sclerosis. Mult Scler J. 2016; 1–9. doi: 10.1177/ 1352458516658137.
25. Vienne-Jumeau A, Quijoux, F, Vidal PP, Ricard D. Value of gait analysis for measuring disease severity using inertial sensors in patients with
multiple sclerosis: protocol for a systematic review and meta-analysis. Syst Rev. 2019;8(1):1-5. doi:10.1186/s13643-018-0918-z.
26. Alexander S, Peryer G, Gray E, Barkhof F, Chataway J. Wearable technologies to measure clinical outcomes in multiple sclerosis: a scoping
review. Mult Scler. 2021;27(11):1643-1656. doi:10.1177/1352458520946005.
Citation: David AC. (2023).!Mini-Review: Gait and balance assessment in multiple sclerosis. Brazilian Journal of Motor Behavior, 17(4):146-149.
Editor-in-chief: Dr Fabio Augusto Barbieri - São Paulo State University (UNESP), Bauru, SP, Brazil. !
Associate editors: Dr José Angelo Barela - São Paulo State University (UNESP), Rio Claro, SP, Brazil; Dr Natalia Madalena Rinaldi - Federal University of Espírito Santo
(UFES), Vitória, ES, Brazil; Dr Renato de Moraes – University of São Paulo (USP), Ribeirão Preto, SP, Brazil.
Guest editors: Dr Fabio Augusto Barbieri - São Paulo State University (UNESP), Bauru, SP, Brazil; Dr Lucas Simieli; Dr Victor Spiandor Beretta - São Paulo State
University (UNESP), Presidente Prudente, SP, Brazil.!
Copyright:© 2023 David and BJMB. This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives 4.0
International License which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: Nothing to declare.
Competing interests: The authors have declared that no competing interests exist.
DOI:!https://doi.org/10.20338/bjmb.v17i4.357