literature review gait analysis

Evidence on the Use of Gait Analysis - A Review

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First Online: 30 August 2020
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Afonso Laranjo 19 ,
Susana Costa 19 ,
Fernando Duarte 20 ,
Miguel Carvalho 21 &
Pedro Arezes 19

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1269))

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International Conference on Human Systems Engineering and Design: Future Trends and Applications

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Gait analysis consists of evaluating the individual through kinematic analysis, while walking along a surface. Kinematic analysis relates the relative movement between rigid bodies and finds applications in gait analysis. The purpose of this paper is to find the applications of gait analysis, the methodologies used to perform it and conclude about the different methodologies’ uses. A literature search was performed using PRISMA Guidelines. Twenty-two documents fulfilled the inclusion criteria. A total of 15 different countries presented researches in this topic. The areas within which these papers are published include Sports Medicine (7), Pediatric Medicine (1), General Medicine (11), Occupational Medicine (1), Engineering (2). Gait analysis has many different areas of intervention. Some gait parameters are interrelated and there are a few different methodologies available to perform gait analysis. A comprehensive table of results has been developed, where results are presented.

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Acknowledgments

This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020.

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Fernando Duarte

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Laranjo, A., Costa, S., Duarte, F., Carvalho, M., Arezes, P. (2021). Evidence on the Use of Gait Analysis - A Review. In: Karwowski, W., Ahram, T., Etinger, D., Tanković, N., Taiar, R. (eds) Human Systems Engineering and Design III. IHSED 2020. Advances in Intelligent Systems and Computing, vol 1269. Springer, Cham. https://doi.org/10.1007/978-3-030-58282-1_9

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Research Article

Outcome measures used in trials on gait rehabilitation in multiple sclerosis: A systematic literature review

Roles Conceptualization, Data curation, Methodology, Writing – original draft, Writing – review & editing

* E-mail: [email protected] , [email protected]

Affiliations Department of Physiology, University of the Basque Country, UPV/EHU, Leioa, Spain, Biocruces Bizkaia Health Research Institute, Barakaldo, Bizkaia, Spain

Roles Data curation, Writing – review & editing

Affiliation Institute of Psychiatry and Neuroscience of Paris, INSERM U1266, Université Paris Descartes, Sorbonne Paris Cité, Paris, France

Roles Conceptualization, Writing – original draft, Writing – review & editing

Roles Writing – original draft, Writing – review & editing

Affiliation Department of Physiology, University of the Basque Country, UPV/EHU, Leioa, Spain

L. Santisteban,
M. Teremetz,
J. Irazusta,
P. G. Lindberg,
A. Rodriguez-Larrad

Published: September 30, 2021
https://doi.org/10.1371/journal.pone.0257809
Reader Comments

Multiple Sclerosis (MS) is associated with impaired gait and a growing number of clinical trials have investigated efficacy of various interventions. Choice of outcome measures is crucial in determining efficiency of interventions. However, it remains unclear whether there is consensus on which outcome measures to use in gait intervention studies in MS.

We aimed to identify the commonly selected outcome measures in randomized controlled trials (RCTs) on gait rehabilitation interventions in people with MS. Additional aims were to identify which of the domains of the International Classification of Functioning, Disability and Health (ICF) are the most studied and to characterize how outcome measures are combined and adapted to MS severity.

Pubmed, Cochrane Central, Embase and Scopus databases were searched for RCT studies on gait interventions in people living with MS according to PRISMA guidelines.

In 46 RCTs, we identified 69 different outcome measures. The most used outcome measures were 6-minute walking test and the Timed Up and Go test, used in 37% of the analyzed studies. They were followed by gait spatiotemporal parameters (35%) most often used to inform on gait speed, cadence, and step length. Fatigue was measured in 39% of studies. Participation was assessed in 50% of studies, albeit with a wide variety of scales. Only 39% of studies included measures covering all ICF levels, and Participation measures were rarely combined with gait spatiotemporal parameters (only two studies).

Conclusions

Selection of outcome measures remains heterogenous in RCTs on gait rehabilitation interventions in MS. However, there is a growing consensus on the need for quantitative gait spatiotemporal parameter measures combined with clinical assessments of gait, balance, and mobility in RCTs on gait interventions in MS. Future RCTs should incorporate measures of fatigue and measures from Participation domain of ICF to provide comprehensive evaluation of trial efficacy across all levels of functioning.

Citation: Santisteban L, Teremetz M, Irazusta J, Lindberg PG, Rodriguez-Larrad A (2021) Outcome measures used in trials on gait rehabilitation in multiple sclerosis: A systematic literature review. PLoS ONE 16(9): e0257809. https://doi.org/10.1371/journal.pone.0257809

Editor: Peter Schwenkreis, BG-Universitatsklinikum Bergmannsheil, Ruhr-Universitat Bochum, GERMANY

Received: December 1, 2020; Accepted: September 12, 2021; Published: September 30, 2021

Copyright: © 2021 Santisteban et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Data are available as supporting information .

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

1. Introduction

1.1. rationale.

Multiple Sclerosis (MS) is an inflammatory demyelinating chronic disease of the central nervous system, and it is the most common non-traumatic cause of disability among young adults [ 1 ]. The clinical presentation and evolution of this disease is very heterogeneous, generating quite different disorders with important functional repercussions [ 2 ]. Gait impairment is one of the most common motor disorders [ 3 ] and is perceived as one of the most important bodily functions across the MS disability spectrum [ 4 ].

There is a central nervous system remodeling after inflammatory and demyelinating injuries by spontaneous mechanisms of recovery [ 1 ] that can be enhanced by rehabilitation interventions that promote activity dependent neural plasticity [ 5 ], improve the degree of functionality and increase Participation [ 6 , 7 ].

In recent years, with advances in the field of technology and neurorehabilitation, there have been a growing number of new rehabilitation approaches and RCTs to assess their efficacy [ 8 ]. Assessment in this context is central and selecting the most appropriate outcome measures is crucial for determining which rehabilitation treatments are most efficient [ 9 ]. There are many assessment tools, clinical scales, self-questionnaires, and technological devices that are validated and commonly used in gait assessment in MS [ 8 , 10 ]. Psychometric properties of some of these assessment methods have already been studied by many authors [ 11 , 12 ]. However, a consensus about which are the most appropriate is lacking, although agreement is crucial to generalize outcomes.

Primary symptoms of MS impact not only on disability and functioning but can also have major effects on quality of life and socioeconomic issues. The World Health Organization proposes a framework and classification for measuring health and disability known as the International Classification of Functioning, Disability and Health (ICF). According to the ICF, health domains of people living with MS (pwMS) are classified into three levels: Body structure/Body function, Activity, and Participation domains [ 13 , 14 ]. In RCTs, assessing health according to all three ICF domains is considered beneficial in determining efficacy of rehabilitation techniques in the different health domains. For example, including a measure from the Participation domain would provide information on whether the bio-psycho-social situation of people changes following the rehabilitation intervention. Gait rehabilitation interventions can improve not only walking abilities, classified in the ICF Activity domain, but also other aspects like strength, range of movement or spasticity, included in the Body function/Body structure domain, and aspects like self-esteem, social interaction or quality of life, included in the ICF Participation domain [ 10 , 15 ].

European Multiple Sclerosis rehabilitation recommendations [ 16 ] state that a comprehensive view of the pwMS status across all ICF domains is needed to provide adequate health care. It is emphasized to select outcome measures according to the ICF framework in clinical trials on MS rehabilitation.

There is a need for a systematic literature review focusing on assessment methods used in clinical trials on gait rehabilitation interventions in pwMS in recent years. This would inform on which outcome measures are most used in the clinical and scientific community. If measures are quite common across all studies, this would indicate a good consensus in the field. Knowing which outcome measures are used in clinical trials is a first step that would help improve the design of future studies by identifying weaknesses and strong points in gait assessment procedures.

The first aim of this systematic review was to identify the commonly selected outcome measures in randomized controlled trials (RCTs) on gait rehabilitation interventions in pwMS.

Secondary aims were to identify which of the domains of the ICF are the most studied and to characterize how outcome measures are combined and adapted to MS severity.

2.1. Study design and search strategy

A systematic literature review was performed according to PRISMA guidelines 2009 [ 17 ] and following the recommendations provided in the Cochrane handbook for literature reviews [ 18 ].

The search was performed in the following databases: Medline using Pubmed interface, Cochrane Central, Embase and Scopus.

The search strategy included articles from January 2010 until February 2021, using the following key words and Mesh terms: ("Walking"[Mesh] OR "Gait"[Mesh] OR "Gait Disorders, Neurologic"[Mesh] OR "Mobility Limitation"[Mesh]) AND ("Rehabilitation"[Mesh] OR "rehabilitation" [Subheading] OR "Physical and Rehabilitation Medicine"[Mesh] OR "Neurological Rehabilitation"[Mesh] OR "Exercise Therapy"[Mesh]) AND (“Multiple Sclerosis"[Mesh]).

The literature search included manual scanning of the reference lists of the included articles.

We limited the search (using database filters) to studies performed on human adults and published from 1/1/2010 to 28/02/2021.

Two independent reviewers (L.S., A.R.-L.) identified which articles to include.

The search and selection processes were performed independently by both L.S. and A.R.-L. Disagreements on whether to include a study were resolved by discussing with a third author (J.I) and reaching consensus.

2.2. Study identification

Following the removal of duplicates with Refworks and verifying them manually, included studies were identified by first screening the title and abstract and, secondly, by full text screening.

Articles were included if they fulfilled the following inclusion criteria: i) randomized clinical trials regarding rehabilitation interventions to improve gait capacities in pwMS, ii) adult participants > 18 years old. Exclusion criteria included: i) literature reviews, ii) study protocols, iii) studies regarding the psychometric properties of outcome measures, iv) studies combining participants with other neurological diseases, v) studies evaluating specific rehabilitation interventions of other impairments (e.g. upper limb rehabilitation interventions, pelvic floor muscle rehabilitation interventions, memory rehabilitation interventions, swallowing rehabilitation interventions, balance specific rehabilitation interventions, vestibular rehabilitation interventions), if the aim of the intervention was not to improve gait capacities.

2.3. Data extraction

Full articles were reviewed for: year of publication, characteristics of the participants (age, disease severity according to EDSS, form of MS), type of rehabilitation intervention, number of participants and reported outcome measures.

2.4. Data analysis

The data have been analyzed using Microsoft Excel software. Figs 2 and 3 were created with Excel software and Fig 4 with Gimp software.

Data are available.

The electronic search yielded 88 articles in Pubmed, 90 in Cochrane Central, 363 in Embase and 258 in Scopus.

The selection process is explained in Fig 1 .

PPT PowerPoint slide
PNG larger image
TIFF original image

https://doi.org/10.1371/journal.pone.0257809.g001

Forty-six articles [ 19 – 64 ] shown in Table 1 . fulfilled selection criteria, involving a total of 1842 patients. 69 outcome measures were identified in included RCTs, they are shown in Table 2 . The summary of data collection is shown in Table 1 .

https://doi.org/10.1371/journal.pone.0257809.t001

https://doi.org/10.1371/journal.pone.0257809.t002

Most commonly used outcome measures according to ICF levels

The wide range of outcome measures used across RCTs is depicted in Fig 2 . The most used outcome measures were the 6-minute walking test and the Timed Up and Go test, followed by gait spatiotemporal parameters (GSTP).

Abbreviations: 6MWT 6-minute walking test; TUG Timed up and go test; GSTP Gait spatio-temporal parameters; MSWS-12 Multiple sclerosis walking scale-12; BBS Berg balance scale; T25W Timed 25-foot walk; 10m 10-meter walking test; 2MWT 2-minute walking test; MSIS-29 Multiple sclerosis Impact Scale_29; FSS Fatigue severity scale; FIS/mFIS Fatigue impact scale/modified fatigue impact scale; EDSS Expanded disability status scale; DGI Dynamic gait index; MS-IM Muscle strength isokinetik measure; Ac Accelerometers; ABC Activities-specific balance confidence scale; MAS Modified Ashworth scale; VAS (pain) Visual analogic scale (pain); ROM Range of motion; VO2 peak oxygen uptake; FSST Four step square test; TBS Tinetti balance scale; QoL SF-36 Quality of life short form 36; MSQoL-54 Multiple sclerosis quality of life; SA Stabilometric assessment; MS-SS: Muscle strength static strength; FMSC Fatigue scale for motor and cognitive function; FRT Functional reach test; FES Falls efficacy scale; HRSD Hamilton rating scale for depression; HADS Anxiety and depression scale; MusiQoL Multiple Sclerosis International Quality of Life scale; PQH-9 Patient health questionnaire; MSSE Mini mental state examination; STS Sit to stand test; MSSS-88 Multiple sclerosis Spasticity Scale– 88; MRC Medical research council; MS-MD Muscle strength mechanical device; MS-LD Muscle strength lokomat device; WLT Working load in treadmill; DTI Diffusion tensor imaging; GNDS Guy’s Neurological Disability Scale; SSST Six spot step tests; mBEest Test Mini best test; CTSIB Test for sensory interaction and balance; 5MWT 5-minute walking tests; 3MWT 3-minute walking test; FAC Functional ambulatory scale; AI Ambulatory index; WHODAS 2.0 World health organization disability assessment schedule; SOT Sensory organization test; CPET Maximal cardiopulmonary exercise test; TST Timed stair test; MSFCS Multiple sclerosis functional composite; COPM Canadian occupational performance measure; FD Falls diary; PASAT Paced auditory serial attention test; SRT sit and reach test; FBS Fullerton balance scale; WE Wurzburger inventory; WHOQoL-Bref WHO quality of life-bref; RAND-36 Random 36 health survey; BDI Beck depression inventory; COPE Coping Orientation to Problem Experienced; WEI-MuS Wurzburg Fatigue Inventory for Multiple Sclerosis; FAB Frontal assessment battery; MSSS-88 Multiple sclerosis Spasticity Scale; QoL-EQD Euro quality of life; PDDS Patient Determined Disease Steps.

https://doi.org/10.1371/journal.pone.0257809.g002

Of the 69 outcome measures found, 20 assessed Body function and Body structure , 35 assessed Activity and 14 assessed Participation domains of ICF (See Fig 3 ). 17% of the studies assessed only one ICF domain, 44% of RCTs included measures covering two ICF domains and only 39% measures from all three ICF domains.

Abbreviations: GSTP Gait spatiotemporal parameters; FSS Fatigue severity scale; FIS/mFIS Fatigue impact scale/modified fatigue impact scale; MS-IM Muscle strength isokinetik measure; VAS (pain) Visual analogic scale (pain); ROM Range of motion; VO2 peak oxygen uptake; MAS Modified Ashworth scale; SA Stabilometric assessment; MS-SS: Muscle strength static strength; MSC Fatigue scale for motor and cognitive function; MRC Medical research council; MS-MD Muscle strength mechanical device; MS-LD Muscle strength lokomat device; WLT Working load in treadmill; DTI Diffusion tensor imaging; MSSS-88 Multiple sclerosis Spasticity Scale– 88; WEI-MuS Wurzburg Fatigue Inventory for Multiple Sclerosis; MSIS-29 Multiple sclerosis Impact Scale_29; QoL SF-36 Quality of life short form 36; MSQoL-54 Multiple sclerosis quality of life; HRSD Hamilton rating scale for depression; HADS Anxiety and depression scale; MusiQoL Multiple Sclerosis International Quality of Life scale; PQH-9 Patient health questionnaire; MSSE Mini mental state examination; WHOQoL-Bref WHO quality of life-bref; RAND-36 Random 36 health survey; BDI Beck depression inventory; COPE Coping Orientation to Problem Experienced; FAB Frontal assessment battery; QoL-EQD Euro quality of life; 6MWT 6-minute walking test; TUG Timed up and go test; MSWS-12 Multiple sclerosis walking scale-12; BBS Berg balance scale; T25W Timed 25-foot walk; 10m 10-meter walking test; 2MWT 2-minute walking test; EDSS Expanded disability status scale; DGI Dynamic gait index; Ac Accelerometers; ABC Activities-specific balance confidence scale; FSST Four step square test; TBS Tinetti balance scale; FRT Functional reach test; FES Falls efficacy scale; STS Sit to stand test; GNDS Guy’s Neurological Disability Scale; PDDS Patient Determined Disease Steps; SSST Six spot step tests; Mini Best Test Mini best test; CTSIB Test for sensory interaction and balance; 5MWT 5-minute walking tests; 3MWT 3-minute walking test; FAC Functional ambulatory scale; AI Ambulatory index; WHODAS 2.0 World health organization disability assessment Schedule; SOT Sensory organization test; CPET Maximal cardiopulmonary exercise test; TST Timed stair test; MSFCS Multiple sclerosis functional composite; COPM Canadian occupational performance measure; FD Falls diary; PASAT Paced auditory serial attention test; SRT sit and reach test; FBS Fullerton balance scale.

https://doi.org/10.1371/journal.pone.0257809.g003

The Body structure/Body function domain was assessed in 80% of studies and the most used outcome measure to assess this domain was GSTP, used in 35% of RCTs. GSTP referred to b770 on ICF domain [ 15 ], was performed using different systems: nine studies used the Gaitrite system, two used the Vicon system, one used the Smart-D BTS bioengineering system, two used the Qualisys motion system, one study used the Gait-Real-time-Analysis-Interactive-Lab and one study a 3D photogrammetry. All these systems provide GSTP and some of these technological systems provide kinematics parameters with information about displacement and range of movement of joints. In studied RCT only 10% provide kinematic parameters.

In terms of GSTP, most studies (87%) reported gait speed, 67% of these studies reported cadence (steps/minute), 56% reported step length, and 37% analyzed stride length. Specific GSTP used in each study are reported in Table 3 .

https://doi.org/10.1371/journal.pone.0257809.t003

Fatigue , referred by the Body function/Body structure ICF item b4552 [ 15 ], is a cardinal symptom in MS impacting on gait pattern and functioning, and was assessed in 39% of studies using four different scales, the fatigue severity scale (15% of studies), the fatigue impact scale (15% of studies), the fatigue scale for motor and cognitive function (4% of studies), and the Wei-MUS scale (4% of studies).

The Activity domain was assessed in 91% of studies, assessing walking capacities referring to d450 ICF item (walking) and d4609 item (move around) [ 15 ]. Following the 6-minute walking test and the Timed Up and Go test used in 37% of studies, the Multiple Sclerosis Walking Scale-12 was used in 26% of studies and the Berg Balance Scale was used in 24% of studies. The expanded disability status scale (EDSS) for MS is used in 91% of the studies. Studies used the EDSS for different purposes. Only 13.33% used the EDSS to assess intervention efficacy and 80% of the studies used EDSS for classifying clinical status of the participants.

Participation and quality of life was assessed in 50% of studies, using 14 different scales. The most used outcome measure to assess this domain was the Multiple Sclerosis Impact Scale 29, used in 17% of the studies, followed by the Quality of Life Short Form 36, used in 6% of the studies.

How outcome measures are distributed according to ICF levels is described in Fig 3 .

Combination of outcome measures

How often outcome measures were combined with each other is shown in Fig 4 . Four scales were combined as ‘Minutes walked’: 2-meter walking test, 3-minute walking test, 5-minute walking test, and 6-minute walking test. ‘Meters walked’ represents a combination of 10-meter walking test and the Timed 25-foot walk test. Ms represents combination of muscle strength with Lokomat device, isokinetic dynamometers, mechanical devices, and static strength measures.

Abbreviations: FSS Fatigue Severity Scale; FIS Fatigue impact scale; GSTP Gait spatio temporal parameters; Ms Muscle strength; MSIS Multiple sclerosis impact scale; QoLSF- 36 Quality of life short form 36; MSQoL-54 Multiple sclerosis quality of life 54; MSWS-12 Multiple Sclerosis Walking Scale-12; Minute walk 2-minute,3-minute, 5-minute and 6-minute walking Tests merged; Meters walk 10-meter walking test/Timed 25-foot walk test merged; TUG Timed Up and Go; BBS Berg Balance Scale.

https://doi.org/10.1371/journal.pone.0257809.g004

The most common combination of measures was between ‘Meters walked’ and ‘Minutes walked’ measures used in 32% of studies (15 RCT) and between ‘Minutes walked’ and Timed Up and Go used in 24% of studies (11 RCT).

The most common inter-domain combinations of measures were between Fatigue Impact Scale on Body structure/Function level and ‘Minutes walked’ measure on Activity level (85% of studies using FIS) and between Multiple Sclerosis Impact Scale on Participation level and ‘Minutes Walked’ (88% of studies using MSIS) on Activity level.

GSTP assessment was complemented by other clinical mobility measures: 31% of them used a measure of walking time (predominantly 6-minute walking test) and 31% of studies also assessed Timed 25-foot walk test ( meters walked ; Fig 4 ). GSTP was less often combined with Berg Balance Scale (three studies, 19%) and Multiple Sclerosis Walking Scale-12 (four studies, 25%) and Timed Up and Go (two studies, 12%). GSTP was combined with muscle strength measurement in 19% of studies, but was rarely combined with fatigue measures (only one study, 6%) using Fatigue Severity Scale, and was combined with quality of life or participation assessments in only two RCT.

In Fig 4 . we can see how outcome measures were combined in studies. Represented by a line between scales, the thicker the line is the more often the two scales are used in the same RCTs.

Outcome measure selection adapted to severity of MS

We stratified studies according to clinical status and gait capacity of the participants to study whether this influenced selection of outcome measures. A score of 4.5 on EDSS has been used [ 65 , 66 ] to classify MS participants into those with mild walking disability (score <4.5) and moderate to severe (score >4.5) gait disturbance [ 67 ]. In 19 RCTs, including participants with severe gait disturbance according to EDSS, the Timed Up and Go was the most used outcome measure, used in 47% of studies, followed by the 6-minute walking test used in 42% of studies. In 22 RCTs with less affected participants, the most used outcome measure was GSTP used in 54% of studies followed by the 6-minute walking test and Multiple sclerosis walking scale-12, used in 32% of studies.

4. Discussion

This systematic review showed that the most used outcome measures in RCTs on gait interventions in MS were the 6-minute walking test and the Timed Up and Go test, followed by GSTP, and that the choice of outcome measures depended on MS disease severity of participants. This study also highlights the large heterogeneity in the outcome measures used, and the fact that only the 39% of analyzed studies considered the three ICF domains in their assessment.

Gait spatiotemporal parameters and clinical assessments of gait

Assessments performed with technological devices to assess GSTP provide clinicians and researchers with accurate objective information. The studied parameters included time or distance parameters like stance duration, swing duration, stride length, gait cycle duration, cadence, velocity and normalized velocity [ 68 ]. One advantage of technological gait evaluation is that specific and sensitive information about gait quality (e.g., lower limb movement symmetry, support phase symmetry) and gait pattern (e.g., spastic-paretic, ataxia like, unstable gait) [ 69 ] is obtained allowing to gauge the impact of the studied interventions on these aspects.

In reviewed studies, the GSTP most often assessed with technological devices was gait speed. Other parameters like step length or support are not sensitive enough to detect changes in gait capacity across EDSS spectrum of mobility [ 70 ].

In the included RCTs, GSTP were more frequently reported in studies on patients with mild EDSS (score <4.5). GSTP were also often combined with clinical assessment of gait, mobility, and balance (6-minute walking test, Timed Up and Go, Berg Balance Scale; see Fig 4 ). Included RCTs have thus provided comprehensive evaluations of gait.

There is a growing tendency to use GSTP to assess gait capacities in RCTs. Despite this fact, studies on the psychometric properties of these methods is needed. This point was already pointed out by Andreopoulou in 2019 [ 71 ], stating that although 3D gait analysis is considered a “gold” standard, psychometric properties of some of the measures provided by these technological systems have not been examined in pwMS. They studied the relative and absolute reliability of ankle kinematics and GSTP provided by VICON system in a sample of 49 pwMS. Their results indicate good to excellent relative reliability of walking speed, step length and cadence. Psychometric properties of other systems like GAITrite have been studied. Riis in 2020 [ 72 ] studied its convergent validity in a sample of 24 geriatric patients, studying correlations between Berg Balance Scale, DGI and Timed Up and Go test, showing moderate correlations between GAITrite parameters and functional tests. Hoschproung in 2014 [ 73 ] compared GAITrite provided GSTP with results of the Timed 25-foot walk test in a sample of 85 pwMS, obtaining as results that the GAITrite system has the same clinical validity in gait evaluation as the Timed 25-foot walk test. Sosnoff in 2011 [ 74 ] studied the validity of the functional ambulatory profile (FAP) score from GAITrite in a sample of 13 pwMS. They found that this specific parameter strongly correlated with the EDSS, walking performance (Timed 25-foot walk tests and Timed Up and Go tests) supporting validity of this GAITrite measure. But there is still a lack of knowledge about psychometric properties of GSTP obtained using other technological systems.

The most used clinical scales for gait assessment in the Activity domain of the ICF were the following: 6-minute walking test, Timed Up and Go test, 10-meter walking test, Timed 25-foot walk test. These clinical measures have good psychometric properties [ 75 ] and they assess gait in a quantitative manner. The 6-minute walking test gives information about cardiopulmonary function, and also provides information about walking capacities; the Timed Up and Go test provides quantitative information about gait and functional capacities, assessing a sit to stand transfer from a chair followed by 3 meter walk, a turning and a return to the sitting position, allowing to assess also dynamic balance and gait stability; the Timed 25-foot walk test is a short distance measure of walking speed; the 10-meter walking test assesses a short distance walk allowing to asses gait speed [ 76 ]. All these tests can be complementary to each other, giving information about different aspects of gait. But it is difficult to compare efficacy of interventions across RCTs when different outcome measures are used. This makes clinical decision making and the establishment of evidence-based guidelines challenging, particularly when metanalyses are lacking.

Gait speed was the most commonly used GSTP and was also measured in clinical gait assessments. There is thus good consensus among clinical researchers to use gait speed to assess efficacy of gait rehabilitation interventions. There are other authors that describe gait speed as a suitable outcome to assess differences in gait performance [ 70 ]. However, GSTP, 10-meter walking test, 2-minute walking test, 3-minute walking tests, and the Timed 25-foot walk, assess gait speed in different ways. Gait speed over short distances is assessed in the 10-meter walking test, and Timed 25-foot walk test, while 2-minute walking test, 3-minute walking test, 5-minute walking test, and 6-minute walking test assess gait speed and endurance over longer distances. Clinical scales and assessment with technological systems also differ in terms of instructions provided to the subject or required speed (maximal speed, comfort speed), with no standardized protocol for every technological system.

Gait speed seems to be the parameter that researchers choose to assess gait rehabilitation interventions, assessing gait capacities in a quantitative manner. Although all trials include gait speed as an outcome measure, it is difficult to compare across clinical trials since testing procedures differed, e.g., distances covered and instructions provided were not the same. A consensus about modalities of assessment of this parameter, including standardized protocol for short and long-distance testing, could help in comparing results across RCTs.

Although gait speed is one of the parameters that is affected in pMS, decreasing while EDSS increases [ 69 ], one may ask if improving gait speed in performed tests really reflects an improvement in gait capacities. A less studied aspect, walking speed reserve (i.e., the difference between usual and fastest speed) could be important for interpretation of RCT results. Gijbels in 2010 [ 77 ] found that pace instructions provided influenced gait speed of the participants. They also reported that the difference between comfortable self-induced walking pace and fastest possible walking speed decreases as the degree of ambulatory dysfunction increases. That means that in more affected patients the performed gait speed is not necessarily a reflection of their comfortable walking speed. Taking this discrepancy into account in RCTs on gait interventions could help in improving accuracy and identifying efficacy of interventions on gait capacities.

Fatigue is a cornerstone symptom in pwMS [ 78 ] that likely determines gait pattern and gait functionality in everyday life [ 79 , 80 ]. In our results we can see that 39% of studies assessed this aspect using four different scales. To know which gait rehabilitation intervention minimizes this symptom is central for optimal clinical decision making.

Few studies combined GSTP evaluation with measures of fatigue. This highlights a gap in previous research priorities in RCTs on gait interventions. Fatigue interacts with GSTP, for example, fatigue can be reflected by changes in stride length, gait velocity and stride time [ 81 ]. Future RCTs should therefore combine GSTP and fatigue measurements for a more complete mechanistic understanding.

Participation

Reducing restriction in Participation and obtaining good quality of life is the overall objective of rehabilitation interventions. Quality of life questionnaires provide useful information about this aspect that is identified by therapists as one of the goals of their therapies [ 82 ]. However, Participation was not systematically assessed (only 50% of studies assessed it) and there was considerable heterogeneity in the choice of outcome measures, with 14 different outcome measures for assessing Participation. Assessing this aspect more frequently in RCTs on gait interventions is recommended since this review showed a lack of consensus among researchers on the need to assess this aspect and on which measure to select. Improved consensus here would make it possible to compare the effects of rehabilitation interventions on quality of life across studies more easily.

In our findings, GSTP were combined with Participation assessments in only two studies, showing that most RCTs that focus on objective and fine assessment of gait parameters do not consider the repercussion of the studied intervention on the patient’s specific life context. It is important that future studies on gait interventions combine these measures to extend results on pwMS quality of life, which is the final objective of rehabilitation interventions and enable more comprehensive understanding of intervention effects.

Gait capacities characterized by EDSS

EDSS is widely used for defining participant characteristics [ 65 , 66 , 83 ] and in our results, we observed that different outcome measures were used depending on gait capacities assessed by the EDSS.

Assessment with EDSS have many limitations [ 84 ], and assessments capable of compensating these limitations are needed when assessing gait capacities. Some outcome measures can be challenging for patients with a high EDSS, while others may not be sensitive enough to assess changes in pwMS with high gait capacities. GSTP, for example, were more frequently used in less affected pwMS characterized with a lower EDSS that need a fine assessment to detect changes in gait, since other tests like Timed Up and Go test can have ceiling effects and would not be responsive enough to changes due to rehabilitation interventions. In contrast, Timed Up and Go test, which provides information about gait over short distances and functional aspects like transfers, was used in more affected patients with higher scores in EDSS.

Regarding GSTP in pwMS, absolute and relative reliability of GSTP have been studied [ 71 ] in populations with lower (0–3.5) and higher (4–6) EDSS scores, and this study showed that higher walking disability in pwMS was associated with higher within-subject variability. These results are consistent with our review findings showing that clinical researchers less often chose this kind of assessment in pwMS with lower gait capacities.

Measuring across ICF domains

Comprehensive assessment, with outcome measures spanning all the ICF domains , is counseled by European recommendations in MS rehabilitation (RIMS) [ 16 ], and International Consensus Conference about ICF core sets in MS [ 15 ]. A recent study about goal setting and assessment according to ICF in MS, points out the need to use ICF Core Sets and standardized outcome measures for evaluation at the different ICF levels, both in clinical practice and in research (82). This multidimensional assessment can give information about efficacy of gait interventions on the global status of the pwMS and not only about one specific component. As we can see in our results, only 39% of analyzed clinical trials consider the three domains of the ICF. Covering all ICF domains more systematically in studies will be useful for comparing the global efficacy of physical interventions among studies. Combining Participation measures with GSTP would allow to answer whether gait interventions that improve quality of gait also enhance quality of life of pwMS. The assessment using the ICF framework has also been recommended in other neurological diseases like Parkinson’s [ 85 ], stroke [ 86 ] and also in pediatric pathology [ 87 ].

There are some authors that have already pointed out the need to refine the assessment in MS clinical trials, alluding to the need for multidimensional measures in order to allow full coverage of disease progression and the value of technological measures [ 10 , 80 ]. Nonetheless, our results point to a lack of consensus among researchers as to the best outcome measures to assess gait performance in all ICF domains after gait rehabilitation interventions in MS.

Implications for research

There are literature reviews about measurement properties of gait assessment in people with MS [ 88 ], and some authors have been interested in studying psychometric properties of specific technological devices for assessment in MS [ 11 ]. However, there is still a lack of knowledge of psychometric properties of all technological devices used to assess GSTP in pwMS.

There is a clear need for a systematic review evaluating measurement properties of gait assessment in people with MS, including all technological systems used for assessing GSTP, to recommend specific outcome measures for future studies.

Limitations of the study

In this review we only included RCTs. Data from longitudinal or cross-sectional studies was not included.

We have analyzed the influence of gait capacities on the choice of outcome measures, but we have not analyzed whether the type of MS can influence this choice.

Neither have we analyzed whether the sample of participants in studies could influence the choice of outcome measures.

Another limitation is that we have only included studies on rehabilitation interventions if the aim of the study was to improve gait capacities. There are rehabilitation interventions like balance interventions, vestibular specific interventions or exercise interventions that focus on improving specific aspects other than gait capacities, which can have an influence in gait performance, that are not included in this review.

5. Conclusion

Assessment in pwMS poses a great challenge due to the heterogeneity of symptoms and the progressive changing status of pwMS. This systematic literature review highlights the heterogeneity in choice of outcome measures used in RCTs on gait interventions and the lack of systematic assessment across the whole ICF spectrum. Improved consensus in assessment across studies would help clinicians and researchers interpret results of rehabilitation interventions and facilitate meta-analyses to compare results across studies [ 18 ]. Assessment of the whole ICF spectrum is needed to determine which gait interventions are the most efficient ones to improve capacities at Body structure and Body function, Activity, and Participation levels. A growing consensus was identified for the use of GSTP to evaluate the effects of gait interventions. These measures were often combined with clinical gait, mobility, and balance measures. However, GSTP were rarely combined with measures of fatigue or Participation, highlighting an important gap in research knowledge. Continued efforts are needed to move forward in establishing consensus on selection of outcome measures in clinical trials on gait interventions in MS and assessing psychometric properties of commonly used assessment methods.

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16. European Multiple Sclerosis Platform (EMSP). Recommendations on Rehabilitation Services for Persons with Multiple Sclerosis in Europe. RIMS, Rehabilitation in Multiple Sclerosis 2012. Available from: www.eurims.org/images/stories/documents/Brochures/Recommendations
18. Higgins J, Thomas J, Chandler J, Cumpston M, Li T, Page M, et al. Cochrane Handbook for Systematic Reviews of Interventions 2 nd ed. Chichester UK: Wiley-Blackwell,2019.

A Review on Clinical Gait Analysis

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Role of machine learning in gait analysis: a review

Affiliations.

1 Academy of Scientific and Innovative Research, Ghaziabad, India.
2 Biomedical Instrumentation Unit, CSIR-CSIO, Chandigarh, India.
PMID: 33078988
DOI: 10.1080/03091902.2020.1822940

Human biomechanics and gait form an integral part of life. The gait analysis involves a large number of interdependent parameters that were difficult to interpret due to a vast amount of data and their inter-relations. To simplify evaluation, the integration of machine learning (ML) with biomechanics is a promising solution. The purpose of this review is to familiarise the readers with key directions of implementation of ML techniques for gait analysis and gait rehabilitation. An extensive literature survey was based on research articles from nine databases published from 1980 to 2019. With over 943 studies identified, finally, 43 studies met the inclusion criteria. The outcome reported illustrates that supervised ML techniques showed accuracies above 90% in the identified gait analysis domain. The statistical results revealed support vector machine (SVM) as the best classifier (mean-score = 0.87 ± 0.07) with remarkable generalisation capability even on small to medium datasets. It has also been analysed that the control strategies for gait rehabilitation are benefitted from reinforcement learning and (deep) neural-networks due to their ability to capture participants' variability. This review paper shows the success of ML techniques in detecting disorders, predicting rehabilitation length, and control of rehabilitation devices which make them suitable for clinical diagnosis.

Keywords: Artificial intelligence (AI); gait analysis; gait rehabilitation; machine learning (ML); pathology detection.

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v.15(1); 2018 Mar

Gait analysis methodology for the measurement of biomechanical parameters in total knee arthroplasties. A literature review

Georgios i. papagiannis.

a Orthopaedic Research and Education Center “P.N. Soukakos”, Biomechanics and Gait Analysis Laboratory “Sylvia Ioannou”, “Attikon” University Hospital, 1st Department of Orthopaedics, Medical School, National and Kapodistrian University of Athens, 12462, Greece

Athanasios I. Triantafyllou

Ilias m. roumpelakis, panayiotis j. papagelopoulos, george c. babis.

b Konstantopouleio General Hospital, Nea Ionia, 2nd Department of Orthopaedics, Medical School, National and Kapodistrian University of Athens, 14233 Greece

Gait analysis using external skin markers provides scope for the study of kinematic and kinetic parameters shown on different total knee arthroplasties (TKA). Thus an appropriate methodology is of great importance for the collection and correlation of valid data. Calibration of equipment is of great importance before measurements, to assure accuracy. Force plates should be calibrated to 1080 Hz and optoelectronic cameras should use 120 Hz frequency, because of the nature of gait activity. Davis model which accurately defines the position of the markers is widely accepted and cited, for the gait analysis of TKA’s. To ensure the reproducibility of the measurement, a static trial at the anatomical position must be captured. Following, all acquisitions of dynamic data must be checked for consistency in walking speed, and abnormal gait style because of fatigue or distraction. To establish the repeatability of the measurement, this procedure must be repeated at a pre-defined number of 3–5 gait cycles. Anthropometric measurements should be combined with three-dimensional marker data from the static trial to provide positions of the joint’s center and define anatomical axes of total knee arthroplasty. Kinetic data should be normalized to bodyweight (BW) and percentage of BW and height depending on the study. External moments should also be calculated by using inverse dynamics and amplitude-normalized to body mass (Nm/kg). Gait analysis using external skin markers provides scope for the study of biomechanical parameters shown on different TKAs. Thus a standard gait analysis methodology when measuring TKA biomechanical parameters is necessary for the collection and correlation of accurate, adequate, valid and reproducible data. Further research should be done to clarify if the development of a specific kinematic model is appropriate for a more accurate definition of total knee implant joint center in measurements concerning 3D gait analysis.

1. Background

Both joint kinematics and joint kinetics are important input parameters for total knee arthroplasty wear testing according to International Organization for Standardization (ISO),(ISO 14243-3, ISO 14343-1). 1 , 2 Gait analysis measurements can sufficiently provide these data to scientists. Such parameters can also be correlated to in vitro data (input waveforms) in order to address wear and longevity as well as to provide an integrated aspect for the development of total knee implant designs. Especially in case of knee prosthesis, the behavior of the joint in transversal plane may represent a crucial factor, because the modern knee prosthesis are focused in stabilizing the knee and allow the most natural movements, such as rotation. 3 , 4 Thus the measurement of biomechanical parameters in all three planes is equally important to identify the actual behavior of the arthroplasty and contribute to a more precise design of the implant.

Knee implants development over the past decade has been greatly advanced in designs and the presence of polyethylene bearings has resulted in superior resistance to wear. The polyethylene bearing is one of the major factors involved in wear performance of the knee. More specifically the method of forming the bearing, the choice of polyethylene resin, the sterilization method of choice, any post-sterilization heat treatments and the shelf aging of the polyethylene bearing before implantation, can majorly affect wear performance. Obvious improvements have been made in the polyethylene bearings as a result of sterilization with the use of radiation in an inert environment or with non-irradiation sterilization methods. However, controversy remains over whether it is preferable to highly-crosslink polyethylene bearings in an effort to obtain maximum wear resistance or to use of non-crosslinked polyethylenes to maintain better mechanical properties such as tensile strength and fatigue resistance. Wear can be clinically assessed either from radiographic studies of ongoing patients or from laboratory simulations or through biomechanical assessment such as gait analysis. All of the above represent very demanding tasks and the more exacting the method the fewer number of patients or follow-up duration.

From a biomechanical point of view it would be interesting to study whether wear rate for walking combined with stair climbing would be more severe than for normal walking tests. In such a study, Cottrell et al 5 compared NexGen CR Augmentable (CR) to 5 NexGen Legacy PS (LPS: Zimmer, Warsaw). All specimens were 25 kGy gamma/N2 tibial inserts. Three wear tests were conducted: one using standard gait (ISO 14243-1) and two using a combination of gait plus stairs. The authors concluded that higher wear rates were present in standard gait compared to gait with added bouts of stair climbing. Therefore normal walking appeared to be the best estimate for a ‘worst case’ scenario. Thus our literature review examined studies that approached the biomechanics parameters of TKA’s using gait analysis, that being the most important daily activity for humans.

Gait analysis using external skin markers provides scope for the study of kinematic and kinetic parameters shown on different total knee prostheses. Patients after TKA show altered gait mechanics that developed prior to, or soon after surgery. 6 Patients with TKA walk slower, have less knee flexion excursion during stance, demonstrate lower peak knee flexion during swing phase and altered sagittal plane knee moments compared to controls ( Fig. 1 ). 7 , 8

Kistler force plates calibration.

Previous studies examined level walking patterns in TKA patients. 9 , 10 , 11 , 12 Two recent reviews concluded in agreement that TKA patients walk with a characteristic pattern that differs than that of asymptomatic healthy controls. 13 , 14 When walking at a self-selected speed, TKA patients walk with decreased speed, have shorter stride length, and decreased single support. Kinematic abnormalities are characterized by decreased flexion in both stance and swing. A dynamic and proper knee flexion in weight acceptance (early stance) and before lift-off (late stance) is important to propel smoothly the entire body in the changes of balance between stance and swing phases. 11

Gait analysis after total knee arthroplasty has been assessed in two systematic reviews over the past few years. 15 , 16 These have shown consistently reduced total range of motion in the knee, and reduced range of flexion during stance. There are also indications of knee kinetics alteration, with only one out of three TKA patients in the studies exhibiting a biphasic pattern of sagittal plane moments. More recently, similar results have been reported for reduced knee angle during stance phase, but detailed musculoskeletal modelling has shown that the forces and extension moments developed by the quadriceps are reduced in early stance in TKA. 17 All systematic reviews assessed the findings of the studies without focusing on the gait analysis methodology followed for the data capture.

When an accurate and adequate methodology is followed to minimize as much as possible all sources of errors referred in bibliography, gait analysis procedure can sufficiently calculate the kinematic and kinetic parameters of TKA’s. Thus the purpose of this literature review is to provide an in depth evaluation of the gait analysis methodology followed by researchers for the study of the biomechanical behavior of TKAs.

2. Literature review-Body

In our literature review we tried to identify the basic principles of gait analysis methodology followed by researchers for the assessment of TKAs.

A literature review search database of Pubmed, Medline, EMBASE, AMED and CINAL was conducted using the following relevant keywords and phrases that describe relevant studies: Gait analysis, Total knee arthroplasty, Total knee replacement, Kinetic analysis, Kinematic analysis, Force plates, Optoelectronic cameras, Motion analysis, Gait analysis methodology, TKA biomechanics.

All research teams used clinical evaluation tools prior to data collection. Radiological examination is one of the most common methods used. Wilson and colleagues 18 used radiostereometric analysis (RSA) and double clinical examination of the subjects to ensure accuracy according to Valstar directions. 19 The importance of radiological examination 20 , 21 , 22 lies on the fact that it can accurately evaluate the alignment of the knee and the femoral and tibial component positions. The position of the joint line was determined in anteroposterior films by calculating the distance between the tip of the fibular head and the distal margin of the lateral femoral condyle at 2–3 years postoperatively. 23

The examination of knee range of motion through a standard goniometer took place in almost all studies to ensure that all subjects are suitable for 3D gait analysis examination.

The knee society score ( Table 1 .) was commonly used as clinical evaluation test 22 , 24 too. The test is based on clinical parameters that evaluate pain, range of motion, and stability in the coronal and sagittal plane. It also offers deductions for flexion contractures, extension lag, and misalignment.

The knee society clinical score.

Objective scoring	Score
Pain
None	50
Mild or occasional
Stairs only	45
Walking and stairs	30
Moderate
Occasional	20
Continuous	10
Severe	0

Range of motion (5° = 1 point)	25

Stability
Anteroposterior
<5 mm	10
5–10 mm	5
>10 mm	0
Mediolateral
<5°	15
6–9°	10
10–14°	5
15°	0

Flexion contracture
5–10°	−2
10–15°	−5
16–20°	−10
>20°	−15

Extension lag
<10°	−5
10–20°	−10
20°	−15

Alignment
0–4°	0
5–10°	3 points each degree
11–15°	3 points each degree

Wegrzyn et al 24 assessed knee function postoperatively by evaluating pain, patient’s function and knee motion. Apart from the Knee Society Score (KSS), 25 they used a number of clinical evaluation scores prior to gait analysis (SF-12, 26 Knee Injury and Osteoarthritis Outcome Score (KOOS) and UCLA activity 26 , 27 ).

Yoshida et al. in 2013 28 examined the relationship between the performance of the musculature crossing the knee during loading response in early walking and the persistent quadriceps weakness observed in patients subjected to TKA. The parameters were measured by using gait analysis and the clinical evaluation included besides the examination of active knee ROM, the self-report questionnaires – SF-36 which is used to assess the patients’ health-related quality of life. 17 , 18 , 19 , 20 The same researcher 33 in another gait analysis study of patients undergone total knee arthroplasty, followed the same clinical evaluation methodology and additionally used performance-based functional testing that included the timed up-and-go test (TUG), the stair-climbing test (SCT), and the 6 min walk test (6MW).

Finally Hatfield et al, 21 studied the gait pattern of TKA patients by using 3D gait analysis system. They evaluated their subjects through standard, weight-bearing anteroposterior and lateral radiographs. 34 Their patients were also assessed through a self-reported pain and function at baseline (and at follow-up in the no-TKA group) by using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). 35

Calibration of the equipment used in gait analysis seemed to be important in every study. A few researchers, performed calibration of the laboratory coordinate system (global coordinate system) with respect to the kinematic (optoelectronic cameras’) and kinetic (force plates’) coordinate system following the calibrating process of the corresponding manufacturer. Two more studies 22 , 36 refer such a procedure to assure the accuracy of the measurements as well as to use these data for the computation of each marker’s 3D coordinates.

In three dimensional gait analysis the frequency of the optoelectronic cameras and force plates that are used has to be set to a range that corresponds to the measured activity. Hans Gerber 37 at his study used Kistler force plates and Vicon motion analysis system. The force data were sampled at 1000 Hz. It is mentioned that when the above range of frequency is combined with the center of pressure of the force and corrected by the method introduced by Dettwyler, 38 the accuracy increased to less than ±1 mm on the surface of the plate. The sampling frequency of the cameras corresponds to a maximum of 500 Hz. And thus the accuracy of the system in the measuring volume was ±1 mm.

Although in most studies the kinetic equipment was set to a frequency close to 1 kHz (range 1000–1080 Hz) 22 , 28 , 33 , 39 as in Gerber’s study, the cameras system’s frequency was set in a magnitude different than 500 Hz. Most researches used 100–120 Hz for the kinematic data capture. According to our opinion this range seems to be more reliable for the data capture of gait study, when the acquisitions are performed at the comfortable velocity of the subject.

The most important anthropometric data that are usually collected refer to body mass and body height, knee and ankle joint diameters as well as ASIS distance and pelvic depth, the later measured with a caliper. 22 , 28 , 33 When combined with the kinematic protocol (marker placement) and the static calibration trial, these data can accurately identify joint centers.

The basic concept of a kinematic data model is standardization. Davis model provides an input for the markers’ position and is widely accepted and cited, for the gait analysis of TKA’s. 40 , 41 , 42 The necessary markers that should be placed when Davis protocol is used for the kinematic and kinetic data collection that concerns the TKA joint are:

• 1 marker at each anterior superior iliac spine (ASIS), placed directly over the anterior superior iliac spine,
• 1 marker at the sacrum on the skin mid-way between the posterior superior iliac spines (PSIS),
• 1 marker at each greater trochanter.
• 1 marker at each external femoral condyle attached on the lateral epicondyle of each knee femoral component,
• 1 marker at each peroneus head.
• 1 marker at each lateral malleolus placed on an imaginary line that passes through the transmalleolar axis,
• 1 marker at each head of the fifth metatarsal placed over the fifth metatarsal head and
• 1 marker at each heel. This is placed only for the static trial calibration acquisition on the calcaneous at the same height above the plantar surface of the foot as the toe marker.
• Finally 1 thigh wand is used for each femur that is placed on each leg over the lower lateral 1/3 surface of the thigh, just below the swing of the hand. (The antero-posterior placement of the marker is critical for correct alignment of the knee flexion axis. The position of the marker should be in alignment with the plane that contains the hip and knee joint centers and the knee flexion/extension axis.) and
• 1 tibial wand for each tibia. Similar to the thigh markers, these are placed over the lower 1/3 of the shank to determine the alignment of the ankle flexion axis (The tibial marker should lay in the plane that contains the knee and ankle joint centers and the ankle flexion/extension axis.)

Most researchers used Davis protocol marker placement to identify joint centers usually adding a set of three to four markers attached on an extra rigid thermoplastic shell. Such shells were placed in particular key anatomic positions to ensure an accurate joint center definition by minimizing the markers’ movement artifacts.

Following the appropriate standardized kinematic protocol all researchers proceeded to the static trial calibration procedure. 21 , 28 , 33 , 39 The collected data ensure the reproducibility of the measurement procedure and minimize errors reported in the literature, 43 regarding video capture of external skin markers. A static trial at the anatomical position was captured to ensure that all segments could be correctly reconstructed, before collection of the dynamic trials’ data that were used at the statistical analysis. The data from this trial were used as reference for the calculation of the joint centers and anatomic angles. The participants were instructed to stand in the anatomic position on one of the two force plates, with their feet parallel and 15 cm apart. The static trial procedure allowed for correction of markers’ misalignment. Furthermore, the data from this trial were used as a reference for the definition of zero degrees for the segmental movements in all planes.

Hatfield 21 proceeded to estimate frontal plane alignment. It was calculated by using motion-captured data from a standing calibration trial as the angle formed between 1) the line connecting the anterior superior iliac spine (ASIS) and the center of knee joint and 2) the line connecting the knee and ankle joint centers. In a subset of 35 participants, this angle measure was found to correlate well with alignment obtained from standing full-leg radiographs.

A predefined number of dynamic trials were used in all studies for the kinematic and kinetic data collection. A successful trial is defined as a trial in which the subjects contacted opposing force platforms with each foot, without evidence of targeting. A minimum of three trials is necessary for the repeatability of the measurements. The number of acquisitions that researchers used in our literature review varied from three to ten complete gait cycles, always following these guidelines.

It is necessary for data expression of gait analysis to consider and accept the subjects as rigid bodies. Yoshida calculated the joint angles using rigid body analysis employing Euler angles and so did all researchers. The net joint moments of the hip, knee and ankle calculated with an inverse dynamics procedure, 44 and always normalized to body mass and the anatomical joint coordinate system as described by Grood and Suntay. 45 Kinematic and kinetic data are also time-normalized with regard to the gait cycle. Thus all measurements express internal data (that applied to the subject’s body).

3. Conclusions

The collection of reliable kinetic and kinematic data with the use of optoelectronic cameras and force plates during gait in patients subjected to TKAs is of great importance for total knee implant designs development. The purpose of this literature review was to highlight the most important aspects of gait analysis methodology referred in bibliography. In this study we concluded that gait analysis researches for the measurement of biomechanical parameters of TKAs followed the same methodology as in normal subjects. An important issue is that no specific mention was found about the TKA joint center definition. It seems that all researchers assumed that the anthropometric measurements when combined with the static trial calibration data and the kinematic model used, can accurately calculate the artificial joint’s center and consequently therefore the kinematic and kinetic data are considered to be reliable. It is widely accepted that total knee implants show substantial differences from the normal knee joint biomechanics as well as differences exist among different types of implants (fixed bearing, mobile bearing, etc). Thus further research should be done to clarify if a specific kinematic model should be developed with respect to total knee implant designs specifications when biomechanics parameters are studied through gait analysis.

The importance of gait analysis as a tool for the biomechanical study of total knee implants is clearly identified in many researches. The nature of gait activity requires specific frequency range and calibration of the equipment used. The concept of a standard kinematic data model is an integral part of gait analysis and the development of a specific model for the TKAs joint center definition might be the key factor that would lead to more accurate data collection. To ensure the reproducibility of the measurement a static trial at the anatomical position should be captured, before dynamic acquisition, and combined to anthropometric measurements. This procedure is crucial since it allows for the accurate definition of the joint center and the correction of errors regarding the markers placement. Furthermore the data from the static calibration should correlate to the clinical evaluation test, such as the radiographs, so as to provide a more accurate definition of the joint centers. A predefined number of three to ten dynamic acquisitions should be followed according to all research studies to ensure more reliable data. Finally the kinetic data should be calculated by using inverse dynamics so as to concern forces acting to the subject. Amplitude-normalization to body mass and height should be followed to ensure that the results can be interpreted to population.

The necessity of total knee implant research for the determination of its biomechanical behavior is unquestionable. Several methods have been used to predict the longevity and identify the wear mechanisms that affect TKAs. As new implant designs evolve and other improvements take place, researchers and scientists involved should focus in achieving increased longevity and improved patients’ function, especially among younger patients. Obviously there is a relationship between the longevity of the implant and the functional use of the joint in a patient’s everyday life, since that use reflects the loads and the range of motion that the joint is subjected to. In addition, ultimate breakdown of the prosthesis depends upon these same loads. 46 An accurate way to estimate longevity is via the number of TKAs that require revision each year. Most current data suggests that knee replacements have an annual failure rate between 0.5–1.0%. This adds up to a 90–95% chance of 10 years, and 80–85% of 20 years longevity. Improvements in technology, may improve these rates.

External knee moments (a representative value for load) have been correlated to the medial and lateral wear scar areas of TKA’s since 1986. 47 Nowadays two separate standards for knee joint prosthesis wear testing are recommended from the International Organization for Standardization (ISO). Input based on joint kinematics is described by ISO 14243-3. ISO 14343-1 determines forces as input for TKA wear testing too. 1 , 2 These kinematic and kinetic parameters constitute a significant piece of the biomechanics mosaic since they can be combined with several input waveforms and functional data analysis to provide an integrated insight into wear study and therefore implant longevity. Gait analysis using external skin markers provides scope for the study of these biomechanical parameters shown on different total knee prostheses. Thus a standard gait analysis methodology when measuring TKA biomechanical parameters is necessary for the collection and correlation of accurate, adequate, valid and reproducible data. Further research should be done to clarify if the development of a specific kinematic model is appropriate for a more accurate definition of total knee implant joint center in measurements concerning 3D gait analysis.

Confict of interest

No author associated with this paper declare that they have any conflict of interest.

No funding was received for this study.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

IMAGES

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