Summary measures for clinical gait analysis: A literature review

doi:10.1016/j.gaitpost.2014.02.001

Gait & Posture

Volume 39, Issue 4, April 2014, Pages 1005-1010

https://doi.org/10.1016/j.gaitpost.2014.02.001 Get rights and content

Highlights

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Gait analysis is important to quantify the gait pattern alterations.
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A typical gait analysis evaluation produces a vast amount of data.
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Several gait summary measures quantify the degree of gait deviation from normal.

Abstract

Instrumented 3D-gait analysis (3D-GA) is an important method used to obtain information that is crucial for establishing the level of functional limitation due to pathology, observing its evolution over time and evaluating rehabilitative intervention effects. However, a typical 3D-GA evaluation produces a vast amount of data, and despite its objectivity, its use is complicated, and the data interpretation is difficult. It is even more difficult to obtain an overview on patient cohorts for a comparison. Moreover, there is a growing awareness of the need for a concise index, specifically, a single measure of the ‘quality’ of a particular gait pattern. Several gait summary measures, which have been used in conjunction with 3D-GA, have been proposed to objectify clinical impression, quantify the degree of gait deviation from normal, stratify the severity of pathology, document the changes in gait patterns over time and evaluate interventions.

Introduction

Three-dimensional instrumented gait analysis (3D-GA) provides comprehensive data on normal and pathological gait, which are useful in clinical practice and scientific purposes because they provide objective information about joint motions (kinematics), time-distance variables (spatio-temporal data), and joint moments and powers (kinetics). It has been widely demonstrated that 3D-GA is an important method that is used to obtain crucial information for the determination of the level of functional limitation due to pathology and for its follow up evaluation over time. Furthermore, it can help to evaluate the rehabilitative intervention aimed at reducing the functional limitation due to pathology. However, a typical 3D-GA evaluation produces a vast amount of data, and despite its objectivity, makes it an instrument that is sometimes complicated to use and difficult to interpret. Specifically, comparative overviews are difficult. There is currently a debate regarding how to best use these data; for example, there is a perspective that the volume of information produced by 3D-GA could be an obstacle for its clinical use. Given the importance of 3D-GA in the management of many populations with movement disorders and because clinical decisions are generally also based on an interpretation of the complex information contained in these data, considerable attention should be directed towards GA data.

Within the last decade, there has been a growing clinical awareness of the need for a concise index, specifically, a single measure of the ‘quality’ of a particular gait pattern. Several gait summary measures, when used in conjunction with 3D-GA, have been proposed and used to objectify clinical impression, quantify the degree of gait deviation from normal, stratify the severity of pathology, document changes in gait over time and evaluate interventions.

The aim of this review is to summarise the studies on the most important and widespread summary parameters proposed by the literature, focusing on studies proposed for clinical applications and discussing the advantages and limits of these parameters.

Section snippets

Methods

To provide a comprehensive overview on gait summary measures, an electronic literature search was performed within the MEDLINE, CINAHL, EMBASE and Journal Citation Reports databases for articles published in english until December 2012 using the following keywords: locomotion, gait analysis, gait summary measures and biomechanics.

Results

From our research, only studies concerning gait summary measures were considered. The first attempt to define a summary measure was performed in 1979 by Tibarewala and Ganguli [1]. In healthy adult males, a number of gait curves defined as “normal’’ gait curves were selected, and a “gait abnormality index’’ was developed to be used as a quantitative measure of human performance in locomotion, which would be suitable for application in pathological states. Some years later, a computer algorithm

Conclusions

The aim of this review paper is to provide an overview of the most frequent gait summary measures that have a clinical application, which were computed starting from 3D-GA. For all indices, after a brief presentation of the calculation methods and the applications on pathological states, their advantages and limitations were discussed.

A discrete number of papers was found on summary measures, but we observed that most of these studies were articles describing the origin and construction of

Conflict of interest

Nothing to declare.

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Cited by (198)

The gait abnormality index: A summary metric for three-dimensional gait analysis
2023, Gait and Posture
This paper proposes an easy to calculate and adaptable summary gait metric, the Gait Abnormality Index (GAI), which is capable of simultaneously including kinematic and kinetic data, overcoming a key limitation of existing metrics.
To determine the validity, reliability and sensitivity of the GAI.
The GAI is calculated by averaging Gait Abnormality Scores, which are normalised distance metrics used to describe the deviation of pathological gait data from that of healthy controls. Validity was assessed using Pearson’s correlation analysis to explore relationships between the GAI and the Gait Profile Score. Test-retest reliability of the GAI was assessed using intra-class correlation coefficients (ICC) and standard error of the measurement (SEM), and data from total hip arthroplasty patients. An independent samples t-test was used to compare GAI scores between knee osteoarthritis and total hip arthroplasty patients to explore the metrics sensitivity.
A strong positive correlation (r ≥ 0.896; p < 001) was reported between the GAI and the Gait Profile Score. Good test-retest reliability (ICC =0.830) was reported for the GAI. Knee osteoarthritis patients displayed significantly (p = .017; Hedge’s g effect size = 0.98) greater GAI scores compared to total hip arthroplasty patients, with the mean difference (0.34 a.u) above the SEM (0.15 a.u).
The GAI offers an easy to calculate summary metric for three-dimensional gait analysis, which displays good validity and reliability, and is sensitive to different pathological conditions.
Relationship between spatiotemporal parameters and clinical outcomes in children with bilateral spastic cerebral palsy: Clinical interpretation proposal
2023, Journal of Orthopaedic Science
Understanding the links between gait disorders, impairments, and activity limitations is essential for correctly interpreting the instrumented gait analysis. We aimed to evaluate the relationships between spatiotemporal parameters and clinical outcomes in children with bilateral spastic cerebral palsy, and find out whether spatiotemporal parameters provide clinical information regarding gait pattern and walking.
Data from 19 children with bilateral spastic cerebral palsy (nine males, ten females, 9.6 ± 2.8 years old) were collected retrospectively. All children underwent an instrumented gait analysis and a standardized clinical assessment. Seven spatiotemporal parameters were calculated: non-dimensional cadence, stride length, step width, gait speed, first double support, single support, and time of toe off. Clinical outcomes included measures of two different components of the International Classification of Functioning, Disability and Health - Children and Youth version: body functions and structures (spasticity, contractures and range of motion, and deformities), and activities and participation (gross motor function, and walking capacity). Pearson correlation, ANOVA, Student’s t, Mann–Whitney U, and Kruskal–Wallis tests were used to analyze relationships. Spatiotemporal parameters related to clinical outcomes of body functions and structures were interpreted as outcome measures of gait pattern, while those related to clinical outcomes of activities and participation were interpreted as outcome measures of walking.
Non-dimensional cadence, stride length, and gait speed showed relationships (p < 0.05) with hip flexors spasticity and hindfoot deformity, ankle plantar flexors spasticity, and hindfoot deformity, respectively. All spatiotemporal parameters except non-dimensional cadence showed correlation (p < 0.05) with gross motor function and walking capacity.
Spatiotemporal parameters provide clinical information regarding both gait pattern and walking.
Influence of the Hawthorne effect on spatiotemporal parameters, kinematics, ground reaction force, and the symmetry of the dominant and nondominant lower limbs during gait
2023, Journal of Biomechanics
The Hawthorne effect is a change in behavior resulting from awareness of being observed or evaluated. This study aimed to determine whether awareness of being evaluated or presence of an observer influence gait. Twenty-one young women were asked to walk in three conditions. In the first condition (unawareness of evaluation; UE), participants were aware that it was a practice trial, and there was no observer. In the second condition (awareness of evaluation; AE), participants were aware that their gait was being evaluated. The third condition (AE + researcher observation; RO) was similar to the second condition except that an additional researcher observed the participant' gait. The spatiotemporal, kinematic, ground reaction forces, and ratio index (symmetry of both lower limbs) were compared among the three conditions. A higher ratio index indicated a relative increase in the value on left versus right. Gait speed (P = 0.012) and stride length (right and left; P = 0.006 and 0.007, respectively) were significantly increased in the AE + RO than in UE. Range of motion of the right hip and left ankle was significantly greater in AE than in UE (P = 0.039 and 0.012, respectively). The ratio index of ground reaction force during push-off was significantly higher in AE and AE + RO conditions than in UE (P < 0.001 and P = 0.004, respectively). The Hawthorne effect (awareness of being evaluated or presence of an observer) potentially influences gait. Thus, factors that influence gait analysis should be considered when evaluating normal gait.
A comprehensive study on codebook-based feature fusion for gait recognition
2023, Information Fusion
Vision-based person identification using gait is one of the important and challenging tasks in the fields of computer vision and machine learning. It has received significant research efforts in the past two decades due to its several benefits. It is non-invasive and can be performed at a distance without active collaboration from users. The identification can be performed from low-resolution videos using simple instrumentation. The conventional gait recognition approaches usually operate on the sequence of extracted human silhouettes. They derive several gait-related features from the segmented binary energy maps of the walker. However, such processes are sensitive to variations in the silhouette shapes, thus limiting their efficacy. Codebook-based feature encoding techniques have been proven to be effective and reported state-of-the-art recognition results on several visual datasets such as action recognition, image, and video classification, etc. The whole process usually follows the pipeline of pattern recognition which mainly consists of five steps: (i) local feature extraction, (ii) feature pre-processing, (iii) codebook computation, (iv) feature encoding, and (v) classification. Each step in the pipeline plays a crucial role in recognition accuracy. Since the visual gait sequences comprise different walking patterns of the subjects due to variations in their static appearance and motion dynamics, several features are extracted to encode this information. Finally, they are fused to recognize the identity of the subject. This paper presents a comprehensive study of codebook-based approaches, explains all the steps in the encoding of visual gait sequences, and uncovers some good practices to obtain state-of-the-art recognition results. In particular, we investigated two different local features to encode the static appearance and motion information of the walker, and twelve kinds of feature encoding methods. An extensive evaluation of these encoding methods is carried out on a large benchmark CASIA-B gait database and their performance comparison is presented.
How many observations in the reference dataset are required to compute a consistent Gait Deviation Index & Gait Profile Score?
2023, Gait and Posture
The Gait Deviation Index (GDI) and the Gait Profile Score (GPS) are the most used scores to sum up gait deviations and are used as primary outcomes in many clinical studies. They are considered as equivalent scores. The computation of these scores is based on a reference dataset but often no description is provided. Among other characteristics, the number of observations needed and its possible influence on the computation of the scores remains unknown.
Define the number of observations needed in the reference dataset to compute consistent and reliable GDI and GPS.
Fifty individuals with cerebral palsy (CP) were randomly selected from our laboratory database. Both scores were computed based on the reference dataset of Schwartz et al. (2008). A bootstrap analysis was performed, for every individual, to assess the effect of the number of observations on both scores. N number of observations were randomly selected, with replacement, from the reference dataset. This procedure was repeated 2000 times for every individual and every N and performed from N = 5 to N = 165 with an increment of 5. The 95 % of the absolute error distribution was considered for every individual and every N. The smallest detectable change (SDC) for both scores was considered as a threshold (GDI: 10.8; GPS:1.3°) to determine the minimum N required.
A minimum of 90 and 20 observations are required to compute consistent GDI and GPS, respectively. The number of observations has a higher impact on the GDI than the GPS, mainly because the GPS calculation does not rely on the standard deviation (SD). Furthermore, the GDI absolute error seems to be higher in individuals with greater gait deviations, i.e. lower GDI value. This effect was not observed on the GPS. In the case of a small reference dataset, the GPS should therefore be preferred.
Inertial measurement unit-based motion capture to replace camera-based systems for assessing gait in healthy young adults: Proceed with caution
2022, Measurement: Sensors
Gait analysis can identify injury-risk markers indiscernible to the naked eye. Inertial measurement unit (IMU)-based motion capture circumvents optokinetic motion capture (OMC) clinical implementation barriers with its portability, increased affordability, and decreased computational burden. We compared an IMU system to a robust OMC marker set for gait analysis. 10 healthy adults walked at self-selected speeds equipped with Noraxon MyoMotion IMUs and a 24-marker, 5-cluster marker-set in view of 14 OMC cameras. A single calibration was applied. IMU system and OMC calculated joint angles were compared. A single calibration performed similarly to previously reported repeated calibration. IMU and OMC agreement was best in the sagittal plane with IMU axis-mixing affecting off-sagittal plane agreement. System differences were greater than 5° for most motions. Measurement system bias showed at the ankle and knee, however differences varied across participants. IMU kinematics should be interpreted with caution; consistency and accuracy must improve before IMUs can replace OMC.

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ReviewSummary measures for clinical gait analysis: A literature review

Highlights

Abstract

Introduction

Section snippets

Methods

Results

Conclusions

Conflict of interest

J Biomed Eng

Gait Posture

Gait Posture

Gait Posture

Gait Posture

Gait Posture

Gait Posture

Gait Posture

Gait Posture

Gait Posture

Res Dev Disabil

Gait Posture

Gait Posture

Gait Posture

Gait Posture

Review
Summary measures for clinical gait analysis: A literature review