scholarly journals Rater agreement for assessment of equine back mobility at walk and trot compared to quantitative gait analysis

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252536
Author(s):  
T. J. P. Spoormakers ◽  
E. A. M. Graat ◽  
F. M. Serra Bragança ◽  
P. R. van Weeren ◽  
H. Brommer
Keyword(s):  
Gait Analysis ◽  
Correlation Coefficients ◽  
Visual Assessment ◽  
Analysis Data ◽  
Rater Agreement ◽  
Veterinary Students ◽  
Visual Evaluation ◽  
Straight Line ◽  
Custom Made ◽  
General Mobility

Background Lameness assessment in horses is still predominantly performed using subjective methods. Visual assessment is known to have moderate to good intra-rater agreement but relatively poor inter-rater agreement. Little is known about inter- and intra-rater agreement on the evaluation of back motion, for which no objective measurement technique in a clinical setting is available thus far. Objectives To describe inter- and intra-rater agreement of visual evaluation of equine back mobility. Study design Rater reliability study using a fully crossed design in which all horses are rated by all observers. This data is compared with objective gait analysis. Methods Seventy equine professionals (veterinarians and physiotherapists) and veterinary students evaluated videos of 12 healthy horses at walk and trot on a hard, straight line. Nine parameters related to back mobility were scored: general mobility, thoracic, lumbar, lumbosacral flexion and extension and left and right thoracolumbar latero-flexion. All parameters were compared with simultaneously measured quantitative motion parameters. After 1 month, six randomly chosen horses were re-evaluated by 57 observers. Results For each parameter inter- and intra-rater agreements were calculated using intra-class correlation coefficients. For all parameters, inter-rater agreement was very poor (<0.2). The mean intra-rater agreement of all observers and for all parameters was poor (~0.4) but varied between 0.0 and 0.96 for individual observers. There was no correlation between the visual subjective scoring and objective gait analysis measurements. Main limitations Horses were scored from videos and by lack of any existing (semi-) quantitative system, a custom-made system had to be used. Conclusions The poor inter- and intra-rater agreements of visual scoring of mobility of the equine back and the disagreement between subjective and objective gait analysis data, demonstrate the need for the development and introduction of objective, quantitative and repeatable techniques to assess equine back motion.

scholarly journals A Validation of Supervised Deep Learning for Gait Analysis in the Cat

2021 ◽  
Vol 15 ◽  
Author(s):  
Charly G. Lecomte ◽  
Johannie Audet ◽  
Jonathan Harnie ◽  
Alain Frigon
Keyword(s):  
Deep Learning ◽  
Gait Analysis ◽  
Correlation Coefficient ◽  
Motion Tracking ◽  
Low Cost ◽  
Intraclass Correlation ◽  
Correlation Coefficients ◽  
Bony Landmarks ◽  
Custom Made ◽  
Adult Cat

Gait analysis in cats and other animals is generally performed with custom-made or commercially developed software to track reflective markers placed on bony landmarks. This often involves costly motion tracking systems. However, deep learning, and in particular DeepLabCutTM (DLC), allows motion tracking without requiring placing reflective markers or an expensive system. The purpose of this study was to validate the accuracy of DLC for gait analysis in the adult cat by comparing results obtained with DLC and a custom-made software (Expresso) that has been used in several cat studies. Four intact adult cats performed tied-belt (both belts at same speed) and split-belt (belts operating at different speeds) locomotion at different speeds and left-right speed differences on a split-belt treadmill. We calculated several kinematic variables, such as step/stride lengths and joint angles from the estimates made by the two software and assessed the agreement between the two measurements using intraclass correlation coefficient or Lin’s concordance correlation coefficient as well as Pearson’s correlation coefficients. The results showed that DLC is at least as precise as Expresso with good to excellent agreement for all variables. Indeed, all 12 variables showed an agreement above 0.75, considered good, while nine showed an agreement above 0.9, considered excellent. Therefore, deep learning, specifically DLC, is valid for measuring kinematic variables during locomotion in cats, without requiring reflective markers and using a relatively low-cost system.

scholarly journals Intra- and Interobserver Reliability Comparison of Clinical Gait Analysis Data between Two Gait Laboratories

2020 ◽  
Vol 10 (15) ◽  
pp. 5068
Author(s):  
René Schwesig ◽  
Regina Wegener ◽  
Christof Hurschler ◽  
Kevin Laudner ◽  
Frank Seehaus
Keyword(s):  
Gait Analysis ◽  
Interobserver Reliability ◽  
Intraclass Correlation ◽  
Correlation Coefficients ◽  
Analysis Data ◽  
Individual Variability ◽  
Intraobserver Reliability ◽  
Single Measure ◽  
Ankle Kinematics ◽  
Clinical Gait Analysis

Comparing clinical gait analysis (CGA) data between clinical centers is critical in the treatment and rehabilitation progress. However, CGA protocols and system configurations, as well as choice of marker sets and individual variability during marker attachment, may affect the comparability of data. The aim of this study was to evaluate reliability of CGA data collected between two gait analysis laboratories. Three healthy subjects underwent a standardized CGA protocol at two separate centers. Kinematic data were captured using the same motion capturing systems (two systems, same manufacturer, but different analysis software and camera configurations). The CGA data were analyzed by the same two observers for both centers. Interobserver reliability was calculated using single measure intraclass correlation coefficients (ICC). Intraobserver as well as between-laboratory intraobserver reliability were assessed using an average measure ICC. Interobserver reliability for all joints (ICCtotal = 0.79) was found to be significantly lower (p < 0.001) than intraobserver reliability (ICCtotal = 0.93), but significantly higher (p < 0.001) than between-laboratory intraobserver reliability (ICCtotal = 0.55). Data comparison between both centers revealed significant differences for 39% of investigated parameters. Different hardware and software configurations impact CGA data and influence between-laboratory comparisons. Furthermore, lower intra- and interobserver reliability were found for ankle kinematics in comparison to the hip and knee, particularly for interobserver reliability.

scholarly journals Deep Convolutional and LSTM Networks on Multi-Channel Time Series Data for Gait Phase Recognition

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 789
Author(s):  
David Kreuzer ◽  
Michael Munz
Keyword(s):  
Gait Analysis ◽  
Time Series Data ◽  
Low Cost ◽  
Analysis Data ◽  
Gait Disorders ◽  
Human Gait ◽  
Series Data ◽  
Ageing Society ◽  
Time Motion ◽  
Gait Phase

With an ageing society comes the increased prevalence of gait disorders. The restriction of mobility leads to a considerable reduction in the quality of life, because associated falls increase morbidity and mortality. Consideration of gait analysis data often alters surgical recommendations. For that reason, the early and systematic diagnostic treatment of gait disorders can spare a lot of suffering. As modern gait analysis systems are, in most cases, still very costly, many patients are not privileged enough to have access to comparable therapies. Low-cost systems such as inertial measurement units (IMUs) still pose major challenges, but offer possibilities for automatic real-time motion analysis. In this paper, we present a new approach to reliably detect human gait phases, using IMUs and machine learning methods. This approach should form the foundation of a new medical device to be used for gait analysis. A model is presented combining deep 2D-convolutional and LSTM networks to perform a classification task; it predicts the current gait phase with an accuracy of over 92% on an unseen subject, differentiating between five different phases. In the course of the paper, different approaches to optimize the performance of the model are presented and evaluated.

scholarly journals Method for instrumentation of orthotic joints for measurement of internal joint loads

2017 ◽  
Vol 3 (1) ◽  
pp. 35-38
Author(s):  
David Hochmann ◽  
Lucien Opitz
Keyword(s):  
Gait Analysis ◽  
Cross Talk ◽  
Inertial Sensors ◽  
Small Sample Size ◽  
Fem Simulation ◽  
Small Sample ◽  
Safety Testing ◽  
Internal Joint ◽  
Custom Made ◽  
Joint Loads

Abstract:Introduction:The lack of knowledge of mechanical loads in orthotic joints can lead to oversized or breaking components. Previous studies suffer from small sample size and technical limitations. The goal of this study was to develop and validate a method that allows the direct measurement of moments in sagittal, frontal and transverse planes in knee and ankle joints of existing custom made orthoses.Methods:We developed a modular measurement system based on standard joint components, which were instrumented with strain gauges. To ensure sufficient signals and reduce cross talk an iterative approach based on FEM simulation was utilized. The system also contains inertial sensors for mobile gait analysis.Results:Instrumented joints show good results regarding linearity, hysteresis and cross talk. First pilot trials with post-polio and ICP patients demonstrated that joint loads depend on several factors and not solely on body weight. If combined with conventional gait analysis, measurement results can characterize the individual muscle situation of the patient.Conclusion:A novel method for obtaining data on loads in orthotic components was developed and validated. It provides the basis to develop safety testing standards and clinical guidelines, as well as allowing individual optimization of orthotic devices.

scholarly journals Evaluation of a treadmill with integrated force plates for kinetic gait analysis of sound and lame dogs at a trot

2006 ◽  
Vol 19 (04) ◽  
pp. 205-212 ◽  
Author(s):  
N. M. M. Moens ◽  
J. R. Runciman ◽  
N. S. Brebner
Keyword(s):  
Gait Analysis ◽  
Correlation Coefficients ◽  
Force Platform ◽  
Target Velocity ◽  
Vertical Force ◽  
Belt Speed ◽  
Hind Limbs ◽  
The Mean ◽  
Good Concordance

SummaryThe objective was to compare mean peak vertical force (PVF) obtained with a treadmill with two integrated force plates (TM) with the piezoelectric force platform (FP) for sound and lame dogs at a trot. The aim was also to report the inter-step variability (ISV) for both systems and the effect of lameness on these values. Six sound dogs (20.0–25.5 kg) and six dogs with a grade 2/5 forelimb lameness (17.0–36.1 kg) were used in the study. Dogs were acclimatized and assigned an individual target velocity (1.8–2.2 m/s). Mean PVF measurements were obtained for both TM and FP. Subject velocity was controlled by belt speed on TM and restricted to 0.25 M/s above or below the assigned target velocity for FP. Acceleration was limited to +/- 0.3 M/s2. For the sound dogs, concordance and correlation coefficients of the mean PVF for the front limbs was 0.79 and 0.76, respectively. Concordance and correlation for the rear limbs was 0.90 and 0.81, respectively. For the lame dogs, concordance and correlation for the front limbs was 0.73 and 0.59, respectively. Concordance and correlation for the rear limbs was 0.89 and 0.95, respectively. ISV was 0.94 with TM and 0.84 with FP for the sound dogs and 0.96 with TM and 0.87 with FP for the lame dogs. In conclusion, TM provided rapid PVF measurements, good concordance for the hind limbs, and substantial concordance for the forelimbs in both sound and lame dogs at a trot as compared to FP. Both systems demonstrated excellent ISV for both lame and sound dogs.

scholarly journals RISK ANALYSIS OF INEFFICIENCY AT UKRAINE’S MACHINE BUILDING ENTERPRISES

2019 ◽  
Vol 2019 (3) ◽  
pp. 22-34
Author(s):  
Maryna AFANASIEVA ◽  
Keyword(s):  
Production Efficiency ◽  
Rank Correlation ◽  
Correlation Coefficients ◽  
Value Added ◽  
Risk Groups ◽  
Analysis Data ◽  
Risk Identification ◽  
Machine Building ◽  
Distribution Law ◽  
Market Capture

The paper considers the risk identification of inefficiency concerning 51 Ukrainian joint-stock companies of machine building in 2012–2017. The value added at factor cost (VA) is determined as the resulting indicator of production efficiency, which is a source of income of various social groups, so it contributes to combined efforts. To support advanced production and management technologies, rather than an extensive market capture, the multiplicative model of VA has been suggested with the VA share in output to assess the quality processes within the enterprise. Economic analysis of the annual public financial statements and the structural statistics were conducted to study proportion between the cost elements in sum of expenses with link to profit in net turnover for the main operating activity. As a result the models of two types of risk coefficient have been proposed. It has been verified by statistical analysis. Data were checked on submission to normal distribution law by Shapiro – Wilk test and homogeneity by coefficient of variation. With the help of nonparametric analysis of variance by Kruskal – Wallis test and Spearman rank correlation coefficients; it has been proved that risk groups differ from other enterprises and from each other statistically significantly. We conclude that 37% of the sample enterprises are risky; a third of this is the large and medium-sized companies. Advantages of the method in comparison with Ward clusterization were shown. When making decisions about resource allocation, it should be confirmed that the enterprise is risk-free according to algorithms provided. To improve situation it needs to apply sustainable development concept.

Abstract 3426: Approximate Volume Using "XYZ/2" Is Equivalent to Planimetric Volume Mismatch Evaluation

Stroke ◽  
2012 ◽  
Vol 43 (suppl_1) ◽  
Author(s):  
Marie Luby ◽  
Jennifer Hong ◽  
José G Merino ◽  
John K Lynch ◽  
Amie W Hsia ◽  
...  
Keyword(s):  
Positive Predictive Value ◽  
Predictive Value ◽  
Gold Standard ◽  
Correlation Coefficients ◽  
High Sensitivity ◽  
Evaluation Methods ◽  
Slice Thickness ◽  
Linear Measurements ◽  
Visual Evaluation ◽  
Volume Measurements

Objectives: In the clinical setting, the extent of mismatch on MRI is frequently assessed with an approximate “XYZ/2” method but the agreement with the “gold standard” planimetric volume and the “visual evaluation” methods are not known. In a published study, we established that the visual evaluation and planimetric methods are equivalent as far as mismatch classification. The objectives of this study were to quantify the agreement of the approximate method with the “gold standard” and “visual evaluation” methods and to compare the mismatch classification results. Methods: Patients were selected from the Lesion Evolution of Stroke and Ischemia On Neuroimaging (LESION) database if they: had an acute ischemic stroke, were treated with intravenous rt-PA only, and had a pre-treatment MRI with evaluable maps including trace or isotropic b1000 DWI and MTT images. A trained rater viewed the images on the PACS, placed the two perpendicular linear measurements, “X” and “Y”, on the slices with the largest DWI and MTT lesion areas, and then used a “XYZ/2” formula where “Z” was the product of the slice thickness and the total number of slices containing the lesion. A separate expert rater measured the planimetric volumes on a slice-by-slice basis with a semiautomated segmentation tool followed by manual editing. Expert readers evaluated the MRI scans for the presence of qualitative mismatch. The expert readers were not the trained reader that performed the approximate volume measurements. Quantitative mismatch was considered present if MTT volume - DWI volume ≥50 ml. Mismatch classifications using the ≥ 50 ml definition were compared by constructing contingency tables. Results: A total of 194 patients met the study criteria and had median DWI and MTT planimetric volumes of 13.06 ml and 99.27 ml respectively. For both the DWI (n=170) and MTT (n=164), 94% of the measurements were within two standard deviations of the difference between the planimetric and approximate volume measurements. Comparing the planimetric and approximate volume measurements, the Spearman correlation coefficients were 0.855 and 0.886 for the DWI and MTT measurements respectively (p<0.01). Compared to the planimetric method, the approximate “XYZ/2” method had a high sensitivity (0.91), specificity (0.80), accuracy (0.86) and positive predictive value (0.85) to detect mismatch using the ≥ 50 ml definition. Compared to the qualitative method, the approximate “XYZ/2” method had a sensitivity (0.77), specificity (0.76), accuracy (0.77) and positive predictive value (0.87) to detect mismatch using the ≥ 50 ml definition. Conclusions: The approximate “XYZ/2” method is sufficient for classifying the presence of MRI determined mismatch in acute stroke patients and therefore is a potential tool when using MRI determined mismatch as an inclusion criteria for clinical trials.

scholarly journals Agreement of Gait Events Detection during Treadmill Backward Walking by Kinematic Data and Inertial Motion Units

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6331
Author(s):  
Uri Gottlieb ◽  
Tharani Balasukumaran ◽  
Jay R. Hoffman ◽  
Shmuel Springer
Keyword(s):  
Gait Analysis ◽  
Balance Control ◽  
Analysis Data ◽  
Inertial Motion ◽  
Unique Challenge ◽  
Backward Walking ◽  
Orthopedic Rehabilitation ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Events Detection

Backward walking (BW) is being increasingly used in neurologic and orthopedic rehabilitation as well as in sports to promote balance control as it provides a unique challenge to the sensorimotor control system. The identification of initial foot contact (IC) and terminal foot contact (TC) events is crucial for gait analysis. Data of optical motion capture (OMC) kinematics and inertial motion units (IMUs) are commonly used to detect gait events during forward walking (FW). However, the agreement between such methods during BW has not been investigated. In this study, the OMC kinematics and inertial data of 10 healthy young adults were recorded during BW and FW on a treadmill at different speeds. Gait events were measured using both kinematics and inertial data and then evaluated for agreement. Excellent reliability (Interclass Correlation > 0.9) was achieved for the identification of both IC and TC. The absolute differences between methods during BW were 18.5 ± 18.3 and 20.4 ± 15.2 ms for IC and TC, respectively, compared to 9.1 ± 9.6 and 10.0 ± 14.9 for IC and TC, respectively, during FW. The high levels of agreement between methods indicate that both may be used for some applications of BW gait analysis.

123I-FP-CIT SPECT imaging of the dopaminergic state

2012 ◽  
Vol 51 (06) ◽  
pp. 244-251 ◽  
Author(s):  
C. Eggers ◽  
A. Holstein ◽  
C. Schneider ◽  
D. J. Pedrosa ◽  
M. Dietlein ◽  
...  
Keyword(s):  
Quantitative Analysis ◽  
Single Photon ◽  
Photon Emission ◽  
Visual Assessment ◽  
Emission Computed Tomography ◽  
Rater Agreement ◽  
Automated Method ◽  
Atypical Parkinsonian Syndrome ◽  
Study Results ◽  
Dopaminergic Degeneration

Summary123I-N-ω-fluoropropyl-2β-carbomethoxy-3β- (4-iodophenyl)nortropan (123I-FP-CIT) single photon emission computed tomography (SPECT) can be evaluated by both visual assessment and quantitative analysis to assess the striatal dopamine state in vivo. The aim of our study was to investigate if visual assessment according to a predefined image grading scale reflects the results of quantitative assessment techniques. Patients, methods: 195 patients with a clinical diagnosis of idiopathic Parkinson's disease (n = 134), atypical parkinsonian syndrome (n = 47) or essential tremor (n = 14) were examined with 123I-FP-CIT SPECT and included in this retrospective study. Results were analysed according to predefined visual patterns of dopaminergic degeneration and graded as normal (grade 5) or abnormal (grade 1–4) independently by three raters. Quantitative two-dimensional (2D) operator-dependent, manual and three-dimensional (3D) operator- independent, automated approaches were used for quantitative analysis of the specific 123I-FP-CIT tracer binding ratio (SBR) for caudate and putamen. Results: Sensitivity, specificity, PPV, NPV and diagnostic accuracy of visual assessment of 123I-FP-CIT SPECT for the diagnosis of a neuro degenerative Parkinson's syndrome were 99%, 86%, 99%, 86% and 98%, respectively. Visual assessment and quantitative analysis agreed well in evaluating the degree of dopaminergic degeneration. Significant differences (p < 0.001) were found between degeneration patterns. Only between the so-called eagle wing degeneration and the normal pattern no significant differences in SBR caudate and putamen were found, neither by the quantitative manual (p = 1.00; p = 0.196) nor by the quantitative automated method (p = 1.0; p = 0.785). Inter-rater agreement for visual assessment was substantial for all possible pairs of the three raters (κ = 0.70 to 0.74). Strong correlations were observed between the quantitative manual and quantitative automated methods for quantification of SBR caudatum (r = 0.920, r2 = 0.846, p < 0.001) and SBR putamen (r = 0.908, r2 = 0.824, p < 0.001). Conclusion: Visual assessment was highly consistent with the results obtained by quantitative analysis and showed a substantial inter-rater agreement between experienced and inexperienced raters. Our findings indicate that visual assessment might be a reliable analysis approach for clinical routine.

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