Since self-paced treadmills enable more natural gait patterns compared to fixed-speed treadmills we examined the use of a self-paced treadmill as a alternative for overground gait analysis in persons ...after stroke.
Twenty-five persons after stroke (10 males/15 females; 53 ± 12.05 years; 40.72 ± 42.94 months post-stroke) walked at self-selected speed overground (GAITRite, CIR Systems) and on a self-paced treadmill (GRAIL, Motek) in randomized order. Spatiotemporal parameters, variability and symmetry measures were compared using paired-sample t-tests or Wilcoxon Signed Rank tests. Concurrent validity was assessed using intraclass correlation coefficients and Bland-Altman plots. A regression model determined the contribution of the walking velocity to the changes in spatiotemporal parameters.
The velocity on the treadmill was significant lower compared to overground (p < 0.001). This difference predicted the significant changes in other spatiotemporal parameters to varying degrees (27.7%-83.8%). Bland-Altman plots showed large percentage of bias and limits of agreement. Variability and symmetry measures were similar between conditions.
When considering gait analysis in persons after stroke a self-paced treadmill may be a valuable alternative for overground analysis. Although a slower walking velocity, and accompanying changes in other spatiotemporal parameters, should be taken into account compared to overground walking.
Implications for rehabilitation
Considering the advantages regarding space and time, instrumented treadmills provide opportunities for gait assessment and training in a stroke population.
When using self-paced treadmills for clinical gait analysis in persons after stroke, the slower walking velocity and accompanying changes in other spatiotemporal parameters need to be taken into account.
Stroke patients seem to preserve their walking pattern on a self-paced treadmill.
Assessment of pododermatitis, osteoarthritis, and other causes of lameness in penguins can be challenging. Subjective gait analysis using visual observation and response to analgesic therapy can be ...affected by observer variation and caregiver placebo bias. A pressure-sensitive walkway (PSW), however, allows for objective gait analysis and assessment of analgesic therapeutic response. In this study, a 3-m-long PSW was used to analyze gait in 21 adult Humboldt penguins (
). Medical record reviews and comprehensive examinations were performed on all penguins; five penguins were considered abnormal, with either right-sided (
= 3) or bilateral historical lameness-causing disease (
= 2) and were analyzed separately from the normal data set. All penguins walked across the PSW four times and gait parameters (step and stride distances and velocities, maximum force, impulse, and peak pressure) were calculated for each foot in each penguin. Statistical comparisons were made between right and left feet, sexes, and normal and abnormal penguins for each gait parameter. Among normal penguins, there were no significant differences between feet or sex. Left step width was shorter in abnormal penguins than that of normal penguins. Study results established baseline values for Humboldt penguins. This will allow objective monitoring of progression and response to therapy in penguin lameness cases, both current and future. The data also provide a foundation to compare gait parameters with other penguin populations and species.
An important aim of total knee arthroplasty is to achieve functional recovery, which includes post-operative increase in walking speed. Therefore, predicting whether a patient will walk faster or ...slower after surgery is important in TKA, which has not been studied in previous literatures. Who walks faster and who walks slower after TKA? Can we predict these kinds of patients before surgery?
Whether or not a patient walk faster after total knee arthroplasty can be predicted with preoperative characteristics.
In this retrospective cohort study, 128 female patients who underwent staged bilateral total knee arthroplasty were analyzed with gait analysis preoperatively and at postoperative two years. These patients were divided into three different groups according to the percentage of gait speed change after total knee arthroplasty: 1) V(+), more than 10% gait speed increase; 2) V(−), more than 10% gait speed decrease; and 3) V(0), those in-between. Gait parameters, mechanical axis angles, WOMAC pain score and Knee Society scores of the two groups (V(+) and V(−)) were compared. Furthermore, a classification model predicting whether a patient walks faster after total knee arthroplasty was designed using a machine learning algorithm.
After total knee arthroplasty, average gait speed increased by 0.07m/s from 0.87m/s to 0.94m/s (p<0.001) and gait speed increased in 43.8% of the patients (n=56). However, gait speed decreased in a significant number of patients (n=17, 13.3%). When V(+) and V(−) groups were compared, gait speed, cadence, sagittal/coronal knee range of motion, and Knee Society Function score were lower in the V(+) group before surgery, but became higher after surgery. Gait speed change could be predicted using three variables (preoperative gait speed, age, and the magnitude of mechanical axis angle). The area under the receiver operating characteristic curve of the machine learning model was 0.86.
After total knee arthroplasty, gait speed was maintained or increased in most patients. However, gait speed decreased in a significant number of patients. The machine learning classification model showed a good predictive performance, which could aid in the decision-making and the timing of total knee arthroplasty.
III; retrospective cohort study.
Background and Objectives
Gait impairment and reduced mobility are typical features of idiopathic Parkinson's disease (iPD) and atypical parkinsonian disorders (APD). Quantitative gait assessment may ...have value in the diagnostic workup of parkinsonian patients and as endpoint in clinical trials. The study aimed to identify quantitative gait parameter differences in iPD and APD patients using sensor‐based gait analysis and to correlate gait parameters with clinical rating scales.
Subjects and Methods
Patients with iPD and APD including Parkinson variant multiple system atrophy and progressive supranuclear palsy matched for age, gender, and Hoehn and Yahr (≤3) were recruited at two Movement Disorder Units and assessed using standardized clinical rating scales (MDS‐UPDRS‐3, UMSARS, PSP‐RS). Gait analysis consisted of inertial sensor units laterally attached to shoes, generating as objective targets spatiotemporal gait parameters from 4 × 10 m walk tests.
Results
Objective sensor‐based gait analysis showed that gait speed and stride length were markedly reduced in APD compared to iPD patients. Moreover, clinical ratings significantly correlated with gait speed and stride length in APD patients.
Conclusion
Our findings suggest that patients with APD had more severely impaired gait parameters than iPD patients despite similar disease severity. Instrumented gait analysis provides complementary rater independent, quantitative parameters that can be exploited for clinical trials and care.
Our study is the first cross‐sectional study performing an embedded sensor‐based gait analysis in patients with atypical parkinsonian disorders and comparing them to patients with idiopathic Parkinson's disease, matched for global disability, sex and age and to healthy controls. Our results show that sensor‐based gait analysis correlates to clinical rating scores and is able to differentiate patients from controls.
•Movement analysis is applied for the scientific description of gait but also used for clinical evaluation of musculoskeletal conditions.•Analysis methods produce large and complex datasets that ...require profound expertise for interpretation.•Precise selection of the most appropriate measurement technique according to clinical or scientific demands is required.
Movement or gait analysis has become a viable assessment tool not only used in sports science or basic biomechanical research, but has also expanded to be a very valuable instrument in clinical diagnostics, monitoring functional recovery and musculoskeletal rehabilitation. In this context, this method has long been an integral part solely in neurological disorders such as cerebral palsy. However, in the meantime the benefits have also become apparent in other medical areas, such as foot surgery, orthopaedic technology, or in patients after lower limb amputation. These procedures proved to better understand, objectify and quantify the individual causes of gait and movement disorders in order to optimize patient-specific therapy.
Currently we are able to rely on a multitude of available measurement systems. These can either be used in everyday life for simple monitoring of one's own activity or to complement therapeutic approaches in the clinical and scientific environment.
The following review highlights the various fields of movement analysis, including markerless motion capture, marker-based analysis, pedobarography and wearable sensors. Each of these areas presents its own field of application and potential usage as well as the advantages and disadvantages arising in this context.
The following article will give an overview of the type of measurement technology used, the respective fields of application, and the selected parameters and their interpretation possibilities for each of the areas mentioned.
We estimated the severity of cerebellar ataxia by analyzing gait rhythm. We measured the step times in patients with pure cerebellar ataxia and healthy controls and then analyzed the distribution of ...the ratios of adjacent times. Gait rhythm displayed the best adaptation when expressed as the sum of the power law and lognormal distributions in both groups, and the groups could be distinguished by the exponent of the power law distribution, reflecting the fractal property of gait rhythm. Gait rhythm might reflect different features of impairment in patients with cerebellar ataxia, making it a useful continuous scale for cerebellar ataxia.
•We identified a novel pattern of gait rhythm distribution caused by cerebellar ataxia.•A linear combination of power law and lognormal components optimized the fitting of the cumulative gait rhythm distribution.•The power law was indicative of the fractal property of gait rhythm.•The two components correlated SARA kinetic and gait/posture subscores, respectively.•Gait rhythm analysis could provide a useful continuous scale for cerebellar ataxia.
Human gait is a periodic motion of body segments—the analysis of motion and related studies is termed gait analysis. Gait Analysis has gained much popularity because of its applications in clinical ...diagnosis, rehabilitation methods, gait biometrics, robotics, sports, and biomechanics. Traditionally, subjective assessment of the gait was conducted by health experts; however, with the advancement in technology, gait analysis can now be performed objectively and empirically for better and more reliable assessment. State-of-the-art semi-subjective and objective techniques for gait analysis have limitations that can be mitigated using advanced machine learning-based approaches. This paper aims to provide a narrative and a comprehensive analysis of cutting-edge gait analysis techniques and insight into clinical gait analysis. The literature of the previous surveys during the last decade is discussed. This paper presents an elaborated schema, including gait analysis history, parameters, machine learning approaches for marker-based and marker-less analysis, applications, and performance measures. This paper also explores the pose estimation techniques for clinical gait analysis that open future research directions in this area.
•Review on gait analysis including history, parameters, applications, performance measures, traditional and latest approaches•Comparative analysis of previous reviews•Discussion on Marker-Based and Marker-less approaches for gait analysis•Discussion on clinical gait analysis using latest technologies, specifically Pose Estimation•Future directions and open issues discussion in various application areas of gait analysis
For the evaluation of pathological gait, a machine learning-based estimation of the vertical ground reaction force (vGRF) using a low-cost insole is proposed as an alternative to costly force plates. ...However, learning a model for estimation still relies on the use of force plates, which is not accessible in small clinics and individuals. Therefore, this paper presents a force plate-free learning from a single leg stance (SLS) and natural walking measured only by the insoles. This method used a linear least squares regression that fits insole measurements during SLS to body weight in order to learn a model to estimate vGRF during walking. Constraints were added to the regression so that vGRF estimates during walking were of proper magnitude, and the constraint bounds were newly defined as a linear function of stance duration. Moreover, a lower bound for the estimated vGRF in mid-stance was added to the constraints to enhance estimation accuracy. The vGRF estimated by the proposed method was compared with force platforms for 4 healthy young adults and 13 elderly adults including patients with mild osteoarthritis, knee pain, and valgus hallux. Through the experiments, the proposed learning method had a normalized root mean squared error under 10% for healthy young and elderly adults with stance durations within a certain range (600-800 ms). From these results, the validity of the proposed learning method was verified for various users requiring assessment in the field of medicine and healthcare.
In 2014, more than 10 million people in the US were affected by an ambulatory disability. Thus, gait rehabilitation is a crucial part of health care systems. The quantification of human locomotion ...enables clinicians to describe and analyze a patient's gait performance in detail and allows them to base clinical decisions on objective data. These assessments generate a vast amount of complex data which need to be interpreted in a short time period. We conducted a design study in cooperation with gait analysis experts to develop a novel Knowledge-Assisted Visual Analytics solution for clinical Gait analysis (KAVAGait). KAVAGait allows the clinician to store and inspect complex data derived during clinical gait analysis. The system incorporates innovative and interactive visual interface concepts, which were developed based on the needs of clinicians. Additionally, an explicit knowledge store (EKS) allows externalization and storage of implicit knowledge from clinicians. It makes this information available for others, supporting the process of data inspection and clinical decision making. We validated our system by conducting expert reviews, a user study, and a case study. Results suggest that KAVAGait is able to support a clinician during clinical practice by visualizing complex gait data and providing knowledge of other clinicians.
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