scholarly journals Towards Wearable-Inertial-Sensor-Based Gait Posture Evaluation for Subjects with Unbalanced Gaits

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1193 ◽  
Author(s):  
SEN QIU ◽  
Huihui Wang ◽  
Jie Li ◽  
Hongyu Zhao ◽  
Zhelong Wang ◽  
...  
Keyword(s):  
Gait Analysis ◽  
Inertial Sensor ◽  
Strong Support ◽  
3D Models ◽  
Health Condition ◽  
Lower Limbs ◽  
Sensor Nodes ◽  
Human Gait ◽  
Gait Parameters ◽  
Analysis System

Human gait reflects health condition and is widely adopted as a diagnostic basisin clinical practice. This research adopts compact inertial sensor nodes to monitor the functionof human lower limbs, which implies the most fundamental locomotion ability. The proposedwearable gait analysis system captures limb motion and reconstructs 3D models with high accuracy.It can output the kinematic parameters of joint flexion and extension, as well as the displacementdata of human limbs. The experimental results provide strong support for quick access to accuratehuman gait data. This paper aims to provide a clue for how to learn more about gait postureand how wearable gait analysis can enhance clinical outcomes. With an ever-expanding gait database,it is possible to help physiotherapists to quickly discover the causes of abnormal gaits, sports injuryrisks, and chronic pain, and provides guidance for arranging personalized rehabilitation programsfor patients. The proposed framework may eventually become a useful tool for continually monitoringspatio-temporal gait parameters and decision-making in an ambulatory environment.

scholarly journals Concurrent validity and repeatability of inertial sensor gait analysis system for the measurement of gait parameters of young healthy adults

2018 ◽  
Vol 5 (1) ◽  
pp. 1484600 ◽  
Author(s):  
Annukka Myllymäki ◽  
Eliisa Löyttyniemi ◽  
Maria Kaunismäki ◽  
Maiju Pesonen ◽  
Airi Oksanen ◽  
...  
Keyword(s):  
Gait Analysis ◽  
Concurrent Validity ◽  
Inertial Sensor ◽  
Healthy Adults ◽  
Gait Parameters ◽  
Analysis System

Examination of the reliability of an inertial sensor-based gait analysis system

2017 ◽  
Vol 62 (6) ◽  
pp. 615-622 ◽  
Author(s):  
Katja Orlowski ◽  
Falko Eckardt ◽  
Fabian Herold ◽  
Norman Aye ◽  
Jürgen Edelmann-Nusser ◽  
...  
Keyword(s):  
Gait Analysis ◽  
Inertial Sensors ◽  
Inertial Sensor ◽  
Intraclass Correlation ◽  
Correlation Coefficients ◽  
Upper Body ◽  
Initial Contact ◽  
Gait Parameters ◽  
Analysis System ◽  
Almost All

AbstractGait analysis is an important and useful part of the daily therapeutic routine. InvestiGAIT, an inertial sensor-based system, was developed for using in different research projects with a changing number and position of sensors and because commercial systems do not capture the motion of the upper body. The current study is designed to evaluate the reliability of InvestiGAIT consisting of four off-the-shelf inertial sensors and in-house capturing and analysis software. Besides the determination of standard gait parameters, the motion of the upper body (pelvis and spine) can be investigated. Kinematic data of 25 healthy individuals (age: 25.6±3.3 years) were collected using a test-retest design with 1 week between measurement sessions. We calculated different parameters for absolute [e.g. limits of agreement (LoA)] and relative reliability [intraclass correlation coefficients (ICC)]. Our results show excellent ICC values for most of the gait parameters. Midswing height (MH), height difference (HD) of initial contact (IC) and terminal contact (TC) and stride length (SL) are the gait parameters, which did not exhibit acceptable values representing absolute reliability. Moreover, the parameters derived from the motion of the upper body (pelvis and spine) show excellent ICC values or high correlations. Our results indicate that InvestiGAIT is suitable for reliable measurement of almost all the considered gait parameters.

Validation of wearable inertial sensor-based gait analysis system for measurement of spatiotemporal parameters and lower extremity joint kinematics in sagittal plane

2022 ◽  
pp. 095441192110729
Author(s):  
Gunjan Patel ◽  
Rajani Mullerpatan ◽  
Bela Agarwal ◽  
Triveni Shetty ◽  
Rajdeep Ojha ◽  
...  
Keyword(s):  
Gait Analysis ◽  
Motion Analysis ◽  
Motion Capture ◽  
Inertial Sensor ◽  
Joint Kinematics ◽  
Percentage Error ◽  
Motion Capture System ◽  
Spatiotemporal Parameters ◽  
Analysis System ◽  
Motion Capture Systems

Wearable inertial sensor-based motion analysis systems are promising alternatives to standard camera-based motion capture systems for the measurement of gait parameters and joint kinematics. These wearable sensors, unlike camera-based gold standard systems, find usefulness in outdoor natural environment along with confined indoor laboratory-based environment due to miniature size and wireless data transmission. This study reports validation of our developed (i-Sens) wearable motion analysis system against standard motion capture system. Gait analysis was performed at self-selected speed on non-disabled volunteers in indoor ( n = 15) and outdoor ( n = 8) environments. Two i-Sens units were placed at the level of knee and hip along with passive markers (for indoor study only) for simultaneous 3D motion capture using a motion capture system. Mean absolute percentage error (MAPE) was computed for spatiotemporal parameters from the i-Sens system versus the motion capture system as a true reference. Mean and standard deviation of kinematic data for a gait cycle were plotted for both systems against normative data. Joint kinematics data were analyzed to compute the root mean squared error (RMSE) and Pearson’s correlation coefficient. Kinematic plots indicate a high degree of accuracy of the i-Sens system with the reference system. Excellent positive correlation was observed between the two systems in terms of hip and knee joint angles (Indoor: hip 3.98° ± 1.03°, knee 6.48° ± 1.91°, Outdoor: hip 3.94° ± 0.78°, knee 5.82° ± 0.99°) with low RMSE. Reliability characteristics (defined using standard statistical thresholds of MAPE) of stride length, cadence, walking speed in both outdoor and indoor environment were well within the “Good” category. The i-Sens system has emerged as a potentially cost-effective, valid, accurate, and reliable alternative to expensive, standard motion capture systems for gait analysis. Further clinical trials using the i-Sens system are warranted on participants across different age groups.

scholarly journals Assessing the concurrent validity of a gait analysis system integrated into a smart walker in older adults with gait impairments

2019 ◽  
Vol 33 (10) ◽  
pp. 1682-1687 ◽  
Author(s):  
Christian Werner ◽  
Georgia Chalvatzaki ◽  
Xanthi S Papageorgiou ◽  
Costas S Tzafestas ◽  
Jürgen M Bauer ◽  
...  
Keyword(s):  
Gait Analysis ◽  
Gait Speed ◽  
Concurrent Validity ◽  
Stride Length ◽  
Gait Parameters ◽  
Stance Time ◽  
Absolute Agreement ◽  
Analysis System ◽  
Smart Walker ◽  
Gait Impairments

Objective: To assess the concurrent validity of a smart walker–integrated gait analysis system with the GAITRite® system for measuring spatiotemporal gait parameters in potential users of the smart walker. Design: Criterion standard validation study. Setting: Research laboratory in a geriatric hospital. Participants: Twenty-five older adults (⩾65 years) with gait impairments (habitual rollator use and/or gait speed <0.6 m/s) and no severe cognitive impairment (Mini-Mental State Examination ⩾17). Main measures: Stride, swing and stance time; stride length; and gait speed were simultaneously recorded using the smart walker–integrated gait analysis system and the GAITRite system while participants walked along a 7.8-m walkway with the smart walker. Concurrent criterion-related validity was assessed using the Bland–Altman method, percentage errors (acceptable if <30%), and intraclass correlation coefficients for consistency (ICC3,1) and absolute agreement (ICC2,1). Results: Bias for stride, swing and stance time ranged from −0.04 to 0.04 seconds, with acceptable percentage errors (8.7%–23.0%). Stride length and gait speed showed higher bias (meanbias (SD) = 0.20 (0.11) m; 0.19 (0.13) m/s) and not acceptable percentage errors (31.3%–42.3%). Limits of agreement were considerably narrower for temporal than for spatial-related gait parameters. All gait parameters showed good-to-excellent consistency (ICC3,1 = 0.72–0.97). Absolute agreement was good-to-excellent for temporal (ICC2,1 = 0.72–0.97) but only poor-to-fair for spatial-related gait parameters (ICC2,1 = 0.37–0.52). Conclusion: The smart walker–integrated gait analysis system has good concurrent validity with the GAITRite system for measuring temporal but not spatial-related gait parameters in potential end-users of the smart walker. Stride length and gait speed can be measured with good consistency, but with only limited absolute accuracy.

scholarly journals Can an Observational Gait Scale Produce a Result Consistent with Symmetry Indexes Obtained from 3-Dimensional Gait Analysis?: A Concurrent Validity Study

2020 ◽  
Vol 9 (4) ◽  
pp. 926
Author(s):  
Agnieszka Guzik ◽  
Mariusz Drużbicki ◽  
Lidia Perenc ◽  
Justyna Podgórska-Bednarz
Keyword(s):  
Gait Analysis ◽  
Movement Analysis ◽  
Ordinal Scale ◽  
Coefficient Of Determination ◽  
3D Analysis ◽  
3 Dimensional ◽  
Observational Tool ◽  
Gait Parameters ◽  
Flexion Extension ◽  
Analysis System

To investigate whether a simple observational tool may be a substitute to the time-consuming and costly 3-dimensional (3D) analysis, the study applied the Wisconsin Gait Scale (WGS), enabling assessment which is highly consistent with 3D gait parameters in patients after a stroke. The aim of this study was to determine whether, and to what extent, observational information obtained from WGS-based assessment can be applied to predict results of 3D gait analysis for selected symmetry indicators related to spatiotemporal and kinematic gait parameters. Fifty patients at a chronic stage of recovery post-stroke were enrolled in the study. The spatiotemporal and kinematic gait parameters were measured using a movement analysis system. The symmetry index (SI), was calculated for selected gait parameters. The patients’ gait was evaluated by means of the WGS. It was shown that stance % SI, as well as hip and knee flexion-extension range of motion SI can most effectively be substituted by WGS-based estimations (coefficient of determination exceeding 80%). It was shown that information acquired based on the WGS can be used to obtain results comparable to those achieved in 3D assessment for selected SIs of spatiotemporal and kinematic gait parameters. The study confirms that observation of gait using the WGS, which is an ordinal scale, is consistent with the selected aims of 3D assessment. Therefore, the scale can be used as a complementary tool in gait assessment.

scholarly journals Two-dimensional video-based analysis of human gait using pose estimation

2020 ◽  
Author(s):  
Jan Stenum ◽  
Cristina Rossi ◽  
Ryan T. Roemmich
Keyword(s):  
Gait Analysis ◽  
Motion Capture ◽  
Pose Estimation ◽  
Gold Standard ◽  
Three Dimensional ◽  
Human Gait ◽  
Large Set ◽  
Two Dimensional ◽  
Gait Parameters ◽  
Human Gait Analysis

ABSTRACTWalking is the primary mode of human locomotion. Accordingly, people have been interested in studying human gait since at least the fourth century BC. Human gait analysis is now common in many fields of clinical and basic research, but gold standard approaches – e.g., three-dimensional motion capture, instrumented mats or footwear, and wearables – are often expensive, immobile, data-limited, and/or require specialized equipment or expertise for operation. Recent advances in video-based pose estimation have suggested exciting potential for analyzing human gait using only two-dimensional video inputs collected from readily accessible devices (e.g., smartphones, tablets). However, we currently lack: 1) data about the accuracy of video-based pose estimation approaches for human gait analysis relative to gold standard measurement techniques and 2) an available workflow for performing human gait analysis via video-based pose estimation. In this study, we compared a large set of spatiotemporal and sagittal kinematic gait parameters as measured by OpenPose (a freely available algorithm for video-based human pose estimation) and three-dimensional motion capture from trials where healthy adults walked overground. We found that OpenPose performed well in estimating many gait parameters (e.g., step time, step length, sagittal hip and knee angles) while some (e.g., double support time, sagittal ankle angles) were less accurate. We observed that mean values for individual participants – as are often of primary interest in clinical settings – were more accurate than individual step-by-step measurements. We also provide a workflow for users to perform their own gait analyses and offer suggestions and considerations for future approaches.

scholarly journals Two-dimensional video-based analysis of human gait using pose estimation

2021 ◽  
Vol 17 (4) ◽  
pp. e1008935
Author(s):  
Jan Stenum ◽  
Cristina Rossi ◽  
Ryan T. Roemmich
Keyword(s):  
Gait Analysis ◽  
Motion Capture ◽  
Pose Estimation ◽  
Mean Absolute Error ◽  
Three Dimensional ◽  
Absolute Error ◽  
Human Gait ◽  
Two Dimensional ◽  
Gait Parameters ◽  
Human Gait Analysis

Human gait analysis is often conducted in clinical and basic research, but many common approaches (e.g., three-dimensional motion capture, wearables) are expensive, immobile, data-limited, and require expertise. Recent advances in video-based pose estimation suggest potential for gait analysis using two-dimensional video collected from readily accessible devices (e.g., smartphones). To date, several studies have extracted features of human gait using markerless pose estimation. However, we currently lack evaluation of video-based approaches using a dataset of human gait for a wide range of gait parameters on a stride-by-stride basis and a workflow for performing gait analysis from video. Here, we compared spatiotemporal and sagittal kinematic gait parameters measured with OpenPose (open-source video-based human pose estimation) against simultaneously recorded three-dimensional motion capture from overground walking of healthy adults. When assessing all individual steps in the walking bouts, we observed mean absolute errors between motion capture and OpenPose of 0.02 s for temporal gait parameters (i.e., step time, stance time, swing time and double support time) and 0.049 m for step lengths. Accuracy improved when spatiotemporal gait parameters were calculated as individual participant mean values: mean absolute error was 0.01 s for temporal gait parameters and 0.018 m for step lengths. The greatest difference in gait speed between motion capture and OpenPose was less than 0.10 m s−1. Mean absolute error of sagittal plane hip, knee and ankle angles between motion capture and OpenPose were 4.0°, 5.6° and 7.4°. Our analysis workflow is freely available, involves minimal user input, and does not require prior gait analysis expertise. Finally, we offer suggestions and considerations for future applications of pose estimation for human gait analysis.

Two-dimensional video gait analysis: A systematic review of reliability, validity, and best practice considerations

2020 ◽  
Vol 44 (4) ◽  
pp. 245-262
Author(s):  
Alexandria Michelini ◽  
Arezoo Eshraghi ◽  
Jan Andrysek
Keyword(s):  
Systematic Review ◽  
Data Collection ◽  
Gait Analysis ◽  
Motion Capture ◽  
Study Design ◽  
Human Gait ◽  
Two Dimensional ◽  
Specific Patient ◽  
Gait Parameters ◽  
Motion Capture Systems

Background: Motion capture systems are widely used to quantify human gait. Two-dimensional (2D) video systems are simple to use, easily accessible, and affordable. However, their performance as compared to other systems (i.e. three-dimensional (3D) gait analysis) is not well established. Objectives: This work provides a comprehensive review of design specifications and performance characteristics (validity and reliability) of two-dimensional motion capture systems. Study design: Systematic review. Methods: A systematic literature search was conducted in three databases from 1990 to 2019 and identified 30 research articles that met the inclusion/exclusion criteria. Results: Reliability of measurements of two-dimensional video motion capture was found to vary greatly from poor to excellent. Results relating to validity were also highly variable. Comparisons between the studies were challenging due to differences in protocols, instrumentation, parameters assessed, and analyses performed. Conclusions: Variability in performance could be attributed to study design, gait parameters being measured, and technical aspects. The latter includes camera specifications (i.e. resolution and frame rate), setup (i.e. camera position), and analysis software. Given the variability in performance, additional validation testing may be needed for specific applications involving clinical or research-based assessments, including specific patient populations, gait parameters, mobility tasks, and data collection protocols. Clinical relevance This review article provides guidance on the application of 2D video gait analysis in a clinical or research setting. While not suitable in all instances, 2D gait analysis has promise in specific applications. Recommendations are provided about the patient populations, gait parameters, mobility tasks, and data collection protocols.

241 MARKERLESS VISION-BASED HUMAN GAIT ANALYSIS SYSTEM FOR GAIT REHABILITATION

2010 ◽  
Vol 16 ◽  
pp. S69 ◽  
Author(s):  
D. Ristić-Durrant ◽  
A. Leu ◽  
S. Slavnić ◽  
A. Gräser
Keyword(s):  
Gait Analysis ◽  
Human Gait ◽  
Gait Rehabilitation ◽  
Analysis System ◽  
Human Gait Analysis
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