scholarly journals Inertial Measurement Unit-Based Estimation of Foot Trajectory for Clinical Gait Analysis

2019 ◽  
Author(s):  
Yumi Ono ◽  
Koyu Hori ◽  
Hiroki Ora ◽  
Yuki Hirobe ◽  
Yufeng Mao ◽  
...  
Keyword(s):  
Gait Analysis ◽  
Motion Capture ◽  
Stride Length ◽  
Wearable Sensors ◽  
Analysis Method ◽  
Inertial Measurement ◽  
Gait Parameters ◽  
Stride Duration ◽  
Stance Duration ◽  
Foot Trajectory

AbstractGait analysis is used widely in clinical practice for the evaluation of abnormal gait caused by disease. Conventionally, medical professionals use motion capture systems or make visual observations to evaluate a patient’s gait. Recent biomedical engineering studies have proposed easy-to-use gait analysis methods involving wearable sensors with inertial measurement units (IMUs). IMUs placed on the shanks just above the ankles allow for the long-term monitoring of gait because the participant can walk with or without shoes during the analysis. As far as the authors know, there is no report of the gait analysis method that estimates stride length, gait speed, stride duration, stance duration, and swing duration at the same time. In this study, we tested a proposed gait analysis method that uses IMUs attached on the shanks to estimate foot trajectory and temporal gait parameters. We evaluated this proposed method by analyzing the gait of 10 able-bodied participants (mean age 23.1 years, nine men and one woman). Wearable sensors were attached to the participants’ shanks, and we measured three-axis acceleration and three-axis angular velocity with the sensors to estimate foot trajectory during walking. We compared gait parameters estimated from the foot trajectory obtained with the proposed method and those measured with a motion capture system. Mean accuracy (mean ± standard deviation) was –0.046 ± 0.026 m for stride length, –0.036 ± 0.026 m/s for gait speed, –0.002 ± 0.019 s for stride duration, –0.000 ± 0.016 s for stance duration, and –0.002 ± 0.022 s for swing duration. These results suggest that the proposed method is useful for evaluation of clinical gait parameters.

scholarly journals Estimation of stride-by-stride spatial gait parameters using inertial measurement unit attached to the shank with inverted pendulum model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yufeng Mao ◽  
Taiki Ogata ◽  
Hiroki Ora ◽  
Naoto Tanaka ◽  
Yoshihiro Miyake
Keyword(s):  
Motion Capture ◽  
Inertial Measurement Unit ◽  
Stride Length ◽  
Inverted Pendulum ◽  
Previous Method ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Inverted Pendulum Model ◽  
Gait Parameters ◽  
Pendulum Model

AbstractInertial measurement unit (IMU)-based gait analysis systems have become popular in clinical environments because of their low cost and quantitative measurement capability. When a shank is selected as the IMU mounting position, an inverted pendulum model (IPM) can accurately estimate its spatial gait parameters. However, the stride-by-stride estimation of gait parameters using one IMU on each shank and the IPMs has not been validated. This study validated a spatial gait parameter estimation method using a shank-based IMU system. Spatial parameters were estimated via the double integration of the linear acceleration transformed by the IMU orientation information. To reduce the integral drift error, an IPM, applied with a linear error model, was introduced at the mid-stance to estimate the update velocity. the gait data of 16 healthy participants that walked normally and slowly were used. The results were validated by comparison with those extracted from an optical motion-capture system; the results showed strong correlation ($$r>0.9$$ r > 0.9 ) and good agreement with the gait metrics (stride length, stride velocity, and shank vertical displacement). In addition, the biases of the stride length and stride velocity extracted using the motion capture system were smaller in the IPM than those in the previous method using the zero-velocity-update. The error variabilities of the gait metrics were smaller in the IPM than those in the previous method. These results indicated that the reconstructed shank trajectory achieved a greater accuracy and precision than that of previous methods. This was attributed to the IPM, which demonstrates that shank-based IMU systems with IPMs can accurately reflect many spatial gait parameters including stride velocity.

scholarly journals Validation of a Sensor-Based Gait Analysis System with a Gold-Standard Motion Capture System in Patients with Parkinson’s Disease

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7680
Author(s):  
Verena Jakob ◽  
Arne Küderle ◽  
Felix Kluge ◽  
Jochen Klucken ◽  
Bjoern M. Eskofier ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Gait Analysis ◽  
Motion Capture ◽  
Gold Standard ◽  
Wearable Sensors ◽  
Heel Strike ◽  
Motion Capture System ◽  
Gait Parameters ◽  
Analysis System

Digital technologies provide the opportunity to analyze gait patterns in patients with Parkinson’s Disease using wearable sensors in clinical settings and a home environment. Confirming the technical validity of inertial sensors with a 3D motion capture system is a necessary step for the clinical application of sensor-based gait analysis. Therefore, the objective of this study was to compare gait parameters measured by a mobile sensor-based gait analysis system and a motion capture system as the gold standard. Gait parameters of 37 patients were compared between both systems after performing a standardized 5 × 10 m walking test by reliability analysis using intra-class correlation and Bland–Altman plots. Additionally, gait parameters of an age-matched healthy control group (n = 14) were compared to the Parkinson cohort. Gait parameters representing bradykinesia and short steps showed excellent reliability (ICC > 0.96). Shuffling gait parameters reached ICC > 0.82. In a stridewise synchronization, no differences were observed for gait speed, stride length, stride time, relative stance and swing time (p > 0.05). In contrast, heel strike, toe off and toe clearance significantly differed between both systems (p < 0.01). Both gait analysis systems distinguish Parkinson patients from controls. Our results indicate that wearable sensors generate valid gait parameters compared to the motion capture system and can consequently be used for clinically relevant gait recordings in flexible environments.

scholarly journals Accuracy Verification of Spatio-Temporal and Kinematic Parameters for Gait Using Inertial Measurement Unit System

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1343 ◽  
Author(s):  
Sang Seok Yeo ◽  
Ga Young Park
Keyword(s):  
Gait Analysis ◽  
Motion Capture ◽  
Inertial Measurement Unit ◽  
Wearable Sensors ◽  
Measurement Unit ◽  
Kinematic Parameters ◽  
Accurate Analysis ◽  
Inertial Measurement ◽  
Two Systems ◽  
Spatio Temporal

Inertial measurement unit systems are wearable sensors that can measure the movement of a human in real-time with relatively little space and high portability. The purpose of this study was to investigate the accuracy of the inertial measurement unit (IMU) system for gait analysis by comparing it with measurements obtained using an optical motion capture (OMC) system. To compare the accuracies of these two different motion capture systems, the Spatio-temporal and kinematic parameters were measured in young adults during normal walking. Thirty healthy participants participated in the study. Data were collected while walking 5 strides on a 7 m walkway at a self-selected speed. Results of gait analysis showed that the Spatio-temporal (stride time, stride length, cadence, step length) and kinematic (knee joint peak to peak of movement) parameters were not significantly different in the participant. Spatio-temporal and kinematic parameters of the two systems were compared using the Bland–Altman method. The results obtained showed that the measurements of Spatio-temporal and kinematic parameters of gait by the two systems were similar, which suggested that IMU and OMC systems could be used interchangeably for gait measurements. Therefore, gait analysis performed using the wearable IMU system might efficiently provide gait measurements and enable accurate analysis.

The Feasibility and Effectiveness of Wearable Sensor Technology in the Management of Elderly Diabetics with Foot Ulcer Remission: A Proof-Of-Concept Pilot Study with Six Cases

Gerontology ◽  
2021 ◽  
pp. 1-10
Author(s):  
Chenzhen Du ◽  
Hongyan Wang ◽  
Heming Chen ◽  
Xiaoyun Fan ◽  
Dongliang Liu ◽  
...  
Keyword(s):  
Odds Ratio ◽  
Stride Length ◽  
Wearable Sensors ◽  
Foot Ulcer ◽  
Wearable Devices ◽  
Foot Ulcers ◽  
Diabetic Patients ◽  
Wearable Sensor ◽  
Double Support ◽  
Gait Parameters

Aims: Using specials wearable sensors, we explored changes in gait and balance parameters, over time, in elderly patients at high risk of diabetic foot, wearing different types of footwear. This assessed the relationship between gait and balance changes in elderly diabetic patients and the development of foot ulcers, in a bid to uncover potential benefits of wearable devices in the prognosis and management of the aforementioned complication. Methods: A wearable sensor-based monitoring system was used in middle-elderly patients with diabetes who recently recovered from neuropathic plantar foot ulcers. A total of 6 patients (age range: 55–80 years) were divided into 2 groups: the therapeutic footwear group (n = 3) and the regular footwear (n = 3) group. All subjects were assessed for gait and balance throughout the study period. Walking ability and gait pattern were assessed by allowing participants to walk normally for 1 min at habitual speed. The balance assessment program incorporated the “feet together” standing test and the instrumented modified Clinical Test of Sensory Integration and Balance. Biomechanical information was monitored at least 3 times. Results: We found significant differences in stride length (p < 0.0001), stride velocity (p < 0.0001), and double support (p < 0.0001) between the offloading footwear group (OG) and the regular footwear group on a group × time interaction. The balance test embracing eyes-open condition revealed a significant difference in Hip Sway (p = 0.004), COM Range ML (p = 0.008), and COM Position (p = 0.004) between the 2 groups. Longitudinally, the offloading group exhibited slight improvement in the performance of gait parameters over time. The stride length (odds ratio 3.54, 95% CI 1.34–9.34, p = 0.018) and velocity (odds ratio 3.13, 95% CI 1.19–8.19, p = 0.033) of OG patients increased, converse to the double-support period (odds ratio 6.20, 95% CI 1.97–19.55, p = 0.002), which decreased. Conclusions: Special wearable devices can accurately monitor gait and balance parameters in patients in real time. The finding reveals the feasibility and effectiveness of advanced wearable sensors in the prevention and management of diabetic foot ulcer and provides a solid background for future research. In addition, the development of foot ulcers in elderly diabetic patients may be associated with changes in gait parameters and the nature of footwear. Even so, larger follow-up studies are needed to validate our findings.

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 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.

scholarly journals Instrumented gait analysis defines the walking signature of CACNA1A disorders

2021 ◽  
Author(s):  
Elisabetta Indelicato ◽  
Cecilia Raccagni ◽  
Sarah Runer ◽  
Julius Hannink ◽  
Wolfgang Nachbauer ◽  
...  
Keyword(s):  
Gait Analysis ◽  
Wearable Sensors ◽  
Step Length ◽  
Ankle Motion ◽  
Assessment Protocol ◽  
Gait Parameters ◽  
Ambulatory Patients ◽  
Gait Disturbances ◽  
Specific Scale ◽  
Instrumented Gait Analysis

Abstract Background Gait disturbances are a frequent symptom in CACNA1A disorders. Even though, data about their severity and progression are lacking and no CACNA1A-specific scale or assessment for gait is available. Methods We applied a gait assessment protocol in 20 ambulatory patients with genetically confirmed CACNA1A disorders and 39 matched healthy controls. An instrumented gait analysis (IGA) was performed by means of wearable sensors in basal condition and after a treadmill/cycloergometer challenge in selected cases. Results CACNA1A patients displayed lower gait speed, shorter steps with increased step length variability, a reduced landing acceleration as well as a reduced range of ankle motion compared to controls. Furthermore, gait-width in patients with episodic CACNA1A disorders was narrower as compared to controls. In one patient experiencing mild episodic symptoms after the treadmill challenge, the IGA was able to detect a deterioration over all gait parameters. Conclusions In CACNA1A patients, the IGA with wearable sensors unravels specific gait signatures which are not detectable at naked eye. These features (narrow-based gait, lower landing acceleration) distinguish these patients from other ataxic disorders and may be target of focused rehabilitative interventions. IGA can potentially be applied to monitor the neurological fluctuations associated with CACNA1A disorders.

scholarly journals Concurrent Validity of a Commercial Wireless Trunk Triaxial Accelerometer System for Gait Analysis

2019 ◽  
Vol 28 (6) ◽  
Author(s):  
Roel De Ridder ◽  
Julien Lebleu ◽  
Tine Willems ◽  
Cedric De Blaiser ◽  
Christine Detrembleur ◽  
...  
Keyword(s):  
Correlation Coefficient ◽  
Intraclass Correlation Coefficient ◽  
Concurrent Validity ◽  
Stride Length ◽  
Intraclass Correlation ◽  
Sensor System ◽  
Double Support ◽  
Spatiotemporal Parameters ◽  
Stride Duration ◽  
Stance Duration

Context: Wearable sensor devices have notable advantages, such as cost-effectiveness, easy to use, and real-time feedback. Wirelessness ensures full-body motion, which is required during movement in a challenging environment such as during sports. Research on the reliability and validity of commercially available systems, however, is indispensable. Objective: To confirm the test–retest reliability and concurrent validity of a commercially available body-worn sensor—BTS G-WALK® sensor system—for spatiotemporal gait parameters with the GAITRite® walkway system as golden standard. Design: Reliability and concurrent validity study. Setting: Laboratory setting. Participants: Thirty healthy subjects. Main Outcome Measures: Spatiotemporal parameters: speed, cadence, stride length, stride duration, stance duration, swing duration, double support, and single support. Results: In terms of test–retest reliability of the BTS G-WALK® sensor system, intraclass correlation coefficient values for both the spatial and temporal parameters were excellent between consecutive measurements on the same day with intraclass correlation coefficient values ranging from .85 to .99. In terms of validity, intraclass correlation coefficient values between measurement systems showed excellent levels of agreement for speed, cadence, stride length, and stride duration (range = .88–.97), and showed poor to moderate levels of agreement (range = .12–.47) for single/double support and swing/stance duration. Bland–Altman plots showed overall percentage bias values equal to or smaller than 3% with limits of agreement ≤15% (speed, cadence, stride length, stride duration, swing duration, and stance duration). Only for single and double support, the limits of agreement were higher with, respectively, −15.4% to 19.5% and −48.0% to 51.4%. Conclusion: The BTS G-WALK® sensor system is reliable for all measured spatiotemporal parameters. In terms of validity, excellent concurrent validity was shown for speed, cadence, stride length, and stride duration. Cautious interpretation is necessary for temporal parameters based on final foot contact (stance, swing, and single/double support time).

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.

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