The efficacy of a video-based marker-less tracking system for gait analysis (original) (raw)
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Repeated measures of adult normal walking using a video tracking system
Gait & Posture, 1997
The reproducibility of quantitative gait analysis measurements is an important consideration when analyzing data of both normal subjects and patients. Waveform similarity statistics were used to assess the reproducibility of lower extremity kinematic and kinetic data collected on 5 normal adult subjects. For each subject, gait evaluations were done on 3 separate test days with 3 trials collected each day. Pelvis angles were fairly repeatable, however, with notably poor reproducibility in sagittal plane tilt. Re-application errors of the sacral wand coupled with a small range of motion are believed to be the principle contributors to variability in this pelvis angle. The sagittal plane angles for the hip, knee, and ankle demonstrated excellent repeatability within test days and between test days. Frontal and transverse plane angles were fairly repeatable within test days but between-day repeatability was considerably lower. The 'downstream' errors accompanying Euler angle calculations coupled with the smaller ranges of motion in the non-sagittal plane angles are suggested to contribute to the ambient variability already in these data and, thus, affect the within-day repeatability. Errors in re-application of midthigh and midcalf wands further contribute to the variability of these data between test days. Net resultant joint forces and moments were repeatable overall with slightly lower between-day statistical values. The exception to this observation was the adduction moment of the ankle which was notably variable between test days. Several explanations for this variability are presented. Results of this study have led to modifications in some marker placement procedures and reinforced the need for others already being used.
Video-Based Marker-Less Tracking System in Gait Analysis
2016
An alternative to the 30 motion marker-based optical camera capture is the Star Tracker 3D, a marker-less video-based tracking system. The aim of our study is to investigate the efficacy of the Star Tracker 3D. A series of gait analysis tests were carried out on ten subjects with a marker and marker-less tracking system simultaneously. The study suggests potential application in gait analysis in the academic classrooms and clinical settings where observations of anatomical motions can provide meaningful feedback.
Biomedical Engineering Letters, 2018
Comparison of results indicates a mean correlation of 99.542% with a standard deviation of 0.834%. The maximum root mean square error of the foot pitch angle measured by the IMU compared with the Vicon Optical Motion Capture System was 3.738º and the maximum error in the same walking trail between two measurements was 9.927º. These results indicate the level of correlation between the two systems. 1 INTRODUCTION Gait analysis has received significant interest in orthopedics and rehabilitation applications [1]; it has important implications in many clinical settings. The term 'Gait analysis' refers to the systematic study of animal locomotion [2], specifically the study of human motion, using equipments to measure body movements and the activity of the muscles [2]. It involves measurement and analysis of measurable parameters such as absolute and relative angles, positions, movement patterns and joints' range of motion. However, monitoring and measuring the human gait characteristics is a sophisticated task and thus, still rarely used for routine clinical evaluation [3]. There are three major commonly accepted methods available for gait analysis. The first and most common method is visual inspection. Second method is goniometric measurements, which is performed by goniometer that provides the range of motion in joints. Third is 3-dimensional marker-based optical motion capture (MBMOCAP) system which is an optoelectronic gait analysis method using optical motion capture for real-time 3-dimensional motion analysis [4] and considered as the standard method of movement analysis [5][6]. This
A Monocular Marker-Free Gait Measurement System
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2000
This paper presents a new, user-friendly, portable motion capture and gait analysis system for capturing and analyzing human gait, designed as a telemedicine tool to monitor remotely the progress of patients through treatment. The system requires minimal user input and simple single-camera filming (which can be acquired from a basic webcam) making it very accessible to nontechnical, nonclinical personnel. This system can allow gait studies to acquire a much larger data set and allow trained gait analysts to focus their skills on the interpretation phase of gait analysis. The design uses a novel motion capture method derived from spatiotemporal segmentation and model-based tracking. Testing is performed on four monocular, sagittal-view, sample gait videos. Results of modeling, tracking, and analysis stages are presented with standard gait graphs and parameters compared to manually acquired data. Index Terms-Automated tracking, gait analysis, human movement, motion analysis. I. INTRODUCTION A. Motivation C URRENT gait measurement methods involve complex marker systems, multiple cameras, a dedicated gait laboratory and trained personnel. This paper presents a simple single-camera system which has low processing time and is usable remote from the filming location and without the need for qualified gait analysts at the data acquisition stage. While this system is not intended to replace marker-based systems, it allows the study of gait to broaden beyond the gait laboratory while providing results comparable to those achievable with standard systems. It has been used, for example, to analyze gait in video clips filmed in another country. It is hoped that its simplicity will encourage therapists and patients to participate in gait studies and make the most of the technology available. B. Marker-Based Systems Marker-based systems are still the most reliable and widely used. However, they require specific equipment and expertise, not accessible outside a gait laboratory. This can be a significant issue when patients are too unwell to travel or when large data sets are required for study. Also, as demonstrated in [1], gait facilities are not readily available to many potential users. Within a gait laboratory, marker placement is still difficult. Marker positions have a significant effect on system output.
A 2D Markerless Gait Analysis Methodology: Validation on Healthy Subjects
2015
A 2D markerless technique is proposed to perform lower limb sagittal plane kinematic analysis using a single video camera. A subject-specific, multisegmental model of the lower limb was calibrated with the subject in an upright standing position. Ankle socks and underwear garments were used to track the feet and pelvis segments, whereas shank and thigh segments were tracked by means of reference points identified on the model. The method was validated against a marker based clinical gait model. The accuracy of the spatiotemporal parameters estimation was found suitable for clinical use (errors between 1% and 3% of the corresponding true values). Comparison analysis of the kinematics patterns obtained with the two systems revealed high correlation for all the joints (0.82 < í µí± 2 < 0.99). Differences between the joint kinematics estimates ranged from 3.9 deg to 6.1 deg for the hip, from 2.7 deg to 4.4 deg for the knee, and from 3.0 deg to 4.7 deg for the ankle. The proposed technique allows a quantitative assessment of the lower limb motion in the sagittal plane, simplifying the experimental setup and reducing the cost with respect to traditional marker based gait analysis protocols.
Reliability of a low-cost webcam recording system for three-dimensional lower limb gait analysis
International Biomechanics, 2019
The purposes of this study were to develop and evaluate the test-retest reliability of a specific low-cost three-dimensional webcam recording system (3D-WCRS) and compare its reliability to a standard motion analysis system. Twenty healthy volunteers comprised of 5 males and 15 females with a mean age of 22.90 years and mean BMI of 22.72 kg/m 2 were investigated for angles of hip, knee and ankle joints in three planes while walking at a self-selected speed. Intraclass correlation coefficients (ICCs) were used to evaluate as well as compare the test-retest reliability of the 3D-WCRS and standard motion analysis system. Standard error of measurement (SEM) was also analyzed for the purposes of the study. The results exhibited excellent test-retest reliability for the 3D-WCRS (ICCs ranged between 0.93 and 0.99, p = 0.001) in the three joints and planes. The standard motion analysis system demonstrated excellent reliability for all joints and planes (ICCs ranged between 0.99 and 1.00, p = 0.001). Minimal SEM values were observed in both the 3D-WCRS and standard motion analysis systems. Therefore, the developed low-cost 3D-WCRS exhibits good to excellent test-retest reliability. The test-retest reliability of the 3D-WCRS is likely to be comparable to a standard motion analysis system.
PLoS ONE, 2014
During the last decade markerless motion capture techniques have gained an increasing interest in the biomechanics community. In the clinical field, however, the application of markerless techniques is still debated. This is mainly due to a limited number of papers dedicated to the comparison with the state of the art of marker based motion capture, in term of repeatability of the three dimensional joints' kinematics. In the present work the application of markerless technique to data acquired with a marker-based system was investigated. All videos and external data were recorded with the same motion capture system and included the possibility to use markerless and marker-based methods simultaneously. Three dimensional markerless joint kinematics was estimated and compared with the one determined with traditional marker based systems, through the evaluation of root mean square distance between joint rotations. In order to compare the performance of markerless and marker-based systems in terms of clinically relevant joint angles estimation, the same anatomical frames of reference were defined for both systems. Differences in calibration and synchronization of the cameras were excluded by applying the same wand calibration and lens distortion correction to both techniques. Best results were achieved for knee flexion-extension angle, with an average root mean square distance of 11.75 deg, corresponding to 18.35% of the range of motion. Sagittal plane kinematics was estimated better than on the other planes also for hip and ankle (root mean square distance of 17.62 deg e.g. 44.66%, and 7.17 deg e.g. 33.12%), meanwhile estimates for hip joint were the most incorrect. This technique enables users of markerless technology to compare differences with marker-based in order to define the degree of applicability of markerless technique. Citation: Ceseracciu E, Sawacha Z, Cobelli C (2014) Comparison of Markerless and Marker-Based Motion Capture Technologies through Simultaneous Data Collection during Gait: Proof of Concept. PLoS ONE 9(3): e87640.
A low-cost video-based tool for clinical gait analysis
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2009
In physical and rehabilitation medicine physicians need to perform clinical gait analysis to assess patients walking ability. Despite the relevant research on motion tracking, gait analysis technologies are far to be commonly diffused in clinical practice since they are quite expensive, need high-structured laboratories and trained personnel who are not always available. In order to overcome such limitations, this work proposes a low-cost, video-based portable tool for clinical gait analysis which provides the bi-dimensional kinematic analysis of walking. The system processes a video stream by means of tracking different markers placed in five anatomical landmarks of the subject's leg, applying Kalman filter in conjunction with a method that copes with occlusions. The system has been validated on a healthy subject, showing that it is able to reconstruct marker position and leg kinematics even if several occlusions occur.
2022
Background: Markerless motion capture has the potential to perform movement analysis with reduced data collection and processing time compared to marker-based methods. This technology is now starting to be applied for clinical and rehabilitation applications and therefore it is crucial that users of these systems understand both their potential and limitations. This literature review aims to provide a comprehensive overview of the current state of markerless motion capture for both single camera and multi camera systems. Additionally, this review explores how practical applications of this technology are being used in clinical and rehabilitation settings, and examines the future challenges and directions markerless research must explore to facilitate full integration of this technology within clinical biomechanics. Methodology: A scoping review is needed to examine this emerging broad body of literature and determine where gaps in knowledge exist, which is key to developing motion capture methods that are cost effective and practically relevant to clinicians, coaches and researchers around the world. Literature searches were performed to examine studies that report accuracy of markerless motion capture methods, explore current practical applications of markerless motion capture methods in clinical biomechanics and identify gaps in our knowledge that are relevant to future developments in this area. Results: Markerless methods increase motion capture data versatility, enabling datasets to be re-analyzed using updated pose estimation algorithms and may even provide clinicians with the capability to collect data while patients are wearing normal clothing. While markerless temporospatial measures generally appear to be equivalent to marker-based motion capture, joint center locations and joint angles are not yet sufficiently accurate for clinical applications. Pose estimation algorithms are approaching similar error rates of marker-based motion capture, however, without comparison to a gold standard, such as bi-planar videoradiography, the true accuracy of markerless systems remains unknown. Conclusions: Current open-source pose estimation