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Corr, Sandra A. "Avian gait analysis." Thesis, University of Glasgow, 1999. http://theses.gla.ac.uk/6629/.
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Two methods were used in this research. The pedobarograph is a relatively novel method of gait analysis for animals which enables footfall patterns to be recorded, enabling spatial parameters (step length, width and angle) and plantar pressure patterns to be described and measured. A Kistler force plate was then used to measure the three-dimensional ground reaction forces (GRF's) produced during walking. Speed and cadence can be calculated using either system. Gait patterns are described for normal birds, and for different strains of broilers, raised on different feeding regimes. All the gait parameters were very variable, both between birds, and within the same bird, even when bodyweight and speed were controlled for. Despite the high variability, however, significant differences were identified in many of the gait parameters between the different groups. The vertical and craniocaudal GRF's of Brown Leghorns showed similar characteristics to those produced in human walking. The peak vertical forces were of a similar order of magnitude in the birds as in humans (125-150 % bodyweight), and the peak craniocaudal forces, and the rate of change of force, were closely tied to speed. All the GRF's in the birds increased significantly with increasing speed, except for braking rate (which was more variable) and stance time (which decreased significantly). The mediolateral forces were much greater in the birds than have been reported for other species, however, with peaks of 10-22% bodyweight. Analysis of plantar pressures showed that the pressure were concentrated on the digital pads, with the lowest pressure on the metatarsal pad (131 kNm-2), and highest pressure on the medial toe (up to 218 kNm-2).Combined gait analysis and morphometric studies of ad libitum-fed selected broilers identified many ways in which their gait deviated from that of relaxed broilers and Brown Leghorns, in ways which would serve to increase stability and decrease stresses on the skeleton.
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Ma, Weizen. "Instrumentation of Gait Analysis." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-28759.
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This master’s thesis project “Instrumentation of Gait Analysis” was carried out at and funded by Integrum AB, Gothenburg, Sweden. Force analysis is critical during rehabilitation process of amputation patients, since overloading might place the bone-implant interface at risk; while underloading might extend unnecessarily the already long rehabilitation program [1]. Highly developed sensor and data acquisition technology provides an easy and reliable way to do force analysis. This thesis introduces the problem and provides background material regarding Orthotics and Prosthetics, including osseointegration. The existing gait analysis techniques and sensor technology will be described. Based upon the criteria that are introduced, a suitable sensor and integration platform was selected to implement a new gait analysis system. Several trials of different gait states are proposed using the prototype to do gait analysis, the results are presented and analyzed. The success of this prototype has lead to plans to design an Osseointegrated Prostheses for the Rehabilitation of Amputees(OPRA) product
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Lee, Lily 1971. "Gait analysis for classification." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/8116.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002.Includes bibliographical references (p. 121-124).
This thesis describes a representation of gait appearance for the purpose of person identification and classification. This gait representation is based on simple localized image features such as moments extracted from orthogonal view video silhouettes of human walking motion. A suite of time-integration methods, spanning a range of coarseness of time aggregation and modeling of feature distributions, are applied to these image features to create a suite of gait sequence representations. Despite their simplicity, the resulting feature vectors contain enough information to perform well on human identification and gender classification tasks. We demonstrate the accuracy of recognition on gait video sequences collected over different days and times, and under varying lighting environments. Each of the integration methods are investigated for their advantages and disadvantages. An improved gait representation is built based on our experiences with the initial set of gait representations. In addition, we show gender classification results using our gait appearance features, the effect of our heuristic feature selection method, and the significance of individual features.
by Lily Lee.
Ph.D.
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Hong, Jie. "Human gait identification and analysis." Thesis, Brunel University, 2012. http://bura.brunel.ac.uk/handle/2438/7115.
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Human gait identification has become an active area of research due to increased security requirements. Human gait identification is a potential new tool for identifying individuals beyond traditional methods. The emergence of motion capture techniques provided a chance of high accuracy in identification because completely recorded gait information can be recorded compared with security cameras. The aim of this research was to build a practical method of gait identification and investigate the individual characteristics of gait. For this purpose, a gait identification approach was proposed, identification results were compared by different methods, and several studies about the individual characteristics of gait were performed. This research included the following: (1) a novel, effective set of gait features were proposed; (2) gait signatures were extracted by three different methods: statistical method, principal component analysis, and Fourier expansion method; (3) gait identification results were compared by these different methods; (4) two indicators were proposed to evaluate gait features for identification; (5) novel and clear definitions of gait phases and gait cycle were proposed; (6) gait features were investigated by gait phases; (7) principal component analysis and the fixing root method were used to elucidate which features were used to represent gait and why; (8) gait similarity was investigated; (9) gait attractiveness was investigated. This research proposed an efficient framework for identifying individuals from gait via a novel feature set based on 3D motion capture data. A novel evaluating method of gait signatures for identification was proposed. Three different gait signature extraction methods were applied and compared. The average identification rate was over 93%, with the best result close to 100%. This research also proposed a novel dividing method of gait phases, and the different appearances of gait features in eight gait phases were investigated. This research identified the similarities and asymmetric appearances between left body movement and right body movement in gait based on the proposed gait phase dividing method. This research also initiated an analysing method for gait features extraction by the fixing root method. A prediction model of gait attractiveness was built with reasonable accuracy by principal component analysis and linear regression of natural logarithm of parameters. A systematic relationship was observed between the motions of individual markers and the attractiveness ratings. The lower legs and feet were extracted as features of attractiveness by the fixing root method. As an extension of gait research, human seated motion was also investigated.
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Kepenekci, Burcu. "Human Activity Recognition By Gait Analysis." Phd thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613089/index.pdf.
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This thesis analyzes the human action recognition problem. Human actions are modeled as a time evolving temporal texture. Gabor filters, which are proved to be a robust 2D texture representation tool by detecting spatial points with high variation, is extended to 3D domain to capture motion texture features. A well known filtering algorithm and a recent unsupervised clustering algorithm, the Genetic Chromodynamics, are combined to select salient spatio-temporal features of the temporal texture and to segment the activity sequence into temporal texture primitives. Each activity sequence is represented as a composition of temporal texture primitives with its salient spatio-temporal features, which are also the symbols of our codebook. To overcome temporal variation between different performances of the same action, a Profile Hidden Markov Model is applied with Viterbi Path Counting (ensemble training). Not only parameters and structure but also codebook is learned during training.
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Deluzio, Kevin John. "Modelling and analysis of gait waveforms." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/nq22455.pdf.
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Hayfron-Acquah, James Ben. "Automatic gait recognition by symmetry analysis." Thesis, University of Southampton, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.274080.
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Wiik, Anatole Vilhelm. "Gait analysis using an instrumented treadmill." Thesis, Imperial College London, 2016. http://hdl.handle.net/10044/1/42542.
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Background: Gait analysis is used to measure objectively the ability to walk before and after hip and knee joint replacement. Most gait literature to date has measured patients walking at slow speeds, which may have unintentionally characterized successful lower limb operations as the same regardless of its operation type. The aim of this thesis was to use an instrumented treadmill to (1) test the upper limits of gait performance of patients awaiting and after lower limb arthroplasty and (2) describe and compare different joint procedures to healthy controls. Method: Gait analysis was carried out using an instrumented treadmill. Study participants walked at their preferred walking and top walking speed on the treadmill. Their vertical ground reaction force and spatiotemporal data was captured for both limbs by tandem force plates beneath the treadmill's belt. Results: The results suggest that at preferred walking speed on the flat, all subjects' gait characteristics were similar irrespective of joint state. The differences between patient groups became more apparent at top walking speed. Weight acceptance, step length and stride length were the most useful variables assessing these differences. Unicompartmental knee replacement and hip resurfacing had closer to normal gait patterns when compared to total knee replacement and conventional total hip replacement respectively. Predictably patients with knee osteoarthritis had asymmetrical gait patterns, impulse was found to be the best variable distinguishing patients with knee osteoarthritis from healthy controls. The downhill walking assessment established that patients with unicompartmental knee replacements had a more normal gait pattern than total knee replacement patients. Conclusion: The gait results suggest that an instrumented treadmill is a useful metric to describe patient gait patterns. Testing performance at higher walking speeds allowed differences to be detected, which were undetectable at slower speeds. Anatomically conserving procedures such as unicompartmental knee replacement and hip resurfacing appear to have convincing functional advantages compared to less conserving joint replacement procedures.
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Spencer, Nicholas M. "Pose invariant gait analysis and reconstruction." Thesis, University of Southampton, 2005. https://eprints.soton.ac.uk/261776/.
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One of the unique advantages of human gait is that it can be perceived from a distance. A varied range of research has been undertaken within the field of gait recognition. However, in almost all circumstances subjects have been constrained to walk fronto-parallel to the camera with a single walking speed. In this thesis we show that gait has sufficient properties that allows us to exploit the structure of articulated leg motion within single view sequences, in order to remove the unknown subject pose and reconstruct the underlying gait signature, with no prior knowledge of the camera calibration. Articulated leg motion is approximately planar, since almost all of the perceived motion is contained within a single limb swing plane. The variation of motion out of this plane is subtle and negligible in comparison to this major plane of motion. Subsequently, we can model human motion by employing a cardboard person assumption. A subject's body and leg segments may be represented by repeating spatio-temporal motion patterns within a set of bilaterally symmetric limb planes. The static features of gait are defined as quantities that remain invariant over the full range of walking motions. In total, we have identified nine static features of articulated leg motion, corresponding to the fronto-parallel view of gait, that remain invariant to the differences in the mode of subject motion. These features are hypothetically unique to each individual, thus can be used as suitable parameters for biometric identification. We develop a stratified approach to linear trajectory gait reconstruction that uses the rigid bone lengths of planar articulated leg motion in order to reconstruct the fronto-parallel view of gait. Furthermore, subject motion commonly occurs within a fixed ground plane and is imaged by a static camera. In general, people tend to walk in straight lines with constant velocity. Imaged gait can then be split piecewise into natural segments of linear motion. If two or more sufficiently different imaged trajectories are available then the calibration of the camera can be determined. Subsequently, the total pattern of gait motion can be globally parameterised for all subjects within an image sequence. We present the details of a sparse method that computes the maximum likelihood estimate of this set of parameters, then conclude with a reconstruction error analysis corresponding to an example image sequence of subject motion.
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Boston, Robert Trevor. "Techniques for orientation independent gait analysis." Thesis, University of Southampton, 2008. https://eprints.soton.ac.uk/64476/.
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Gait recognition algorithms are being increasingly widely researched, however a common assumption is that the subject will be presented side on to the camera. In practice it may not be possible to capture data from this view, so a useful gait recognition algorithm will have to provide a measure of orientation independence. Three gait recognition algorithms are examined and found to perform poorly with nonnormal orientation. The complex detail used for recognition can not be translated between orientations in a holistic silhouette manner. It is shown that orientation independent features can be extracted using a human model. The algorithm is developed and tested on live captured data and found to perform better across orientations than silhouette based approaches. The performance recorded at a single orientation is lower than that of other approaches, however only the motion of the subject is currently used for recognition. More accurate motion estimation will increase performance as will the inclusion of other model based features.
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Begg, Rezaul K. "A microcomputer-based gait analysis system." Thesis, University of Aberdeen, 1990. http://digitool.abdn.ac.uk/R?func=search-advanced-go&find_code1=WSN&request1=AAIU047104.
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A microcomputer-based video vector system has been developed to display the resultant foot-ground reaction force vector on a television image of the subject in real-time. The system consists of a strain gauged force platform, 12-bit ADC, a video camera, and an Archimedes microcomputer. The output of the computer is synchronised and overlaid on the video image of the camera by a video GENLOCK board. For each television field the resultant force vector is correctly positioned relative to the image of the force platform and superimposed on the TV image at 50 times/sec. A television/computer interface has been designed to detect the position of markers using the real-time video signals. Passive optical markers are used on the subject as a means of identifying regions of interst and a glass plate/light arrangement is used to enhance reflection signals from these markers. A threshold detector extracts marker peaks from the rest of the video and digital counters determine the spatial coordinates of the markers. A hardware video window selector has been designed which is selected prior to data collection to exclude the irrelevant areas in the video field. A 16-bit input/output system has been designed dedicated to data transfer between the TV/computer interface and the Archimedes microcomputer. The system has been tested in all of its aspects to verify its ability to produce repeatable and accurate results. Some of the typical results obtained from the system are presented for both normal and pathological gait. The aim to produce a simple to use and flexible instrument was maintained throughout the design phase. The result is an instrument which can be used to record the various useful gait parameters and be a valuable tool in routine gait evaluation in the clinic.
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Kucuk, Can. "3d Marker Tracking For Human Gait Analysis." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/2/12606941/index.pdf.
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This thesis focuses on 3D marker tracking for human gait analysis. In KISS Gait Analysis System at METU, a subject's gait is recorded with 6 cameras while 13 reflective markers are attached at appropriate locations on his/her legs and feet. These images are processed to extract 2 dimensional (2D) coordinates of the markers in each camera. The 3 dimensional (3D) coordinates of the markers are obtained by processing the 2D coordinates of the markers with linearization and calibration algorithms. Then 3D trajectories of the markers are formed using the 3D coordinates of the markers. In this study, software which takes the 2D coordinates of markers in each camera and processes them to form the 3D trajectories of the markers is developed. Kalman Filter is used in formation of 3D trajectories. The results are found to be satisfactory.
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Trinler, Ursula Kathinka. "Muscle force estimation in clinical gait analysis." Thesis, University of Salford, 2016. http://usir.salford.ac.uk/39257/.
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Neuro-musculoskeletal impairments are a substantial burden on our health care system as a consequence of disease, injury or aging. A better understanding of how such impairments influence the skeletal system through muscle force production is needed. Clinical gait analysis lacks in a sufficient estimation of individual muscle forces. To date, joint moments and EMG measurements are used to deduce on the characteristics of muscle forces, however, known limitations restrain a satisfying analysis of muscle force production. Recent developed musculoskeletal models make it possible to estimate individual muscle forces using experimental kinematic and kinetic data as input, however, are not yet implemented into a clinical gait analysis due to a wide range of different methods and models and a lack of standardised protocols which could be easily applied by clinicians in a routine processing. This PhD thesis assessed the state of the art of mathematical modelling which enables the estimation of muscle force production during walking. This led into devising a standardised protocol which could be used to incorporate muscle force estimation into routine clinical practice. Especially the input of clinical science knowledge led to an improvement of the protocol. Static optimisation and computed muscle control, two mathematical models to estimate muscle forces, have been found to be the most suitable models for clinical purposes. OpenSim, a free available simulation tool, has been chosen as its musculoskeletal models have been already frequently used and tested. Furthermore, OpenSim provides a straight forward pipeline called SimTrack including both mathematical models. Minor and major adjustments were needed to adapt the standard pipeline for the purposes of a clinical gait analysis to be able to create a standardised protocol for gait analyses. The developed protocol was tested on ten healthy participants walking at five different walking speeds and captured by a standard motion capture system. Muscle forces were estimated and compared to surface EMG measurements regarding activation and shape as well as their dependence on walking speed. The results showed a general agreement between static optimisation, computed muscle control and the EMG excitations. Compared to the literature, these results show a good consistency between the modelling methods and surface EMG. However, some differences were shown between mathematical models and between models and EMG, especially fast walking speeds. Additionally, high estimated activation peaks and uncertainties within the estimation process point out that more research needs to be undertaken to understand the mechanisms of mathematical models and the influence of different modelling parameters better (e.g. characteristics of muscle-tendon units, uncertainties of dynamic inconsistency). In conclusion, muscle force estimation with mathematical models is not yet robust enough to be able to include the protocol into a clinical gait analysis routine. It is, however, on a good way, especially slow walking speeds showed reasonable good results. Understanding the limitations and influencing factors of these models, however, may make this possible. Further steps may be the inclusion of patients to see the influence of health conditions.
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Engström, Isak. "Automated Gait Analysis : Using Deep Metric Learning." Thesis, Linköpings universitet, Medie- och Informationsteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-178139.
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Sectors of security, safety, and defence require methods for identifying people on the individual level. Automation of these tasks has the potential of outperforming manual labor, as well as relieving workloads. The ever-extending surveillance camera networks, advances in human pose estimation from monocular cameras, together with the progress of deep learning techniques, pave the way for automated walking gait analysis as an identification method. This thesis investigates the use of 2D kinematic pose sequences to represent gait, monocularly extracted from a limited dataset containing walking individuals captured from five camera views. The sequential information of the gait is captured using recurrent neural networks. Techniques in deep metric learning are applied to evaluate two network models, with contrasting output dimensionalities, against deep-metric-, and non-deep-metric-based embedding spaces. The results indicate that the gait representation, network designs, and network learning structure show promise when identifying individuals, scaling particularly well to unseen individuals. However, with the limited dataset, the network models performed best when the dataset included the labels from both the individuals and the camera views simultaneously, contrary to when the data only contained the labels from the individuals without the information of the camera views. For further investigations, an extension of the data would be required to evaluate the accuracy and effectiveness of these methods, for the re-identification task of each individual.Examensarbetet är utfört vid Institutionen för teknik och naturvetenskap (ITN) vid Tekniska fakulteten, Linköpings universitet
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Jaskowak, Daniel Joseph. "Detecting Transient Changes in Gait Using Fractal Scaling of Gait Variability in Conjunction with Gaussian Continuous Wavelet Transform." Thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/87393.
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Accelerometer data can be analyzed using a variety of methods which are effective in the clinical setting. Time-series analysis is used to analyze spatiotemporal variables in various populations. More recently, investigators have focused on gait complexity and the structure of spatiotemporal variations during walking and running.
This study evaluated the use of time-series analyses to determine gait parameters during running. Subjects were college-age female soccer players. Accelerometer data were collected using GPS-embedded trunk-mounted accelerometers. Customized Matlab® programs were developed that included Gaussian continuous wavelet transform (CWT) to determine spatiotemporal characteristics, detrended fluctuation analysis (DFA) to examine gait complexity and autocorrelation analyses (ACF) to assess gait regularity. Reliability was examined using repeated running efforts and intraclass correlation. Proof of concept was determined by examining differences in each variable between various running speeds. Applicability was established by examining gait before and after fatiguing activity.
The results showed most variables had excellent reliability. Test-retest R2 values for these variables ranged from 0.8 to 1.0. Low reliability was seen in bilateral comparisons of gait symmetry. Increases in running speed resulted in expected changes in spatiotemporal and acceleration variables. Fatiguing exercise had minimal effects on spatiotemporal variables but resulted in noticeable declines in complexity.
This investigation shows that GPS-embedded trunk-mounted accelerometers can be effectively used to assess running gait. CWT and DFA yield reliable measures of spatiotemporal characteristics of gait and gait complexity. The effects of running speed and fatigue on these variables provides proof of concepts and applicability for this analytical approach.Master of Science
Fitness trackers have become widely accessible and easy to use. So much so that athletic teams have been using them to track activity throughout the season. Researchers are able to manipulate data generated from the fitness monitors to assess many different variables including gait. Monitoring gait may generate important information about the condition of the individual. As a person fatigues, running form is theorized to breakdown, which increases injury risk. Therefore the ability to monitor gait may be advantageous in preventing injury. The purpose of this study is to show that the methods in this study are reproducible, respond reasonably to changes in speed, and to observe the changes of gait in the presence of fatigue or on tired legs. Three analyses are used in this study. The first method called autocorrelation, overlays acceleration signals of consecutive foot strikes, and determines the similarity between them. The second method utilizes a wave transformation technique that is able to determine foot contact times. The final method attempts to determine any pattern in the running stride. This method looks for changes in the structure of the pattern. Less structure would indicate a stride that is fatigued. The results showed that the methods of gait analysis used in this study were reproducible and responded appropriately with changes in speed. Small changes in gait were observed due to the presence of fatigue. Further investigation into the use of these methods to determine changes in gait due to the presence of fatigue are warranted.
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Becker, James N. M. 1979. "Effects of Two Marker Placement and Data Analysis Methods on Running Gait Analysis." Thesis, University of Oregon, 2010. http://hdl.handle.net/1794/10470.
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xiii, 143 p. : ill. A print copy of this thesis is available through the UO Libraries. Search the library catalog for the location and call number.This study evaluated the effects of two marker placement methods and two data analysis methods on running gait analysis. Markers placed on the shoe heel counter were compared with markers placed directly on the calcaneous and visible through heel windows cut into the shoe. When analyzed using a traditional group design no significant differences were found between marker conditions for rear foot eversion excursion, percent stance at which peak eversion occurred, maximal instantaneous eversion velocity, or maximal instantaneous vertical loading rate. Ankle frontal plane variability was significantly different between conditions. When analyzed with a single subject design some individuals demonstrated significant differences between conditions while others did not. In some individuals the heel windows condition revealed previously masked coupling parameters thought to be related to injury. The results of this study suggest the heel windows method and single subject analysis should be used for a longitudinal study of runners.
Committee in Charge: Dr. Li-Shan Chou, Chair; Dr. Louis Ostemig; Dr. Stanley James
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Wills, Eric David 1977. "Gait animation and analysis for biomechanically-articulated skeletons." Thesis, University of Oregon, 2008. http://hdl.handle.net/1794/7508.
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xx, 287 p. ; ill. (some col.) A print copy of this title is available through the UO Libraries under the call numbers: SCIENCE QP310.W3 W55 2008Digital three-dimensional (3D) models are useful for biomechanical analysis because they can be interactively visualized and manipulated. Synthesizing and analyzing animal locomotion with these models, however, is difficult due to the large number of joints in a fully articulated skeleton, the complexity of the individual joints, and the huge space of possible configurations, or poses, of the skeleton taken as a whole. A joint may be capable of several biological movements, each represented by a degree of freedom (DOF). A quadrupedal model may require up to 100 DOFs to represent the limbs and trunk segments only, resulting in extremely large spaces of possible body configurations. New methods are presented here that allow limbs with any number of biomechanical DOFs to be kinematically exercised and mapped into a visualization space. The spaces corresponding to the ranges of motion of the left and right limbs are automatically intersected and pruned using biological and locomotion constraints. Hind and fore spaces are similarly constrained so that Genetic Algorithms (GAs) can be used to quickly find smooth, and therefore plausible, kinematic quadrupedal locomotion paths through the spaces. Gaits generated for generic dog and reptile models are compared to published gait data to determine the viability of kinematics-only gait generation and analysis; gaits generated for Apatosaurus, Triceratops , and Tyrannosaurus dinosaur models are then compared to those generated for the extant animals. These methods are used for several case studies across the models including: isolating scapulothorax and shoulder joint functionality during locomotion, determining optimal ankle heights for locomotion, and evaluating the effect of limb phase parameters on quadrupedal locomotion.
Adviser: Kent A. Stevens
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Abdelhadi, Jalal [Verfasser]. "Computerized gait analysis of dogs during normal gait and with induced forelimb lameness / Jalal Abdelhadi." Hannover : Bibliothek der Tierärztlichen Hochschule Hannover, 2013. http://d-nb.info/1037762908/34.
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Carlsson, Hampus, and Kärrman Marcus. "Cloud-based Mobile System for Free-Living Gait Analysis : System component : Server architecture." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-34293.
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Progress in the fields of wearable sensor technologies together with specialized analysis algorithms has enabled systems for gait analysis outside labs. An example of a wearable sensor is the accelerometer embedded in a typical smartphone. The goal was to propose a system design capable of hosting existing gait analysis algorithms in a cloud environment, and tailor the design as to deliver fast results with the ambition of reaching near real-time. The project identified a set of enabling technologies by examining existing systems for gait analysis; the technologies included cloud computing and WebSockets. The final system design is a hierarchical composition starting with a Linux VM running Node.js, which in turn connects to a database and hosts instances of the MatLab runtime. The results show the feasibility of mobile cloud based free-living gait analysis. The architectural design provides a solution to the critical problem of enabling existing algorithms to run in a cloud environment; and shows how the graphical output of the native algorithm could be accurately reproduced in a web browser. The system can process a chunk of 1300 data points under 3 seconds for a client streaming at 128 Hz, while simultaneously streaming the real time signal.
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Kafali, Pinar. "Evaluation Of Sensitivity Of Metu Gait Analysis System." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608390/index.pdf.
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Gait analysis is one of the primary applications of biomechanics and deals with scientific description of human locomotion, which is a qualitative concept as observed through the human eye. METU Gait Analysis Laboratory has been operating in various fields of gait and motion analyses since 1999. Although several studies have previously been undertaken about METU Gait Analysis System, until now, the effects of methodology and protocol related system parameters on kinematic analysis results have not been fully and exhaustively investigated.
This thesis presents an assessment on sensitivity and compatibility of METU Gait Analysis Protocol to variations in experimental methodology and implementation of various joint center estimation methods, performed through investigation of the resulting joint kinematics. It is believed that the performance and reliability of METU Gait Analysis System will be improved based on the findings of this study.
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Balisane, Hewa. "Human gait analysis for biometric identification and authentication." Thesis, Manchester Metropolitan University, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.539385.
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The study of biometrics is concerned with any human physiological or behavioural characteristic which is universal, unique and measurable. Biometric systems operate by acquiring biometric data from individuals, extracting feature sets from data and comparing this feature with the enrolment set in a database. The aIm of this research is to compare the performance of gait-based user recognition of children with adults. Existing analyses techniques in gait-based recognition using wearable sensors for adults are applied to gait analyses in children. This is the first known study to be conducted on children (5-16 years old) for biometric gait recognition. Results presented here show that the performance degradation for children's walking compared to adult walking is approximately 100%. In comparable settings, a 6.21 % Equal Error Rate (EER) for adult gait recognition was reached, whilst for children's walking an EER of 12.69% was achieved. The performance of children's walking whilst carrying an object has also been studied. Results show that carrying an object actually improves the performance when walking normally, but when the children were asked to walk faster the walking becomes unstable, resulting in a higher Equal Error Rate (EER). A comparative investigation of the effects of time on gait recognition in children's walking pattern was carried out. The effects of age and gender have also been considered. In addition, children were tested six months apart; with the sensor on the hip position the performance of gait recognition shows significant variations with EER values. Abstract Finally, this thesis offers for the first time a coupled approach of statistical timedomain and frequency domain methods have been employed in order to match biometric gait signals. It has been shown that initially using root mean squared, crest-factor and kurtosis obtained similar matches in gait signals of children for the ages of 5-16 than for the traditional methods. Hence these novel methods employed can be exploited to verify these more established methods resident in gait recognition software.
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Yoo, Jang-Hee. "Recognizing human gait by model-driven statistical analysis." Thesis, University of Southampton, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.414595.
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Tan, Junjay. "Advancing clinical gait analysis through technology and policy." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/53326.
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Thesis (S.M. in Technology and Policy)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (p. 161-165).
Quantitatively analyzing human gait biomechanics will improve our ability to diagnose and treat disability and to measure the effectiveness of assistive devices. Gait analysis is one technology used to analyze walking, but technical as well as economic, social, and policy issues hinder its clinical adoption. This thesis is divided into two parts that address some of these issues. Part I focuses on the role public policies have in advancing gait analysis. Through an analysis of gait analysis technologies, case studies of MRI and CT Angiography, and a high-level analysis of data standards used in gait analysis, it concludes that policies cannot directly create the institutional structures and the data standards required to advance gait analysis as a clinical diagnostic tool. Only through indirect means, such as research funding, can policies support the development of organizations to take ownership of gait analysis technologies. Part I also concludes that policies should not fund development of gait technologies but instead should fund research units working on data standards and accurate human body models. Part II focuses on a technical issue in gait analysis, namely, how to address uncertainties in joint moment calculations that occur from using different body segment inertial parameter estimation models. This is identified as a technical issue needing attention from our broader policy analysis in Part I. Using sensitivity studies of forward dynamics computer simulations coupled with an analysis of the dynamical equations of motion, Part II shows that joint moment variations resulting from different segment inertial parameters are significant at some parts of the gait cycle, particularly heel strike and leg swing.
(cont.) It provides recommendations about which segment inertial parameters one should estimate more accurately depending on which joints and phases of the gait cycle one is interested in analyzing.
by Junjay Tan.
S.M.
S.M.in Technology and Policy
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Bouchrika, Imed. "Gait analysis and recognition for automated visual surveillance." Thesis, University of Southampton, 2008. https://eprints.soton.ac.uk/266142/.
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Human motion analysis has received a great attention from researchers in the last decade due to its potential use in different applications such as automated visual surveillance. This field of research focuses on the perception and recognition of human activities, including people identification. We explore a new approach for walking pedestrian detection in an unconstrained outdoor environment. The proposed algorithm is based on gait motion as the rhythm of the footprint pattern of walking people is considered the stable and characteristic feature for the classification of moving objects. The novelty of our approach is motivated by the latest research for people identification using gait. The experimental results confirmed the robustness of our method to discriminate between single walking subject, groups of people and vehicles with a successful detection rate of 100%. Furthermore, the results revealed the potential of our method to extend visual surveillance systems to recognize walking people. Furthermore, we propose a new approach to extract human joints (vertex positions) using a model-based method. The spatial templates describing the human gait motion are produced via gait analysis performed on data collected from manual labeling. The Elliptic Fourier Descriptors are used to represent the motion models in a parametric form. The heel strike data is exploited to reduce the dimensionality of the parametric models. People walk normal to the viewing plane, as major gait information is available in a sagittal view. The ankle, knee and hip joints are successfully extracted with high accuracy for indoor and outdoor data. In this way, we have established a baseline analysis which can be deployed in recognition, marker-less analysis and other areas. The experimental results confirmed the robustness of the model-based approach to recognise walking subjects with a correct classification rate of 95% using purely the dynamic features derived from the joint motion. Therefore, this confirms the early psychological theories claiming that the discriminative features for motion perception and people recognition are embedded in gait kinematics. Furthermore, to quantify the intrusive nature of gait recognition we explore the effects of the different covariate factors on the performance of gait recognition. The covariate factors include footwear, clothing, carrying conditions and walking speed. As far as the author can determine, this is the first major study of its kind in this field to analyse the covariate factors using a model-based method.
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Wills, Eric David. "Gait animation and analysis for biomechanically-articulated skeletons /." Connect to title online (Scholars' Bank) Connect to title online (ProQuest), 2008. http://hdl.handle.net/1794/7508.
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Thesis (Ph. D.)--University of Oregon, 2008.Typescript. Includes vita and abstract. Includes bibliographical references (leaves 281-287). Also available online in Scholars' Bank; and in ProQuest, free to University of Oregon users.
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Handzic, Ismet. "Analysis and Application of Passive Gait Rehabilitation Methods." Scholar Commons, 2014. https://scholarcommons.usf.edu/etd/5234.
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Human gait is elegant and efficient in propelling the body forward. While a healthy human gait is symmetric, any deviation from symmetry can cause inefficiencies to the entire body. Such asymmetries may present themselves in hemiplegic patients, prosthetic users, lower limb injuries, limb height and weight discrepancies, or abnormal overground foot rolling. In this dissertation, practical passive methods to alleviate such asymmetric walking dynamics are presented. The novel concepts presented in this manuscript can all be related and applied to passive gait rehabilitation, that is, the rehabilitation of a person's gait through methods that do not require external power. One of the passive rehabilitation solutions for asymmetric gait is the the Gait Enhancing Mobile Shoe (GEMS). The GEMS is designed to mimic the motions of a split-belt treadmill, which is commonly used for asymmetric gait rehabilitation. Two iterations of the GEMS prototype are presented. While the first development design of the GEMS was too bulky, it showed controlled and constant backward motion. The second fully mechanical design was tested on healthy participants and was successful in producing spatial and temporal aftereffects similar to those seen in split-belt treadmill gait studies.
In order to more accurately define the dynamics of the GEMS wheel as an individual steps on the shoe, mathematical models that predict the static and dynamic behavior of irregularly shaped curves on a flat plane as a weight is applied are derived and verified. While this kinetic shape concept can be applied to rolling irregularly shaped wheels, it can also be utilized to predict and manipulate roll-over motions of human feet, prosthetic feet, or even robotic biped feet. This kinetic shape concept was applied to develop a force dependent musical string instrument, transportation device, a more efficient walking crutch for controlled crutch walking, and a unique form of force mathematics.
The asymmetric kinematics of dissimilar human limbs can be synchronized for symmetry with a generalized passive kinematic synchronization technique that can match the motion of two or more dissimilar and uncoupled rotating systems. This kinematic synchronization technique introduced in this dissertation can be applied to duplicate the motion of swinging human limbs with dissimilar masses and mass distributions, which allows for the passive synchronization and rehabilitation of human limbs such as swinging arms and legs during walking. This technique also allows for the synchronization of mechanical systems such as pendulums, propellers, or rotating cams.
Finally, a detailed derivation of a two and three link passive dynamic walker (PDW) model with and without variable radius feet is presented. While PDW models have been studied and derived for decades, this dissertation offers a clear and complete guide on how to derive the kinematics and kinetics of the simplest compass gait, three-link point-foot, and for the first time, a variable radius foot PDW model, where the roll-over foot shape of the PDW can be dependent on its position or other kinematic variables. This advancement in the PDW model allows for the systematic evaluation of the change of various gait parameters such as foot roll-over shape or robotic foot dynamics.
This numerical biped model was compared to human gait parameters. This comparison included normal walking, tied- and split-belt treadmill walking, and GEMS walking. This model was also used to analyze the dynamic effects of changing the foot roll-over parameters such as foot roll radius and foot shape curvature. In addition, the PDW model was employed to investigate the perception of normal and pathological gait. The PDW model was systematically manipulated to produce walking patterns that showed a degree of abnormality in spatial and temporal gait parameters. This analysis showed that certain gait parameters may be asymmetrically changed to some extent without causing an abnormal perception.
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Richards, James David. "Gait analysis under different testing conditions and their effect on non-pathological and intermittent claudication gait." Thesis, Glasgow Caledonian University, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.267083.
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Sharif, Bidabadi Shiva. "Human Gait Model Development for Objective Analysis of Pre/Post Gait Characteristics Following Lumbar Spine Surgery." Thesis, Curtin University, 2019. http://hdl.handle.net/20.500.11937/78468.
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Although multiple advanced tools and methods are available for gait analysis, the gait and its related disorders are usually assessed by visual inspection in the clinical environment. This thesis aims to introduce a gait analysis system that provides an objective method for gait evaluation in clinics and overcomes the limitations of the current gait analysis systems. Early identification of foot drop, a common gait disorder, would become possible using the proposed methodology.
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Razeghi, Mohsen. "Biomechanical analysis of the effect of orthotic shoe inserts." Thesis, University of Nottingham, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.368254.
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Arnell, M. M. "Numerical descriptors of the intersegmental kinematics of gait." Thesis, University of Manchester, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.233041.
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Arnold, Mark Andrew. "Finite element analysis of ankle foot orthoses." Thesis, University of Southampton, 1999. https://eprints.soton.ac.uk/393597/.
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Ko, Seung-uk. "Human gait analysis by gait pattern measurement and forward dynamic model combined with non linear feedback control /." Connect to this title online, 2007. http://hdl.handle.net/1957/3754.
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Srinivasan, Sujatha. "Low-dimensional modeling and analysis of human gait with application to the gait of transtibial prosthesis users." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1179865923.
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Collins, James Joseph. "Joint mechanics - modelling of the lower limb." Thesis, University of Oxford, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.276573.
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Polak, Frances. "Comparison of two doses of botulinum toxin in the treatment of children with cerebral palsy." Thesis, University of Nottingham, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.289068.
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Jin, Li. "KINEMATIC AND KINETIC ANALYSIS OF WALKING AND RUNNING ACROSS SPEEDS AND TRANSITIONS BETWEEN LOCOMOTION STATES." Thesis, University of Oregon, 2018. http://hdl.handle.net/1794/23912.
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DISSERTATION ABSTRACT
Li Jin
Doctor of Philosophy
Department of Human Physiology
March 2018
Title: Kinematic and Kinetic Analysis of Walking and Running across Speeds and Transitions between Locomotion States
Walking and running are general locomotion activities for human beings. Basic gait patterns and whole body center of mass (COM) dynamic patterns are distinctly different between them. Lower extremity joint mechanics patterns could reflect musculoskeletal coordination characteristics. Change of locomotion tasks and speeds can affect lower extremity joint kinematic and kinetic characteristics, and progression of age may also affect these characteristics. Little is known about change of locomotion tasks and speeds effects on lower extremity joint level kinetic characteristics, and whether there is a connection between COM system and lower extremity system. To address this, twenty healthy subjects were recruited to participate in a series of treadmill tests, including walking (0.8 – 2.0 m/s, with 0.2 m/s intervals), running (1.8 – 3.8 m/s, with 0.4 m/s intervals) and gait mode transition from walking to running, and from running to walking (between 1.8 – 2.4 m/s, 0.1 m/s2). Three-dimensional kinematic and kinetic data were collected in all locomotion tests and used to calculate and analyze outcome variables for lower extremity joints and the COM system across different conditions. Results indicate that change of locomotion speeds significantly affect joint level kinetic characteristics within both walking and running locomotion states. Different locomotion task demands (walking vs. running) require fundamental alteration of lower extremity joint level kinetic patterns, even at the same locomotion speed. Progression of age also affects lower extremity joint level kinematic and kinetic patterns in walking and running across speeds. Additionally, stance phase an energy generation and transfer phenomenon occurred between the distal and proximal joints of the lower extremity in both walk-to-run and run-to-walk transitions. Lastly, a connection exists between whole body COM oscillation patterns and lower extremity joint level kinetic characteristics in running. These findings serve to further clarify the mechanisms involved in change of locomotion tasks and speeds effects on lower extremity joint kinetic patterns, and further establish a connection between the COM system and the lower extremity system. These findings may be beneficial for future foot-ankle assistive device development, potential optimization of gait efficiency and performance enhancement.
This dissertation includes previously published and unpublished coauthored material.
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Swamidas, Joshua. "Predicting missing marker positions in simulated gait analysis systems." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/MQ36184.pdf.
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Jenkins, Sian M. "Lower limb modelling for children in clinical gait analysis." Thesis, University of Oxford, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.400179.
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Poon, Mei-ying Dora, and 潘美英. "Gait analysis of normal and total knee replacement subjects." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1997. http://hub.hku.hk/bib/B31214563.
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Martori, Amanda Lynn. "A Wearable Motion Analysis System to Evaluate Gait Deviations." Scholar Commons, 2013. http://scholarcommons.usf.edu/etd/4724.
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A Wearable Motion Analysis System (WMAS) was developed to evaluate gait, particularly parameters that are indicative of mild traumatic brain injury. The WMAS consisted on six Opal IMUs attached on the sternum, waist, left and right thigh and left and right shank. Algorithms were developed to calculate the knee flexion angle, stride length and cadence parameters during slow, normal and fast gait speeds. The WMAS was validated for repeatability using a robotic arm and accuracy using the Vicon motion capture system, the gold standard for gait analysis. The WMAS calculated the gait parameters to within a clinically acceptable range and is a powerful tool for gait analysis and potential concussion diagnosis outside of a laboratory setting.
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Barton, Gabor J. "Visualisation of clinical gait analysis data using neural networks." Thesis, Liverpool John Moores University, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.436553.
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Cunado, David. "Automatic gait recognition via model-based moving feature analysis." Thesis, University of Southampton, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.297628.
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Thakkar, Sneha 1979. "Energy economy gait analysis of an autoadaptive prosthetic knee." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/87872.
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Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002.Includes bibliographical references (leaves [52]-54).
by Sneha Thakkar.
M.Eng.
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Chan, Herman King Yeung. "Machine learning and statistical approaches to support gait analysis." Thesis, Ulster University, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.646039.
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Carneiro, Susana Moreira. "Statistical gait analysis in patients after total hip arthroplasty." Master's thesis, Instituto Politécnico de Bragança, Escola Superior de Tecnologia e Gestão, 2012. http://hdl.handle.net/10198/8221.
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Patient’s functional recovery after Total Hip Arthroplasty (THA) is often slow. Besides, patients tend to adjust gait patterns to avoid the pain, a condition referred to as antalgic gait. The aim of this work is to highlight changes in gait and muscle activation patterns of patients after total hip arthroplasty, by means of a statistical gait analysis.
The gait analysis was performed on 20 patients with unilateral hip prosthesis (3, 6 and 12 months post-operatively) and 20 controls, at self-selected and fast speed. The analysis was performed using the system Step 32 (DemItalia, Italy). Various statistical analyses were done to compare the outcomes of the two groups. Subjects were examined bilaterally by means of basographic sensors (foot switches), goniometric sensors (in the knee and hip), and surface electromyography of five leg muscles.
This study demonstrated that, for patients, the number of atypical strides is higher and the heel contact phase is extended in time, in both sides. Besides, on the operated leg, despite a significant increase in the hip dynamic range of motion, patients do not reach normal range of motion (ROM) values even one year after the intervention. Furthermore, the electromyographic results show that the number of simpler activations tends to increases and the number of complex activations decreases over the time for THA patients, suggesting a compensations strategy. A recuperação funcional do paciente após a artroplastia total da anca (PTA) é muitas vezes demorada. Além disso, os pacientes tendem a ajustar padrões de marcha de forma a evitar a dor, uma condição referida como marcha antálgica. O objetivo deste trabalho é destacar as alterações na marcha e padrões de ativação muscular dos pacientes após artroplastia total da anca, por meio de uma análise estatística da marcha.
A análise da marcha foi realizada em 20 pacientes com prótese unilateral da anca (3, 6 e 12 meses pós-operatório) e 20 controles, com velocidade auto-selecionada e rápida. A análise foi realizada através do sistema Step 32 (DemItalia, Itália). Várias análises estatísticas foram realizadas para comparar os resultados dos dois grupos. Os indivíduos foram examinados bilateralmente através de sensores basográficos (interruptores de pé), sensores goniométricos (no joelho e anca) e electromiografia de superfície em cinco músculos da perna.
Este estudo demonstrou que, para os pacientes, o número de passos atípicos é maior e a fase de contacto do calcanhar (H) é prolongada, em ambos os lados. Além disso, na perna operada, apesar de ocorrer um aumento significativo na amplitude dinâmica do movimento da anca, os pacientes não atingem valores de amplitude de movimento (ADM) normais, mesmo um ano após a intervenção. Além disso, os resultados electromiográficos mostram que o número de ativações mais simples tendem a aumentar e do número de ativações complexos a diminuir ao longo do tempo para os pacientes submetidos a artroplastia total da anca, sugerindo uma estratégia de compensação.
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Arendse, Regan Emile. "The application of clinical gait analysis to running injuries." Doctoral thesis, University of Cape Town, 2005. http://hdl.handle.net/11427/8643.
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Includes bibliographical references.Clinical evaluation of the injured runner requires identification and correction of the multiple factors commonly implicated in running injury. Effective management of running injuries requires that the concerned health professional identify all implicated factors. In this regard it is essential that the relationship between running style and injury he determined, because if there is an association between the gait analysis variables descriptive of running style and injury, these would be important in the management of the injured runner. The Gait Analysis Laboratory at the Sports Science institute of South Africa and the University of Cape Town with its three-dimensional Vicon 370 motion analysis system and Advanced Medical Technology industry® strain gauge force platform is appropriate for collecting data to study running style. These data include the movement patterns and estimated mechanical power and work required to effect the observed movement of the ankle and knee. The forces applied by the supporting surfaces on the runners were collected. The data captured with the Workstation® programme (Oxford Metric, Oxford, England), was processed with GaitLab® (Kiboho Publishers, Cape Town, South Africa), collated in Excel ® (Microsoft Corporation, Redmond, USA) and statistically analysed (StatSoft, Inc. (2000). STATISTICA for Windows [Computer program manual]. Tulsa, OK, USA). In this thesis a series of studies are presented with the aim of determining the relevance of running style to the assessment of the injured runner and the conventional treatment methods used to treat common running injuries.
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D'Angelo, Maurissa S. "Analysis of Amputee Gait using Virtual Reality Rehabilitation Techniques." Wright State University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=wright1279121086.
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Oggero, Elena. "Optimization of force plate size for effective gait analysis /." The Ohio State University, 2000. http://rave.ohiolink.edu/etdc/view?acc_num=osu1488203552781197.
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Liu, Ting-Ting. "A Wearable Gait Analysis System for Overstriding in Runners." Thesis, Harvard University, 2015. http://nrs.harvard.edu/urn-3:HUL.InstRepos:14398557.
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As interest in running continues growing, runners are constantly seeking ways to prevent common aches and injuries. Gait retraining to improve the biomechanics of running can affect the forces experienced by the body, and is hypothesized to lower the chance of injury and improve running efficiency. However, existing gait retraining methods rely heavily on external equipment and human analysis, meaning it is not accessible for everyday runners. The wearable gait analysis system highlighted in this project is designed to monitor running gait without extensive equipment, thus shifting gait analysis out of training centers and giving runners the opportunity to correct their gait independently. This project features IMU technology to specifically target and reduce overstride in runners. By monitoring the shank angles throughout the cycle and determining the overstride angle at time of impact, the system is able to measure overstriding with fewer than 3° of error across a variety of speeds and running styles. This measurement is then translated into live-time feedback for runners.
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HONG, SHAO-HONG, and 洪韶鴻. "Initial gait analysis." Thesis, 1991. http://ndltd.ncl.edu.tw/handle/15551126789840749807.
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