Relevant bibliographies by topics / Gait

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Gait'

Author: Grafiati
Published: 4 June 2021
Last updated: 9 March 2023

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Journal articles on the topic "Gait"

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Chibirov, G. M., T. I. Dolganova, D. V. Dolganov, S. Ducic, and D. A. Popkov. "Changes in the kinematic parameters of gait in children with cerebral palsy after multilevel interventions with the initial patterns of true equinus gait and jump gait." Genij Ortopedii 25, no. 4 (December 2019): 501–9. http://dx.doi.org/10.18019/1028-4427-2019-25-4-501-509.

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Ameer, Mariam A., and Mohamed E. Khallaf. "EFFECT OF TREADMILL GAIT TRAINING ON DIPLEGIC CHILDREN SWING PHASE GAIT PARAMETERS." International Journal of Physiotherapy and Research 5, no. 1 (February 11, 2017): 1829–35. http://dx.doi.org/10.16965/ijpr.2016.200.

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Umair Bin Altaf, M., Taras Butko, and Biing-Hwang Juang. "Acoustic Gaits: Gait Analysis With Footstep Sounds." IEEE Transactions on Biomedical Engineering 62, no. 8 (August 2015): 2001–11. http://dx.doi.org/10.1109/tbme.2015.2410142.

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Fedotov, V. V. "Gait – Pathology or Physiology." Ukraïnsʹkij žurnal medicini, bìologìï ta sportu 3, no. 4 (May 18, 2018): 124–27. http://dx.doi.org/10.26693/jmbs03.04.124.

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Gao, Shuo, Jing Yun, Yumeng Zhao, and Limin Liu. "Gait‐D: Skeleton‐based gait feature decomposition for gait recognition." IET Computer Vision 16, no. 2 (November 2021): 111–25. http://dx.doi.org/10.1049/cvi2.12070.

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Kim, Youngho, and Jinbok Yi. "Gait Analysis in Normal and Hemiplegic Patients Using Accelerometers(Gait & Motion Analysis)." Proceedings of the Asian Pacific Conference on Biomechanics : emerging science and technology in biomechanics 2004.1 (2004): 113–14. http://dx.doi.org/10.1299/jsmeapbio.2004.1.113.

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Law, YC, AFT Mak, WN Wong, and M. Zhang. "THE VARIATION OF DYNAMIC FOOT PRESSURE WITH GAIT PARAMETER.(Gait & Motion Analysis)." Proceedings of the Asian Pacific Conference on Biomechanics : emerging science and technology in biomechanics 2004.1 (2004): 115–16. http://dx.doi.org/10.1299/jsmeapbio.2004.1.115.

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Hahn, Marilyn R. "Gait." Neurology Report 16, no. 1 (1992): 23–25. http://dx.doi.org/10.1097/01253086-199216010-00011.

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Dubin, Andrew. "Gait." Medical Clinics of North America 98, no. 2 (March 2014): 205–11. http://dx.doi.org/10.1016/j.mcna.2013.10.002.

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Sutherland, David H. "Dimensionless gait measurements and gait maturity." Gait & Posture 4, no. 3 (May 1996): 209–11. http://dx.doi.org/10.1016/0966-6362(95)01056-4.

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Dissertations / Theses on the topic "Gait"

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Mjaaland, Bendik Bjørklid. "Gait Mimicking : Attack Resistance Testing of Gait Authentication Systems." Thesis, Norwegian University of Science and Technology, Department of Telematics, 2009. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-8977.

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Biometric technology is rapidly evolving in today's society. A large part of the technology has its roots hundreds, or even thousands of years back in time, while other parts are new and futuristic. Research suggest that individuals can be identified by the way they walk, and this kind of biometrics, gait biometrics, is a rather new and definitely intriguing field. However, the technology is far from mature; the performance is not generally competitive to other biometrics, and it has not been thoroughly tested security-wise. This thesis aims to test the security strength of gait biometrics. It will focus on imitation, or mimicking of gait. The bottom line question is whether it is possible to learn to walk like someone else. If this turns out to be easy, it will have a severe effect on the potential of gait as an authentication mechanism in the future. The report is logically twofold. In one part, the reader is brought up to speed on the field of gait biometrics, and a software tool for gait authentication is developed and presented. Second, an experiment is conducted, involving extensive training of test subjects, and using sources of feedback like video and statistical analysis. The data is analyzed by regression, and the goal is to determine whether or not the participants are increasing their mimicking skills, or simply put: if they are learning. The first part of the experiment involves 50 participants that are successfully enrolled using the developed software. The results compete with state of the art gait technology, with an EER of 6.2%. The rest of the experiment is related to mimicking, and the thesis discovers that six out of seven participants seem to have a natural boundary to their performance, a "plateau", forcing them back whenever they attempt to improve further. The location of this plateau predetermines the outcome of an attack; for success it has to lie below the acceptance threshold corresponding to the EER. Exactly one such boundary is identified for almost all participants, but some data also indicate that more than one plateau can exist simultaneously. The final result however, is that a very limited amount of learning is present, not nearly enough to pose a threat to gait biometrics. Gait mimicking is a hard task, and our physiology works against us when we try to adopt specific gait characteristics.

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Sabir, Azhin Tahir. "Human gait recognition under neutral and non-neutral gait sequences." Thesis, University of Buckingham, 2015. http://bear.buckingham.ac.uk/115/.

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Rapid advances in biometrics technology makes their use for person‘s identity more acceptable in a variety of applications, especially in the areas of the interest in security and surveillance. The upsurge in terrorist attacks in the past few years has focused research on biometric systems that have the ability to identify individuals from a distance, and this is spearheading research interest in Gait biometric due to being unobtrusive and less dependent on high image/video quality. Gait biometric is a behavioral trait that aims to identify individuals from image sequences based on their walking style. The growing list of possible civil as well as security applications for various purposes is paralleled by the emergence of a variety of research challenges in dealing with a various external as well as internal factors influencing the performance of Gait Recognition (GR) in unconstrained recording conditions. This thesis is concerned with Gait Recognition in unconstrained scenarios aims to address research questions covering (1) The selection of sets of features for a gait signature; (2) The effects of gender and/or recoding condition case (neutral, carrying a bag, coat wearing) on the performance of GR schemes; (3) Integrating gender and/or case classifications into GR; and (4) The role of emerging Kinect sensor technology, with its capability of sensing human skeletal features in GR and applications. Accordingly, our objectives will focus on investigating, developing and testing the performance of using a variety of gait sequencefeatures for the various components/tasks and their integration. Our tests are based on large number of experiments based on CASIA B database as well as an in-house database of Kinect sensor recording. In all experiments, we use different dimension reduction and feature selection methods do reduce the dimensions in these proposed feature vectors, such as Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and Fisher Score, followed by different classification methods like; k-nearest-neighbour (k-NN), Support Vector Machine (SVM), Naive Bayes and linear discriminant classifier (LDC), to test the performance of the proposed methods. The initial part is focused on reviewing existing background removal for indoor and outdoor scenarios and developing more efficient versions primarily by adopting the work for wavelet domain rather than the traditional spatial domain based schemes. These include motion detection by frame differencing and Mixture of Gaussians, the latter being more reliable for outdoor scenarios. Subsequently, we investigated a variety of features that can be extractedfrom various subbands of wavelet-decomposed frames of different body parts (partitioned according to the golden ratio). We gradually built sets of features, together with their fused combinations, that can categorized as hybrid of model-based and motion-based models. The first list of features developed to deal with Neutral Gait Recognition (NGR) includes: Spatio-Temporal Model (STM), Legs Motion Detection Feature (LMD), and the Statistical model of the approximation LL-wavelet subband images (AWM). We shall demonstrate that fusing these features achieves accuracy of 97%, which is comparable to the state of the art. These features will be shown to achieve 96% accuracy in gender classification (GC), and we shall establish that the NGR2 scheme that integrates GC into NGR improves the accuracy by a noticeable percentage. Testing the performance of these NGR schemes in recognising non-neutral cases revealed the challenges of Unrestricted Gait Recognition (UGR). The second part of the thesis is focused on developing UGR schemes. For this, first a new statistical wavelet feature set extracted from high frequency subbands, called Detail coefficients Wavelet Model (DWM) was added to the previous list. Using different combinations of these schemes, will be shown to significantly improve the performance for non-neutral gait cases, but to less extent in the coat wearing case. We then develop a Gait Sequence Case Detection (GSCD) which has excellent performance. We will show that integrating GSCD and GC together into UGR improves the performance for all cases. We shall also investigate the different UGS scheme that generalizes existing work on Gait Energy and Gait Entropy images (GEI and GEnI) features but in the wavelet domain and in different body parts. Testing these two schemes, and their fusion, post the PCA dimension reduction yield much improved accuracy for the non-neutral cases compared to existing scheme GEI and GEnI schemes, but are significantly outperformed by the last scheme. However, by fusing the UGS scheme with the GSCD+GC+UGR scheme above we will get best accuracy that outperform the state of the art in GR specially in the non-neutral cases. The thesis ended by conducting a rather limited investigation on the use of the Kinect sensors for GR. We develop two sets of features: Horizontal Distance Features and Vertical Distance Features from small set of skeleton point trajectories. The experimental result on neutral was very successful but for the unrestricted gait recognition (with the 5 case variations) satisfactory but not optimal performance relies on the gallery including balanced number of samples from all cases.
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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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Datta, Ankur. "Gait Based Recognition." Honors in the Major Thesis, University of Central Florida, 2004. http://digital.library.ucf.edu/cdm/ref/collection/ETH/id/436.

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This item is only available in print in the UCF Libraries. If this is your Honors Thesis, you can help us make it available online for use by researchers around the world by following the instructions on the distribution consent form at http://library.ucf
Bachelors
Engineering and Computer Science
Computer Science
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Kagawa, Takahiro, and Yoji Uno. "Gait pattern generation for a power-assist device of paraplegic gait." IEEE, 2009. http://hdl.handle.net/2237/13886.

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Darbha, Naga Harika. "An Optimization Strategy for Hexapod Gait Transition." Wright State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=wright1514915943875043.

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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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Sigurnjak, S. K. "Biometric verification using gait." Thesis, Manchester Metropolitan University, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.592681.

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The work presented within this document details the development of a novel gait verification system suitable for a variety of applications such as human motion studies, medical analysis and security situations. The human gait is a spatio temporal process involving the coordination and interaction between the nervous, skeletal and muscular systems. Due to inherent variations in the limb lengths, muscle strengths and body mass gait is inherently individual. To develop a suitable feature extraction process a virtual gait laboratory was developed. The virtual laboratory contains virtual character templates articulated with a 32 bone skeleton system using motion capture data. Data was extracted from the character as a series of X, Y and Z translations for pro cessing. The virtual laboratory allows the testing of data extraction processes without the need for direct testing on human subjects. Feature extraction was performed using Principal Component Analysis (PCA). PCA allows data to be compressed and describes as a series of principal scores (PC) containing the weightings of the data. Feature extraction was performed on human subjects with the motions applied to a skeletal system containing individual physical dimensions. A second set of features was created by applying the motions to a single skeletal system. This removed the interpersonal variations from the dataset to explore the difference in classification when these variables have been removed. Overall generic motions are present within the first PC score. Higher PC scores contain unique motion characteristics suitable for classification of the subject s within a database. To verify a subject within the database Linear Discriminant Analysis (LOA) was performed. LOA projects data as a linear combination of features using a t raining data set of known outcomes. A subsequent sample can then be projected into the linear space for classification and verification of the subject within the database.
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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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Books on the topic "Gait"

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Alberto, Esquenazi, ed. Gait analysis. Philadelphia: Hanley & Belfus, 2002.

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Spiritual gait. Burnsville, MN: Cornerstone Copy Center, 2014.

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Bruckner, Jan. Gait workbook: A practical guide to clinical gait analysis. Thorofare, NJ: SLACK, Inc., 1998.

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Gait analysis: An introduction. 4th ed. Edinburgh: Butterworth-Heinemann, 2007.

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Rancho Los Amigos Medical Center. Pathokinesiology Service. and Rancho Los Amigos Medical Center. Physical Therapy Dept., eds. Observational gait analysis. Downey, CA: Los Amigos Research and Education Institute, Rancho Los Amigos Medical Center, 1993.

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The human gait. Berlin: Springer-Verlag, 1987.

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Braune, Wilhelm, and Otto Fischer. The Human Gait. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-70326-3.

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Vaughan, C. L. Gait analysis laboratory. Champaign, IL: Human Kinetics Publishers, 1992.

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L, Smidt Gary, ed. Gait in rehabilitation. New York: Churchill Livingstone, 1990.

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Bruckner, Jan. The gait workbook: A practical guide to clinical gait analysis. Thorofare, NJ: SLACK Inc., 1998.

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Book chapters on the topic "Gait"

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Gopinathan, Nirmal Raj, and Prateek Behera. "Gait." In Handbook of Clinical Examination in Orthopedics, 291–99. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1235-9_13.

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Phillips, Raymond E. "Gait." In The Physical Exam, 259–65. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63847-8_26.

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Lemelin, Pierre, and Daniel Schmitt. "Gait." In Encyclopedia of Animal Cognition and Behavior, 1–7. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-47829-6_1458-1.

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Lemelin, Pierre, and Daniel Schmitt. "Gait." In Encyclopedia of Animal Cognition and Behavior, 2847–53. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-319-55065-7_1458.

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Theologis, Tim N. "Gait Analysis." In Children's Neuromuscular Disorders, 1–8. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-552-1_1.

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Beckers, D. "Gait Training." In PNF in Practice, 237–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-34988-1_12.

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Dwyer, Maureen K. "Gait Analysis." In Hip Joint Restoration, 115–22. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4614-0694-5_10.

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Hohler, Anna DePold, and Marcus Ponce de Leon. "Gait Disorders." In Encyclopedia of Clinical Neuropsychology, 1539–40. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-57111-9_455.

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Hohler, Anna DePold, and Marcus Ponce de Leon. "Magnetic Gait." In Encyclopedia of Clinical Neuropsychology, 2062. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-57111-9_464.

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Hohler, Anna DePold, and Marcus Ponce de Leon. "Spastic Gait." In Encyclopedia of Clinical Neuropsychology, 3227–28. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-57111-9_481.

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Conference papers on the topic "Gait"

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Banka, Asif Ali, and Ajaz Hussain Mir. "Human Gait and Gait Databases." In International Conference on Computer Applications — Database Systems. Singapore: Research Publishing Services, 2010. http://dx.doi.org/10.3850/978-981-08-7300-4_1503.

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Arora, Parul, and Smriti Srivastava. "Gait recognition using gait Gaussian image." In 2015 2nd International Conference on Signal Processing and Integrated Networks (SPIN). IEEE, 2015. http://dx.doi.org/10.1109/spin.2015.7095388.

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Seo, Kap-Ho, Yongsik Park, Sungjo Yun, Sungho Park, Jungsoo Jun, and Kwang-Woo Jeon. "Gait pattern generation for gait rehabilitation." In 2013 10th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI). IEEE, 2013. http://dx.doi.org/10.1109/urai.2013.6677388.

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Bashir, K., Tao Xiang, and Shaogang Gong. "Gait recognition using gait entropy image." In 3rd International Conference on Imaging for Crime Detection and Prevention (ICDP 2009). IET, 2009. http://dx.doi.org/10.1049/ic.2009.0230.

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Babaee, Maryam, Linwei Li, and Gerhard Rigoll. "Gait Recognition from Incomplete Gait Cycle." In 2018 25th IEEE International Conference on Image Processing (ICIP). IEEE, 2018. http://dx.doi.org/10.1109/icip.2018.8451785.

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Cotton, R. James, Emoonah McClerklin, Anthony Cimorelli, Ankit Patel, and Tasos Karakostas. "Transforming Gait: Video-Based Spatiotemporal Gait Analysis." In 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE, 2022. http://dx.doi.org/10.1109/embc48229.2022.9871036.

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Shuckra, Amy, and Bruce MacWilliams. "Gait analysis utility in functional gait disorder." In 27th Annual Meeting of the GCMAS. GCMAS, 2022. http://dx.doi.org/10.52141/gcmas2022_64.

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Wang, Ya, Ping Ren, and Dennis Hong. "Gait and Gait Transition for a Robot With Two Actuated Spoke Wheels." In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-86923.

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This paper presents work on the gait and gait transition analysis for a novel mobile robot that uses two actuated spoke wheels. Gait transitions, known as acyclic feed forward patterns, allow the robot to switch from one type of gait to another during walking and turning. The mobile robot IMPASS (Intelligent Mobility Platform with Active Spoke System) uses a unique mobility concept for locomotion, thus gait transition plays an important role in generating gait patterns to walk and turn. The primary focus of this paper is how to perform gait transition between gaits in walking direction. First, the basic gait patterns for steering and straight line walking are presented. More specifically, the critical gait parameterizations and the possible foot positions in different gait patterns to produce capable steering locomotion over terrain are presented. Since IMPASS is expected to utilize its metamorphic configurations to carry out gait transitions, the extending forward and inverse analyses are also presented based on previous work about topology classification and mobility analysis for IMPASS. Then the gait transition analysis and simulation of typical patterns are performed. The results from this work lay the foundation for the future research on trajectory and path planning for IMPASS.
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Sasayama, Misako, and Toshiyuki Murakami. "Design of a gait rehabilitation system: Gait analysis and gait trajectory generation algorithm." In 2013 IEEE 22nd International Symposium on Industrial Electronics (ISIE). IEEE, 2013. http://dx.doi.org/10.1109/isie.2013.6563759.

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"SELF-ORGANISATION OF GAIT PATTERN TRANSITION - An Efficient Approach to Implementing Animal Gaits and Gait Transitions." In 5th International Conference on Informatics in Control, Automation and Robotics. SciTePress - Science and and Technology Publications, 2008. http://dx.doi.org/10.5220/0001476400750079.

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Reports on the topic "Gait"

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Brown, Ashleigh. Gait. Brooke, November 2020. http://dx.doi.org/10.46746/gaw.2020.abi.gait.

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Koch, Mark William. Recognition using gait. Office of Scientific and Technical Information (OSTI), September 2007. http://dx.doi.org/10.2172/922087.

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Vaughan, Phillip, Golnar Nabizadeh, Laura Findlay, Heather Doran, Niamh Nic Daeid, and Mark Brown. Understanding Forensic Gait Analysis #1. Edited by Chris Murray. University of Dundee, February 2020. http://dx.doi.org/10.20933/100001152.

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Weyand, Peter. Gait Dynamics and Locomotor Metabolism. Fort Belvoir, VA: Defense Technical Information Center, October 2011. http://dx.doi.org/10.21236/ada612318.

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Abdel-Malek, Karim. Advanced Prosthetic Gait Training Tool. Fort Belvoir, VA: Defense Technical Information Center, October 2013. http://dx.doi.org/10.21236/ada602320.

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Weyand, Peter. Gait Dynamics and Locomotor Metabolism. Fort Belvoir, VA: Defense Technical Information Center, May 2009. http://dx.doi.org/10.21236/ada618434.

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Abdel-Malek, Karim, Rajan Bhatt, Salam Rahmatalla, and John Yack. Advanced Prosthetic Gait Training Tool. Fort Belvoir, VA: Defense Technical Information Center, October 2014. http://dx.doi.org/10.21236/ada621304.

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Weyand, Peter. Gait Dynamics and Locomotor Metabolism. Fort Belvoir, VA: Defense Technical Information Center, December 2014. http://dx.doi.org/10.21236/ada624102.

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Nixon, Mark S., and John N. Carter. Automatic Gait Recognition for Human ID at a Distance. Fort Belvoir, VA: Defense Technical Information Center, November 2004. http://dx.doi.org/10.21236/ada457973.

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Qian, Guoping, Xiaoye Cai, Kai Xu, Hao Tian, Qiao Meng, Zbigniew Ossowski, and Jinghong Liang. Which Gait Training Intervention Can Most Effectively Improve Gait Ability in Patients with Cerebral Palsy? A Systematic Review and Network Meta-Analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, October 2022. http://dx.doi.org/10.37766/inplasy2022.10.0108.

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Abstract:
Review question / Objective: To help physiotherapists and clinicians make clinical decisions, they may wish to know, on average, "the optimal treatment", so a comprehensive and up-to-date systematic review should be conducted on the relative effectiveness of gait ability intervention programmes in patients with CP. Using NMA, this study aimed to evaluate and compare the effects of different approaches of gait training on gait ability in CP patients. The specific aim of this study was to verify the relative effectiveness of different gait interventions on the gait ability of people with CP. Condition being studied: Cerebral palsy (CP) refers to a group of disorders attributed to non-progressive brain dysfunction in the developing foetus or infant, and it is characterized by central motor and postural dysplasia.
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