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Journal articles on the topic 'Gait'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

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 (2019): 501–9. http://dx.doi.org/10.18019/1028-4427-2019-25-4-501-509.

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2

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 (2015): 2001–11. http://dx.doi.org/10.1109/tbme.2015.2410142.

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3

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 (2017): 1829–35. http://dx.doi.org/10.16965/ijpr.2016.200.

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4

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 (2021): 111–25. http://dx.doi.org/10.1049/cvi2.12070.

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5

Tang, Chaoquan, Lulu Sun, Gongbo Zhou, Xin Shu, Hongwei Tang, and Hao Wu. "Gait Generation Method of Snake Robot Based on Main Characteristic Curve Fitting." Biomimetics 8, no. 1 (2023): 105. http://dx.doi.org/10.3390/biomimetics8010105.

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Gait generation method is one of the important contents of snake robot motion control. Different gait generation methods produce completely different forms of control functions, so snake robots need more complicated programming logic and processes to realize various gaits and their transformation. Therefore, we propose a new unified expression of gait method, The MCC (main characteristics control) method simplifies and unifies the control functions of different snake robots gaits by extracting the main features of the backbone curves of snake robots gaits. Since all periodic curves that meet t

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6

Su, Rung-Hung, Yeh-Liang Hsu, Lung Chan, Hanjun Lin, and Che-Chang Yang. "ASSESSING ABNORMAL GAITS OF PARKINSON'S DISEASE PATIENTS USING A WEARABLE MOTION DETECTOR." Biomedical Engineering: Applications, Basis and Communications 26, no. 02 (2014): 1450031. http://dx.doi.org/10.4015/s1016237214500318.

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Accelerometers have been widely used in wearable systems for gait analysis. Several gait cycle parameters are provided to quantify the level of gait regularity and symmetry. This study attempts to assess abnormal gaits of Parkinson disease (PD) patients based on the gait cycle parameters derived in real-time from an accelerometry-based wearable motion detector (WMD). The results of an experiment with 25 healthy young adults showed that there were significant differences between gait cycle parameters of normal gaits and abnormal gaits derived from the WMD. Five PD patients diagnosed as Hoehn an

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Shen, Zhe, Yudong Ma, and Takeshi Tsuchiya. "Four-Dimensional Gait Surfaces for a Tilt-Rotor—Two Color Map Theorem." Drones 6, no. 5 (2022): 103. http://dx.doi.org/10.3390/drones6050103.

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This article presents the four-dimensional surfaces that guide the gait plan for a tilt-rotor. The previous gaits analyzed in the tilt-rotor research are inspired by animals; no theoretical base backs the robustness of these gaits. This research deduces the gaits by diminishing the adverse effect of the attitude of the tilt-rotor for the first time. Four-dimensional gait surfaces are subsequently found on which the gaits are expected to be robust to the attitude. These surfaces provide the region where the gait is suggested to be planned. However, a discontinuous region may hinder the gait pla

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8

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

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9

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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10

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

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11

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

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12

Kim, Min-Jung, Ji-Hun Han, Woo-Chul Shin, and Youn-Sik Hong. "Gait Pattern Identification Using Gait Features." Electronics 13, no. 10 (2024): 1956. http://dx.doi.org/10.3390/electronics13101956.

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Gait analysis plays important roles in various applications such as exercise therapy, biometrics, and robot control. It can also be used to prevent and improve movement disorders and monitor health conditions. We implemented a wearable module equipped with an MPU-9250 IMU sensor, and Bluetooth modules were implemented on an Arduino Uno R3 board for gait analysis. Gait cycles were identified based on roll values measured by the accelerometer embedded in the IMU sensor. By superimposing the gait cycles that occurred during the walking period, they could be analyzed using statistical methods. We

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13

Kim, Jaewook, Yekwang Kim, and Seung-Jong Kim. "Biomechanical Task-Based Gait Analysis Suggests ReWalk Gait Resembles Crutch Gait." Applied Sciences 12, no. 24 (2022): 12574. http://dx.doi.org/10.3390/app122412574.

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Current gait rehabilitation strategies rely heavily on motor learning principles, which involve facilitating active patient participation, high-doses of biomechanical task-related motor activities and accurate feedback. Furthermore, appropriate muscle groups need to be recruited for the joint movements that constitute the biomechanical task-related activities in order to effectively promote motor learning. Recently, exoskeleton-type robots utilizing crutches have been incorporated into overground gait rehabilitation programs. However, it is unclear which gait-related tasks are being trained be

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14

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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15

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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16

Bai, Long, Hao Hu, Xiaohong Chen, Yuanxi Sun, Chaoyang Ma, and Yuanhong Zhong. "CPG-Based Gait Generation of the Curved-Leg Hexapod Robot with Smooth Gait Transition." Sensors 19, no. 17 (2019): 3705. http://dx.doi.org/10.3390/s19173705.

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This paper presents a novel CPG-based gait generation of the curved-leg hexapod robot that can enable smooth gait transitions between multi-mode gaits. First, the locomotion of the curved leg and instability during the gait transitions are analyzed. Then, a modified Hopf oscillator is applied in the CPG control, which can realize multiple gaits by adjusting a simple parameter. In addition, a smooth gait switching method is also proposed via smooth gait transition functions and gait planning. Tripod gait, quadruped gait, and wave gait are planned for the hexapod robot to achieve quick and stabl

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17

Gonzalez-Islas, Juan-Carlos, Omar-Arturo Dominguez-Ramirez, Omar Lopez-Ortega, Jonatan Peña-Ramirez, Jesus-Patricio Ordaz-Oliver, and Francisco Marroquin-Gutierrez. "Crouch Gait Analysis and Visualization Based on Gait Forward and Inverse Kinematics." Applied Sciences 12, no. 20 (2022): 10197. http://dx.doi.org/10.3390/app122010197.

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Crouch gait is one of the most common gait abnormalities; it is usually caused by cerebral palsy. There are few works related to the modeling of crouch gait kinematics, crouch gait analysis, and visualization in both the workspace and joint space. In this work, we present a quaternion-based method to solve the forward kinematics of the position of the lower limbs during walking. For this purpose, we propose a modified eight-DoF human skeletal model. Using this model, we present a geometric method to calculate the gait inverse kinematics. Both methods are applied for gait analysis over normal,

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18

KITADA, Tatuo, Koji ITO, Yasuro KUROSE, and Yoshimasa UMENO. "A KNOWLEDGE-BASED GAIT ANALYSIS SUPPORTING SYSTEM (GAITS)." Biomechanisms 9 (1988): 207–16. http://dx.doi.org/10.3951/biomechanisms.9.207.

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19

Henderson, Adrienne D., A. Wayne Johnson, Sarah T. Ridge, et al. "Diabetic Gait Is Not Just Slow Gait: Gait Compensations in Diabetic Neuropathy." Journal of Diabetes Research 2019 (November 11, 2019): 1–9. http://dx.doi.org/10.1155/2019/4512501.

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Background. Neuropathic complications from diabetes mellitus affect multiple nerve types and may manifest in gait. However, gait compensations are still poorly understood, as narrow analyses and lack of speed controls have contributed to conflicting or equivocal results. Purpose. To evaluate gait mechanics and energetics in diabetic peripheral polyneuropathy. Methods. Instrumented gait analysis was performed on 14 participants with diabetic peripheral polyneuropathy and 14 matched controls, walking at 1.0 m/s. A full-body model with a multisegment foot was used to calculate inverse dynamics an

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20

Tadano, Shigeru, Ryo Takeda, Keita Sasaki, Tadashi Fujisawa, and Harukazu Tohyama. "Gait characterization for osteoarthritis patients using wearable gait sensors (H-Gait systems)." Journal of Biomechanics 49, no. 5 (2016): 684–90. http://dx.doi.org/10.1016/j.jbiomech.2016.01.017.

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21

Van Nuffel, A., M. Sprenger, FAM Tuyttens, and W. Maertens. "Cow gait scores and kinematic gait data: can people see gait irregularities?" Animal Welfare 18, no. 4 (2009): 433–39. http://dx.doi.org/10.1017/s0962728600000841.

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AbstractIncreasing lameness problems associated with intensified dairy cattle production has lead to the development of several techniques to automatically detect these problems. Comparisons of these new measuring techniques of cow locomotion with the conventional subjective observer scoring are scarce. In order to better understand human observers’ gait scoring, cows walking on a pressure-sensitive mat were evaluated for kinematic gait variables and a visual assessment of gait was also made via video recording. Forty of these videos were used for subjective gait scoring on a 3-point scale, an

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22

Koo, Dohoon, Won-Kyung Song, Sungpil Kim, Hyeongsic Kim, and Seondeok Eun. "PS5-17 COMPARISON OF GAIT PATTERN WITH THE 4 LINKED GAIT TRAINER (GTR) AND TREADMILL GAIT(PS5: Poster Short Presentation V,Poster Session)." Proceedings of the Asian Pacific Conference on Biomechanics : emerging science and technology in biomechanics 2015.8 (2015): 314. http://dx.doi.org/10.1299/jsmeapbio.2015.8.314.

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23

Mogan, Jashila Nair, Chin Poo Lee, Kian Ming Lim, and Kalaiarasi Sonai Muthu. "Gait-ViT: Gait Recognition with Vision Transformer." Sensors 22, no. 19 (2022): 7362. http://dx.doi.org/10.3390/s22197362.

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Identifying an individual based on their physical/behavioral characteristics is known as biometric recognition. Gait is one of the most reliable biometrics due to its advantages, such as being perceivable at a long distance and difficult to replicate. The existing works mostly leverage Convolutional Neural Networks for gait recognition. The Convolutional Neural Networks perform well in image recognition tasks; however, they lack the attention mechanism to emphasize more on the significant regions of the image. The attention mechanism encodes information in the image patches, which facilitates

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24

Yao, Lingxiang, Worapan Kusakunniran, Qiang Wu, and Jian Zhang. "Gait recognition using a few gait frames." PeerJ Computer Science 7 (March 1, 2021): e382. http://dx.doi.org/10.7717/peerj-cs.382.

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Gait has been deemed as an alternative biometric in video-based surveillance applications, since it can be used to recognize individuals from a far distance without their interaction and cooperation. Recently, many gait recognition methods have been proposed, aiming at reducing the influence caused by exterior factors. However, most of these methods are developed based on sufficient input gait frames, and their recognition performance will sharply decrease if the frame number drops. In the real-world scenario, it is impossible to always obtain a sufficient number of gait frames for each subjec

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25

Yanagizono, Taiichiro, Seiji Higuchi, Risa Kondo, Yoko Katsushima, Ichiro Kadouchi, and Akihiro Kawano. "Gait Analysis Using the Gillete Gait Index." Orthopedics & Traumatology 59, no. 2 (2010): 293–95. http://dx.doi.org/10.5035/nishiseisai.59.293.

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26

Zongyi Liu and S. Sarkar. "Improved gait recognition by gait dynamics normalization." IEEE Transactions on Pattern Analysis and Machine Intelligence 28, no. 6 (2006): 863–76. http://dx.doi.org/10.1109/tpami.2006.122.

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27

Ramakrishnan, Tyagi, Seok Hun Kim, and Kyle B. Reed. "Human Gait Analysis Metric for Gait Retraining." Applied Bionics and Biomechanics 2019 (November 11, 2019): 1–8. http://dx.doi.org/10.1155/2019/1286864.

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The combined gait asymmetry metric (CGAM) provides a method to synthesize human gait motion. The metric is weighted to balance each parameter’s effect by normalizing the data so all parameters are more equally weighted. It is designed to combine spatial, temporal, kinematic, and kinetic gait parameter asymmetries. It can also combine subsets of the different gait parameters to provide a more thorough analysis. The single number quantifying gait could assist robotic rehabilitation methods to optimize the resulting gait patterns. CGAM will help define quantitative thresholds for achievable balan

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28

Souza, R. "ABCs of gait and running gait analysis." Osteoarthritis and Cartilage 27 (April 2019): S18. http://dx.doi.org/10.1016/j.joca.2019.02.018.

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29

Adachi, Hironori, Noriho Koyachi, Tatsuya Nakamura, and Eiji Nakano. "Development of Quadruped Walking Robots and Their Gait Study." Journal of Robotics and Mechatronics 5, no. 6 (1993): 548–60. http://dx.doi.org/10.20965/jrm.1993.p0548.

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This paper describes the quadruped walking robots developed at the Mechanical Engineering Laboratory and their gait analysis. Legged locomotion has the potential to adapt itself to changes in walking conditions, but also has problems such as complexity. To overcome these problems, a new link mechanism called ASTBALLEM is used for the legs of the robots, and highly rigid and easily controllable legs are constructed by using this mechanism. To make a legged robot walk stably, it is necessary to provide a suitable gait. In this paper, two kinds of gaits are considered. One is the periodic gait, a

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30

Wang, Fu-Cheng, Szu-Fu Chen, Chin-Hsien Lin, et al. "Detection and Classification of Stroke Gaits by Deep Neural Networks Employing Inertial Measurement Units." Sensors 21, no. 5 (2021): 1864. http://dx.doi.org/10.3390/s21051864.

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This paper develops Deep Neural Network (DNN) models that can recognize stroke gaits. Stroke patients usually suffer from partial disability and develop abnormal gaits that can vary widely and need targeted treatments. Evaluation of gait patterns is crucial for clinical experts to make decisions about the medication and rehabilitation strategies for the stroke patients. However, the evaluation is often subjective, and different clinicians might have different diagnoses of stroke gait patterns. In addition, some patients may present with mixed neurological gaits. Therefore, we apply artificial

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31

Min, Byungeui, Zeungnam Bien, and Seungku Hwangt†. "Basic characteristics and stability properties of quadruped crab gaits." Robotica 11, no. 3 (1993): 233–43. http://dx.doi.org/10.1017/s0263574700016106.

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SUMMARYIn this paper, we investigate the crab gaits of a quadruped. Some important characteristics that simplify the analysis of crab gaits are presented, and several formulas for optimizing the longitudinal gait stability margin of a quadruped crab gait are derived by incorporating the time weighting factor. The analysis and implementation of the gait have been simplified by employing a pseudo-world coordinate frame as a reference frame for describing footholds and vehicle's motion. We also suggest a unique gait which optimizes gait stability margin according to the range of crab angle. Final

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32

QIU, SEN, Huihui Wang, Jie Li, et al. "Towards Wearable-Inertial-Sensor-Based Gait Posture Evaluation for Subjects with Unbalanced Gaits." Sensors 20, no. 4 (2020): 1193. http://dx.doi.org/10.3390/s20041193.

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Human gait reflects health condition and is widely adopted as a diagnostic basisin clinical practice. This research adopts compact inertial sensor nodes to monitor the functionof human lower limbs, which implies the most fundamental locomotion ability. The proposedwearable gait analysis system captures limb motion and reconstructs 3D models with high accuracy.It can output the kinematic parameters of joint flexion and extension, as well as the displacementdata of human limbs. The experimental results provide strong support for quick access to accuratehuman gait data. This paper aims to provide

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33

Park, Sunwoo, Soonjae Ahn, Isu Shin, and Youngho Kim. "PS5-18 Influence of cadence on basic gait parameters in gait initiation, constant-speed walking and gait termination(PS5: Poster Short Presentation V,Poster Session)." Proceedings of the Asian Pacific Conference on Biomechanics : emerging science and technology in biomechanics 2015.8 (2015): 315. http://dx.doi.org/10.1299/jsmeapbio.2015.8.315.

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34

Li, Chenghao, Kah Phooi Seng, and Li-Minn Ang. "Gait-To-Gait Emotional Human–Robot Interaction Utilizing Trajectories-Aware and Skeleton-Graph-Aware Spatial–Temporal Transformer." Sensors 25, no. 3 (2025): 734. https://doi.org/10.3390/s25030734.

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The emotional response of robotics is crucial for promoting the socially intelligent level of human–robot interaction (HRI). The development of machine learning has extensively stimulated research on emotional recognition for robots. Our research focuses on emotional gaits, a type of simple modality that stores a series of joint coordinates and is easy for humanoid robots to execute. However, a limited amount of research investigates emotional HRI systems based on gaits, indicating an existing gap in human emotion gait recognition and robotic emotional gait response. To address this challenge,

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35

Millichap, J. Gordon. "Hysterical Gait." Pediatric Neurology Briefs 2, no. 5 (1988): 39. http://dx.doi.org/10.15844/pedneurbriefs-2-5-13.

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36

Gibson, Margaret E., and Natalie Stork. "Gait Disorders." Primary Care: Clinics in Office Practice 48, no. 3 (2021): 395–415. http://dx.doi.org/10.1016/j.pop.2021.04.004.

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37

Sudarsky, Lewis. "Gait Failure." Emergency Medicine Clinics of North America 5, no. 4 (1987): 677–85. http://dx.doi.org/10.1016/s0733-8627(20)30123-1.

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38

Van Wassen, Cathleen. "Gait Trick." Brain & Life 18, no. 1 (2022): 4. http://dx.doi.org/10.1097/01.nnn.0000820788.60403.6c.

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39

Kim, Byung Gon, and Jae Kyu Roh. "Gait Disturbance." Journal of the Korean Medical Association 40, no. 4 (1997): 501. http://dx.doi.org/10.5124/jkma.1997.40.4.501.

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40

Xu, Weitao, Chitra Javali, Girish Revadigar, Chengwen Luo, Neil Bergmann, and Wen Hu. "Gait-Key." ACM Transactions on Sensor Networks 13, no. 1 (2017): 1–27. http://dx.doi.org/10.1145/3023954.

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41

DeLuca, Peter A. "Gait analysis." Current Opinion in Orthopaedics 4, no. 6 (1993): 101–4. http://dx.doi.org/10.1097/00001433-199312000-00018.

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42

Nandhagopal, R. "Unsteady gait." Postgraduate Medical Journal 82, no. 967 (2006): e7-e7. http://dx.doi.org/10.1136/pgmj.2005.040774.

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43

Paul, J. P. "Gait analysis." Annals of the Rheumatic Diseases 48, no. 3 (1989): 179–81. http://dx.doi.org/10.1136/ard.48.3.179.

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44

Fisher, C. M. "Gait disorders." Neurology 44, no. 4 (1994): 779. http://dx.doi.org/10.1212/wnl.44.4.779-a.

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45

Nutt, J. G., D. C. Marsden, and P. D. Thompson. "Gait disorders." Neurology 44, no. 4 (1994): 780. http://dx.doi.org/10.1212/wnl.44.4.780.

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46

Beard, Jonathan. "Odd Gait." Scientific American Mind 17, no. 1 (2006): 8. http://dx.doi.org/10.1038/scientificamericanmind0206-8b.

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47

Fiol-Matta, Licia. "Chencha's gait." Women & Performance: a journal of feminist theory 18, no. 3 (2008): 287–301. http://dx.doi.org/10.1080/07407700802496041.

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48

Li, Li. "Gait Stability." Medicine & Science in Sports & Exercise 41 (May 2009): 23. http://dx.doi.org/10.1249/01.mss.0000352812.38243.a0.

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49

Down, J. "Kangaroo gait." Veterinary Record 119, no. 1 (1986): 23. http://dx.doi.org/10.1136/vr.119.1.23-a.

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Down, J. "Kangaroo gait." Veterinary Record 119, no. 10 (1986): 255. http://dx.doi.org/10.1136/vr.119.10.255-b.

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