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Journal articles on the topic 'Gait analysi'

Author: Grafiati
Published: 22 February 2023
Last updated: 14 March 2023

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1

Rafferty, D., and F. Bell. "Gait analysi — a semiautomated approach." Gait & Posture 3, no. 3 (September 1995): 184. http://dx.doi.org/10.1016/0966-6362(95)90016-0.

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2

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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3

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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4

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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5

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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6

Fangzhe Chen, Fangzhe Chen, Xuwei Fan Fangzhe Chen, Jianpeng Li Xuwei Fan, Min Zou Jianpeng Li, and Lianfen Huang Min Zou. "Gait Analysis Based Parkinson’s Disease Auxiliary Diagnosis System." 網際網路技術學刊 22, no. 5 (September 2021): 989–97. http://dx.doi.org/10.53106/160792642021092205005.

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7

Rana, Priyanka, Shabnam Joshi, and Monika Bodwal. "QUANTITATIVE GAIT ANALYSIS IN PATIENTS WITH KNEE OSTEOARTHRITIS." International Journal of Physiotherapy and Research 4, no. 5 (October 11, 2016): 1684–88. http://dx.doi.org/10.16965/ijpr.2016.164.

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8

Lee, S. C., S. K. Hong, K. Y. Lee, H. Y. Lee, and J. C. Ryu. "Development of Walking Pattern Analysis System (WPAS) using Inertial Sensors(Gait & Motion Analysis)." Proceedings of the Asian Pacific Conference on Biomechanics : emerging science and technology in biomechanics 2004.1 (2004): 111–12. http://dx.doi.org/10.1299/jsmeapbio.2004.1.111.

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9

Bruderer-Hofstetter, M., F. Rast, C. Bauer, E. Graf, and A. Meichtry. "Pattern recognition methods in clinical gait analysis – What do we gain?" Gait & Posture 42 (December 2015): S59. http://dx.doi.org/10.1016/j.gaitpost.2015.03.104.

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10

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 (October 11, 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, mild, and severe crouch gaits, respectively. A metric-based comparison of workspace and joint space for the three gaits for a gait cycle is conducted. In addition, gait visualization is performed using Autodesk Maya for the three anatomical planes. The obtained results allow us to determine the capabilities of the proposed methods to assess the performance of crouch gaits, using a normal pattern as a reference. Both forward and inverse kinematic methods could ultimately be applied in rehabilitation settings for the diagnosis and treatment of diseases derived from crouch gaits or other types of gait abnormalities.
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11

Kouta, Munetsugu, Koichi Shinkoda, Hirobumi Kawamura, Morihiro Tsujishita, Daisuke Okazaki, and Takamasa Tsurumi. "Affects of the speed on a series of motions that is from sitting to standing and initiating gait(Gait & Motion Analysis)." Proceedings of the Asian Pacific Conference on Biomechanics : emerging science and technology in biomechanics 2004.1 (2004): 109–10. http://dx.doi.org/10.1299/jsmeapbio.2004.1.109.

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12

Tae, Kisik, and Youngho Kim. "Postural Adjustments Against the Forward Perturbation in Standing(Gait & Motion Analysis)." Proceedings of the Asian Pacific Conference on Biomechanics : emerging science and technology in biomechanics 2004.1 (2004): 107–8. http://dx.doi.org/10.1299/jsmeapbio.2004.1.107.

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13

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

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14

Paul, J. P. "Gait analysis." Annals of the Rheumatic Diseases 48, no. 3 (March 1, 1989): 179–81. http://dx.doi.org/10.1136/ard.48.3.179.

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15

Seidel, Geoffrey K. "Gait Analysis." American Journal of Physical Medicine & Rehabilitation 72, no. 6 (December 1993): 408. http://dx.doi.org/10.1097/00002060-199312000-00016.

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16

Perry, Jacquelin, Slac k, and Jon R. Davids. "Gait Analysis." Journal of Pediatric Orthopaedics 12, no. 6 (November 1992): 815. http://dx.doi.org/10.1097/01241398-199211000-00023.

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17

Eriksson, Ejnar. "Gait analysis." Knee Surgery, Sports Traumatology, Arthroscopy 10, no. 4 (June 19, 2002): 203. http://dx.doi.org/10.1007/s00167-002-0299-6.

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18

GAGE, JAMES R. "Gait Analysis." Clinical Orthopaedics and Related Research &NA;, no. 288 (March 1993): 126???134. http://dx.doi.org/10.1097/00003086-199303000-00016.

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19

GAGE, JAMES R., PETER A. DELUCA, and THOMAS S. RENSHAW. "Gait Analysis." Journal of Bone & Joint Surgery 77, no. 10 (October 1995): 1607–23. http://dx.doi.org/10.2106/00004623-199510000-00017.

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20

Hatze, Herbert. "Gait Analysis." Journal of Motor Behavior 19, no. 2 (June 1987): 280–87. http://dx.doi.org/10.1080/00222895.1987.10735413.

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21

Daniluk, Anna, Anna Hadamus, Michał Ludwicki, and Bartłomiej Zagrodny. "Backward vs. Forward Gait Symmetry Analysis Based on Plantar Pressure Mapping." Symmetry 14, no. 2 (January 21, 2022): 203. http://dx.doi.org/10.3390/sym14020203.

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Symmetry is one of the factors analysed in normal and pathological gaits. Backward gait is an area of interest to scientists, in terms of its physiology and therapeutic possibilities. This study aimed to analyse the symmetry of the pressure parameters of backward gait in comparison to forward gait using different symmetry indices. Eighty-one healthy people aged between 19 and 84 years took part in the study. Foot pressure distribution was analysed during forward and backward gaits at self-selected speeds. Mean and maximum pressure values were calculated after dividing the foot into four or ten areas. Delta, Ratio Index, Robinson Index, Gait Asymmetry, and Symmetry Angle were calculated for each area, separately for both forward and backward gaits. Higher ratios of asymmetry were found during backward than during forward gait. Larger ratios of asymmetry were found within toes II–V, forefoot, metatarsals I, II, and III, medial and lateral heel areas. No significant correlation between symmetry indices and age or BMI was found. Results suggested that the lower symmetry of backward gait is caused by a higher number of corrective movements that allow for the maintenance of body balance and global symmetry of gait. This can be realised by increased cortical control of the backward gait, which was a new movement task for all participants.
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22

Raheem, Firas A., and Murtadha Khudhair Flayyih. "Creeping Gait Analysis and Simulation of a Quadruped Robot." Al-Khwarizmi Engineering Journal 14, no. 2 (March 14, 2019): 93–106. http://dx.doi.org/10.22153/kej.2018.12.004.

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A quadruped (four-legged) robot locomotion has the potential ability for using in different applications such as walking over soft and rough terrains and to grantee the mobility and flexibility. In general, quadruped robots have three main periodic gaits: creeping gait, running gait and galloping gait. The main problem of the quadruped robot during walking is the needing to be statically stable for slow gaits such as creeping gait. The statically stable walking as a condition depends on the stability margins that calculated particularly for this gait. In this paper, the creeping gait sequence analysis of each leg step during the swing and fixed phases has been carried out. The calculation of the minimum stability margins depends upon the forward and inverse kinematic models for each 3-DOF leg and depends on vertical geometrical projection during walking. Simulation and results verify the stability insurance after calculation the minimum margins which indicate clearly the robot COG (Center of Gravity) inside the supporting polygon resulted from the leg-tips.
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23

MARUYAMA, Hitoshi. "Movement Analysis. Gait analysis." Journal of exercise physiology 8, no. 3 (1993): 147–52. http://dx.doi.org/10.1589/rika1986.8.147.

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24

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 (March 12, 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 and Yahr stage I to II were recruited. It is difficult to collect data of abnormal gaits of the PD patients; therefore, ranges of the gait cycle parameters of abnormal gaits of PD patients were estimated statistically based on the "lower confidence limit" of the gait cycle parameters of their normal gaits. These results may lead to the future development of wearable sensors enabling real-time recognition of abnormal gaits of PD patients. Ambulatory rehabilitation, gait assessment and personal telecare for people with gait disorders are also possible applications.
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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

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 balanced overall gait asymmetry. The study presented here compares the combined gait parameters with clinical measures such as timed up and go (TUG), six-minute walk test (6MWT), and gait velocity. The comparisons are made on gait data collected on individuals with stroke before and after twelve sessions of rehabilitation. Step length, step time, and swing time showed a strong correlation to CGAM, but the double limb support asymmetry has nearly no correlation with CGAM and ground reaction force asymmetry has a weak correlation. The CGAM scores were moderately correlated with TUG and strongly correlated to 6MWT and gait velocity.
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27

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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28

Rui, Jing, M. Brett Runge, Robert J. Spinner, Michael J. Yaszemski, Anthony J. Windebank, and Huan Wang. "Gait Cycle Analysis." Annals of Plastic Surgery 73, no. 4 (October 2014): 405–11. http://dx.doi.org/10.1097/sap.0000000000000008.

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29

Kyriazis, Vasilios. "Gait analysis techniques." Journal of Orthopaedics and Traumatology 2, no. 1 (November 2001): 1–6. http://dx.doi.org/10.1007/pl00012205.

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30

Murphy, A. J., P. J. Rowe, R. J. Bowers, and C. B. Meadows. "Accessible gait analysis." Gait & Posture 36 (June 2012): S73—S74. http://dx.doi.org/10.1016/j.gaitpost.2011.10.307.

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31

Davis, R. B. "Clinical gait analysis." IEEE Engineering in Medicine and Biology Magazine 7, no. 3 (September 1988): 35–40. http://dx.doi.org/10.1109/51.7933.

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32

Gonzalez-Islas, Juan Carlos, Omar Arturo Dominguez-Ramirez, Heydy Castillejos-Fernandez, and Felix Agustin Castro-Espinoza. "Human gait analysis based on automatic recognition: A review." Pädi Boletín Científico de Ciencias Básicas e Ingenierías del ICBI 10, Especial3 (August 31, 2022): 13–21. http://dx.doi.org/10.29057/icbi.v10iespecial3.8927.

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Gait analysis is one of the most important challenging research areas in clinical and computing settings. Gait biomechanics and gait human recognition are two major areas of interest. Alterations in walking can cause physical and metal health problems in people, so diagnoses and treatments derived from optimal gait analysis are very useful in clinical settings. This paper surveys the gait analysis methods, applications and platforms, gait biomechanics, as well as, gait recognition approaches, and datasets. Then, we describe contributions in gait forward kinematics, useful to assess gaits such as crouched and normal. Also, a framework for antalgic gait recognition based on human activity, using the gyroscope embedded in a smartphone is described. Different algorithms and metrics were used to perform the gait recognition, highlighting Support Vector Machines, Naive Bayes, k- Nearest Neighbours, and Accuracy and F-measure, respectively. Finally, we discuss the challenges and future perspectives on gait recognition.
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33

Kim, Jaewook, Yekwang Kim, and Seung-Jong Kim. "Biomechanical Task-Based Gait Analysis Suggests ReWalk Gait Resembles Crutch Gait." Applied Sciences 12, no. 24 (December 8, 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 because the joint movements and muscle recruitment patterns deviate from those of natural gait. This raises concerns because repetitive training with these devices may not lead to desirable rehabilitative gains. In this study, we compare the lower limb joint angles and electromyography patterns of healthy subjects walking with and without ReWalk in accordance with the three major biomechanical tasks required by bipedal gait: weight acceptance (WA), single-limb support, and limb advancement. Furthermore, we investigate whether the physical constraints of ReWalk, most noticeably the use of crutches and fixed ankle joints, were responsible for the specific changes by conducting additional walking sessions with either crutches or ankle foot orthoses. The results from the six healthy male volunteers suggest that the gait patterns observed with ReWalk deviate significantly from those of natural gait, particularly during the WA, and closely resemble those of crutch gait.
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34

Takeda, Ryo, Shigeru Tadano, Masahiro Todoh, and Satoshi Yoshinari. "GAIT ANALYSIS USING WIRELESS ACCELERATION SENSORS AND GYRO SENSORS(1B3 Orthopaedic & Rehabilitation Biomechanics III)." Proceedings of the Asian Pacific Conference on Biomechanics : emerging science and technology in biomechanics 2007.3 (2007): S35. http://dx.doi.org/10.1299/jsmeapbio.2007.3.s35.

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35

Ueki, Riki, Masamori Shigematsu, Takami Higo, Tsutomu Motooka, and Takao Hotokebuchi. "Quantitative Gait Evaluation of Coxarthrosis Using Gait Analysis." Orthopedics & Traumatology 54, no. 4 (2005): 664–67. http://dx.doi.org/10.5035/nishiseisai.54.664.

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36

MIYASHITA, Hirotada, Hideyasu SUMIYA, and Masatake SHIRAISHI. "304 Gait Assessment from Human Gait Pattern Analysis." Proceedings of Ibaraki District Conference 2008 (2008): 65–66. http://dx.doi.org/10.1299/jsmeibaraki.2008.65.

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37

Xia, Yi, Qiang Ye, Qingwei Gao, Yixiang Lu, and Dexiang Zhang. "Symmetry Analysis of Gait between Left and Right Limb Using Cross-Fuzzy Entropy." Computational and Mathematical Methods in Medicine 2016 (2016): 1–9. http://dx.doi.org/10.1155/2016/1737953.

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The purpose of this paper is the investigation of gait symmetry problem by using cross-fuzzy entropy (C-FuzzyEn), which is a recently proposed cross entropy that has many merits as compared to the frequently used cross sample entropy (C-SampleEn). First, we used several simulation signals to test its performance regarding the relative consistency and dependence on data length. Second, the gait time series of the left and right stride interval were used to calculate the C-FuzzyEn values for gait symmetry analysis. Besides the statistical analysis, we also realized a support vector machine (SVM) classifier to perform the classification of normal and abnormal gaits. The gait dataset consists of 15 patients with Parkinson’s disease (PD) and 16 control (CO) subjects. The results show that the C-FuzzyEn values of the PD patients’ gait are significantly higher than that of the CO subjects with apvalue of less than10-5, and the best classification performance evaluated by a leave-one-out (LOO) cross-validation method is an accuracy of 96.77%. Such encouraging results imply that the C-FuzzyEn-based gait symmetry measure appears as a suitable tool for analyzing abnormal gaits.
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38

Min, Byungeui, Zeungnam Bien, and Seungku Hwangt†. "Basic characteristics and stability properties of quadruped crab gaits." Robotica 11, no. 3 (May 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. Finally, we consider the effects of variations of footholds on stability and maximum permissible stroke in terms of support boundary angle. The results derived in this paper contain previous works on the forward walking gait as a special case of the crab gait.
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39

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 (December 20, 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, and it is systematically classified by two parameters. By using this classification method, suitable gaits for static walking and dynamic walking are selected. The other is the adaptive gait. In order to realize their potentials, walking robots must sense the walking conditions and change their gaits. Two adaptive gait schemes are proposed in this paper. One is a gait which adapts to the position of the center of gravity, and the other is a gait for incline terrain. Both gaits use force sensor data for detecting changes in the walking conditions. All the gaits discussed in this paper are experimentally evaluated.
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40

Shen, Zhe, and Takeshi Tsuchiya. "Gait Analysis for a Tiltrotor: The Dynamic Invertible Gait." Robotics 11, no. 2 (March 16, 2022): 33. http://dx.doi.org/10.3390/robotics11020033.

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A conventional feedback-linearization-based controller, when applied to a tiltrotor (eight inputs), results in extensive changes in tilting angles, which are not expected in practice. To solve this problem, we introduce the novel concept of “UAV gait” to restrict the tilting angles. The gait plan was initially used to solve the control problems in quadruped (four-legged) robots. Applying this approach, accompanied by feedback linearization, to a tiltrotor may give rise to the well-known non-invertible problem in the decoupling matrix. In this study, we explored invertible gait in a tiltrotor, and applied feedback linearization to stabilize the attitude and the altitude. The conditions necessary to achieve a full-rank decoupling matrix were deduced and simplified to near-zero roll and zero pitch. This paper proposes several invertible gaits to conduct an attitude–altitude control test. The accepted gaits within the region of interest were visualized. The simulation was conducted in Simulink, MATLAB. The results show promising responses in stabilizing attitude and altitude.
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QIU, SEN, Huihui Wang, Jie Li, Hongyu Zhao, Zhelong Wang, Jiaxin Wang, Qiong Wang, et al. "Towards Wearable-Inertial-Sensor-Based Gait Posture Evaluation for Subjects with Unbalanced Gaits." Sensors 20, no. 4 (February 21, 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 a clue for how to learn more about gait postureand how wearable gait analysis can enhance clinical outcomes. With an ever-expanding gait database,it is possible to help physiotherapists to quickly discover the causes of abnormal gaits, sports injuryrisks, and chronic pain, and provides guidance for arranging personalized rehabilitation programsfor patients. The proposed framework may eventually become a useful tool for continually monitoringspatio-temporal gait parameters and decision-making in an ambulatory environment.
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42

Li, Mengxuan, Shanshan Tian, Linlin Sun, and Xi Chen. "Gait Analysis for Post-Stroke Hemiparetic Patient by Multi-Features Fusion Method." Sensors 19, no. 7 (April 11, 2019): 1737. http://dx.doi.org/10.3390/s19071737.

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Walking is a basic requirement for participating in daily activities. Neurological diseases such as stroke can significantly affect one’s gait and thereby restrict one’s activities that are a part of daily living. Previous studies have demonstrated that gait temporal parameters are useful for characterizing post-stroke hemiparetic gait. However, no previous studies have investigated the symmetry, regularity and stability of post-stroke hemiparetic gaits. In this study, the dynamic time warping (DTW) algorithm, sample entropy method and empirical mode decomposition-based stability index were utilized to obtain the three aforementioned types of gait features, respectively. Studies were conducted with 15 healthy control subjects and 15 post-stroke survivors. Experimental results revealed that the proposed features could significantly differentiate hemiparetic patients from healthy control subjects by a Mann–Whitney test (with a p-value of less than 0.05). Finally, four representative classifiers were utilized in order to evaluate the possible capabilities of these features to distinguish patients with hemiparetic gaits from the healthy control subjects. The maximum area under the curve values were shown to be 0.94 by the k-nearest-neighbor (kNN) classifier. These promising results have illustrated that the proposed features have considerable potential to promote the future design of automatic gait analysis systems for clinical practice.
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43

Viehweger, E., L. Zürcher Pfund, M. Hélix, M. A. Rohon, M. Jacquemier, D. Scavarda, J. L. Jouve, G. Bollini, A. Loundou, and M. C. Simeoni. "Influence of clinical and gait analysis experience on reliability of observational gait analysis (Edinburgh Gait Score Reliability)." Annals of Physical and Rehabilitation Medicine 53, no. 9 (November 2010): 535–46. http://dx.doi.org/10.1016/j.rehab.2010.09.002.

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44

NAKAMURA, HIDETOMO. "Gait Analysis in Coxarthrosis." Kurume Medical Journal 46, no. 1 (1999): 1–7. http://dx.doi.org/10.2739/kurumemedj.46.1.

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45

Curran, Sarah A., and Howard J. Dananberg. "Future of Gait Analysis." Journal of the American Podiatric Medical Association 95, no. 2 (March 1, 2005): 130–42. http://dx.doi.org/10.7547/0950130.

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Despite the plethora of information on human gait analysis, its continued use as a clinical tool remains uncertain. Analysis of gait dysfunction has become integral to podiatric medical practice, and, like many specialized fields, it is rapidly changing to meet the needs of the future. Practice in the 21st century is predicated on the concept of multidisciplinary working approaches and a growing trend toward evidence-based practice, in which gait analysis could play a prominent role. This article provides a historical synopsis of instrumented gait analysis and its associated subcomponents and discusses the salient issues concerning its future role in podiatric medicine. (J Am Podiatr Med Assoc 95(2): 130–142, 2005)
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ISHIKAWA, Kazuo, Yan WANG, Yutaka SHIBATA, Weng Hoe WONG, and Yoshiaki ITASAKA. "Vertigo and Gait Analysis." Practica Oto-Rhino-Laryngologica 95, no. 5 (2002): 427–36. http://dx.doi.org/10.5631/jibirin.95.427.

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Ueki, Riki, Masamori Shigematsu, Tsutomu Motooka, and Takao Hotokebuchi. "Gait Analysis in Coxarthrosis." Orthopedics & Traumatology 54, no. 1 (2005): 173–75. http://dx.doi.org/10.5035/nishiseisai.54.173.

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CONDIE, DAVID N. "Gait Analysis — An Introduction." International Journal of Rehabilitation Research 15, no. 2 (June 1992): 181. http://dx.doi.org/10.1097/00004356-199206000-00017.

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Ranu, Harcharan Singh. "Gait Analysis of Amputees." Medicine & Science in Sports & Exercise 39, Supplement (May 2007): S261. http://dx.doi.org/10.1249/01.mss.0000274000.36138.b2.

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Sackley, Cath. "Gait Analysis — An introduction." Physiotherapy 82, no. 11 (November 1996): 641. http://dx.doi.org/10.1016/s0031-9406(05)66357-2.

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