Relevant bibliographies by topics / Stance phase of gait

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

Academic literature on the topic 'Stance phase of gait'

Author: Grafiati
Published: 4 June 2021
Last updated: 9 February 2022

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Journal articles on the topic "Stance phase of gait"

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Ando, Takeshi, Eiichi Ohki, Yasutaka Nakashima, Yutaka Akita, Hiroshi Iijima, Osamu Tanaka, and Masakatsu G. Fujie. "Pilot Study of Split Belt Treadmill Based Gait Rehabilitation System for Symmetric Stroke Gait." Journal of Robotics and Mechatronics 24, no. 5 (October 20, 2012): 884–93. http://dx.doi.org/10.20965/jrm.2012.p0884.

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A split belt treadmill for gait rehabilitation was developed to improve the symmetry of the stance phase time of patients with stroke. The system, which increases the stance phase time of the affected leg and then realizes a well-balanced gait, is divided into two components. First, the stance phases of the sound and affected legs were measured and presented visually in real time to the patient and physical therapist as biofeedback. Second, using stance phase biofeedback, the physical therapist sets two different velocities of treadmill belts for sound and affected legs. In an experiment, 11 patients with chronic stroke participated in a short-term intervention trial (20 gait cycles) of the developed treadmill system. Three of the five subjects who had lost balance between the stance phase of the sound leg and that of the affected one improved their gait balance in the intervention trial. In addition, one subject kept the well-balanced gait after the intervention.
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Su, Binbin, and Elena M. Gutierrez-Farewik. "Gait Trajectory and Gait Phase Prediction Based on an LSTM Network." Sensors 20, no. 24 (December 12, 2020): 7127. http://dx.doi.org/10.3390/s20247127.

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Lower body segment trajectory and gait phase prediction is crucial for the control of assistance-as-needed robotic devices, such as exoskeletons. In order for a powered exoskeleton with phase-based control to determine and provide proper assistance to the wearer during gait, we propose an approach to predict segment trajectories up to 200 ms ahead (angular velocity of the thigh, shank and foot segments) and five gait phases (loading response, mid-stance, terminal stance, preswing and swing), based on collected data from inertial measurement units placed on the thighs, shanks, and feet. The approach we propose is a long-short term memory (LSTM)-based network, a modified version of recurrent neural networks, which can learn order dependence in sequence prediction problems. The algorithm proposed has a weighted discount loss function that places more weight in predicting the next three to five time frames but also contributes to an overall prediction performance for up to 10 time frames. The LSTM model was designed to learn lower limb segment trajectories using training samples and was tested for generalization across participants. All predicted trajectories were strongly correlated with the measured trajectories, with correlation coefficients greater than 0.98. The proposed LSTM approach can also accurately predict the five gait phases, particularly swing phase with 95% accuracy in inter-subject implementation. The ability of the LSTM network to predict future gait trajectories and gait phases can be applied in designing exoskeleton controllers that can better compensate for system delays to smooth the transition between gait phases.
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Iosa, Marco, Augusto Fusco, Fabio Marchetti, Giovanni Morone, Carlo Caltagirone, Stefano Paolucci, and Antonella Peppe. "The Golden Ratio of Gait Harmony: Repetitive Proportions of Repetitive Gait Phases." BioMed Research International 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/918642.

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In nature, many physical and biological systems have structures showing harmonic properties. Some of them were found related to the irrational number known as the golden ratio that has important symmetric and harmonic properties. In this study, the spatiotemporal gait parameters of 25 healthy subjects were analyzed using a stereophotogrammetric system with 25 retroreflective markers located on their skin. The proportions of gait phases were compared with , the value of which is about 1.6180. The ratio between the entire gait cycle and stance phase resulted in 1.620 ± 0.058, that between stance and the swing phase was 1.629 ± 0.173, and that between swing and the double support phase was 1.684 ± 0.357. All these ratios did not differ significantly from each other (, , repeated measure analysis of variance) or from (, resp.,t-tests). The repetitive gait phases of physiological walking were found in turn in repetitive proportions with each other, revealing an intrinsic harmonic structure. Harmony could be the key for facilitating the control of repetitive walking. Harmony is a powerful unifying factor between seemingly disparate fields of nature, including human gait.
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Moseley, Anne, Amanda Wales, Rob Herbert, Karl Schurr, and Sally Moore. "Observation and analysis of hemiplegic gait: stance phase." Australian Journal of Physiotherapy 39, no. 4 (1993): 259–67. http://dx.doi.org/10.1016/s0004-9514(14)60486-4.

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Peruzzi, A., A. Cereatti, and U. Della Croce. "Foot velocity profiles during stance phase in gait." Gait & Posture 33 (April 2011): S23—S24. http://dx.doi.org/10.1016/j.gaitpost.2010.10.030.

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Henderson, Adrienne D., A. Wayne Johnson, Sarah T. Ridge, Jonathan S. Egbert, Kevin P. Curtis, Levi J. Berry, and Dustin A. Bruening. "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 and analyze sagittal plane metrics and time series waveforms across stance phase. Results. Alterations included increased hip and knee flexion in early stance followed by a prolonged hip extension moment in midstance. Late stance ankle dorsiflexion and power absorption were increased, and final push-off was delayed and truncated. Conclusion. A neuropathic diabetic gait shares important similarities to a mild crouch gait with weakness/dysfunction in the foot and ankle. This study highlights two main compensation mechanisms that have been overlooked in previous literature. First, increased triceps surae stretch in terminal stance may be used to increase proprioception and/or energy storage, while a prolonged hip extension moment in midstance compensates for a limited push-off. These result in an overall workload shift from distal to proximal joints. Clinical assessment, monitoring, and treatment of neuropathy may benefit by focusing on these specific functional alterations.
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Eizentals, Peteris, Aleksejs Katashev, and Aleksandrs Okss. "GAIT PARTITIONING WITH SMART SOCKS SYSTEM." SOCIETY. INTEGRATION. EDUCATION. Proceedings of the International Scientific Conference 4 (May 21, 2019): 134. http://dx.doi.org/10.17770/sie2019vol4.3844.

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Gait is a very complex movement, involving the central nervous system and a significant part of the skeletomuscular system. Any disease that is affecting one or more of the involved parts will reflect in the gait. Therefore, gait analysis has been studied extensively in the context of early disease diagnostics, post-operation rehabilitation monitoring, and sports injury prevention. Gait cycle phase partitioning is one of the most common gait characteristic analysis methods, which utilizes the cyclical nature of human gait. Pressure sensitive mats and insoles are considered the gold standard, but some inherent limitations of these methods urge researchers to seek for alternatives. One of the proposed alternatives is Smart Sock systems, which contain textile pressure sensors. The main limitation of Smart Sock systems is the limited number of sensors, thus complicating gait phase partitioning by these systems. The present paper describes gait phase partitioning using plantar pressure signal obtained by a Smart Sock system. Six-phase partitioning was achieved, including such gait phases as initial contact, loading response, mid stance, terminal stance, pre-swing and swing phase. Mean gait cycle time values obtained from the experimental data were in accordance with the ones found in the literature.
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Duerinck, Saartje, Friso Hagman, Ilse Jonkers, Peter Vaes, and Peter Van Roy. "Forefoot deformation during the stance phase of normal gait." Journal of Foot and Ankle Research 5, Suppl 1 (2012): P12. http://dx.doi.org/10.1186/1757-1146-5-s1-p12.

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Stamm, Stacy E., and Loren Z. F. Chiu. "Calcaneal Plantar Flexion During the Stance Phase of Gait." Journal of Applied Biomechanics 32, no. 2 (April 2016): 205–9. http://dx.doi.org/10.1123/jab.2015-0044.

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When the rear- and forefoot are constrained, calcaneal plantar flexion may occur, deforming the longitudinal arch. Previous research has reported calcaneal motion relative to the tibia or forefoot; these joint rotations may not accurately describe rotation of the calcaneus alone. This investigation: (1) characterized the calcaneus and leg segment and ankle joint rotations during stance in gait, and (2) described the range of calcaneal plantar flexion in different structural arch types. Men (n = 14) and women (n = 16) performed gait in a motion analysis laboratory. From heel strike to heel off, the leg rotated forward while the calcaneus plantar flexed. Before foot flat, calcaneal plantar flexion was greater than forward leg rotation, resulting in ankle plantar flexion. After foot flat, forward leg rotation was greater than calcaneal plantar flexion, resulting in ankle dorsiflexion. Structural arch type was classified using the longitudinal arch angle. The range of calcaneal plantar flexion from foot flat to heel off was small in low (−2° to −8°), moderate in high (−3° to −12°), and large in normal (−2° to −20°) structural arches. Calcaneal plantar flexion in gait during midstance may reflect functional arch characteristics, which vary depending on structural arch type.
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Andrysek, Jan, Susan Klejman, and John Kooy. "Examination of Knee Joint Moments on the Function of Knee-Ankle-Foot Orthoses During Walking." Journal of Applied Biomechanics 29, no. 4 (August 2013): 474–80. http://dx.doi.org/10.1123/jab.29.4.474.

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The goal of this study was to investigate clinically relevant biomechanical conditions relating to the setup and alignment of knee-ankle-foot orthoses and the influence of these conditions on knee extension moments and orthotic stance control during gait. Knee moments were collected using an instrumented gait laboratory and concurrently a load transducer embedded at the knee-ankle-foot orthosis knee joint of four individuals with poliomyelitis. We found that knee extension moments were not typically produced in late stance-phase of gait. Adding a dorsiflexion stop at the orthotic ankle significantly decreased the knee flexion moments in late stance-phase, while slightly flexing the knee in stance-phase had a variable effect. The findings suggest that where users of orthoses have problems initiating swing-phase flexion with stance control orthoses, an ankle dorsiflexion stop may be used to enhance function. Furthermore, the use of stance control knee joints that lock while under flexion may contribute to more inconsistent unlocking of the stance control orthosis during gait.
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Dissertations / Theses on the topic "Stance phase of gait"

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Aoki(Sakuma), Kaoru. "Immediate effects of stance and swing phase training on gait in patients with stroke." Doctoral thesis, Kyoto University, 2021. http://hdl.handle.net/2433/265169.

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京都大学
新制・論文博士
博士(人間健康科学)
乙第13430号
論人健博第8号
新制||人健||6(附属図書館)
京都大学大学院医学研究科人間健康科学系専攻
(主査)教授 黒木 裕士, 教授 青山 朋樹, 教授 松田 秀一
学位規則第4条第2項該当
Doctor of Human Health Sciences
Kyoto University
DFAM
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Wangerin, Spencer D. "Development and validation of a human knee joint finite element model for tissue stress and strain predictions during exercise." DigitalCommons@CalPoly, 2013. https://digitalcommons.calpoly.edu/theses/1129.

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Osteoarthritis (OA) is a degenerative condition of cartilage and is the leading cost of disability in the United States. Motion analysis experiments in combination with knee-joint finite element (FE) analysis may be used to identify exercises that maintain knee-joint osteochondral (OC) loading at safe levels for patients at high-risk for knee OA, individuals with modest OC defects, or patients rehabilitating after surgical interventions. Therefore, a detailed total knee-joint FE model was developed by modifying open-source knee-joint geometries in order to predict OC tissue stress and strain during the stance phase of gait. The model was partially validated for predicting the timing and locations of maximum contact parameters (contact pressure, contact area, and principal Green-Lagrangian strain), but over-estimated contact parameters compared with both published in vivo studies and other FE analyses of the stance phase of gait. This suggests that the model geometry and kinematic boundary conditions utilized in this FE model are appropriate, but limitations in the material properties used, as well as potentially the loading boundary conditions represent primary areas for improvement.
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Dalton, Elan. "Influence of initial stance configuration on gait initiation." [Gainesville, Fla.] : University of Florida, 2009. http://purl.fcla.edu/fcla/etd/UFE0041274.

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Wühr, Max. "Sensorimotor postural control in healthy and pathological stance and gait." Diss., Ludwig-Maximilians-Universität München, 2014. http://nbn-resolving.de/urn:nbn:de:bvb:19-178182.

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Postural control during standing and walking is an inherently unstable task requiring the interaction of various biomechanical, sensory, and neurophysiological mechanisms to shape stable patterns of whole-body coordination that are able to counteract postural disequilibrium. This thesis focused on the examination of central aspects of the functional roles of these mechanisms and the modes of interaction between them. A further aim was to determine the conditions of dynamic stability for healthy standing and walking performance as well as for certain balance and gait disorders. By studying movement fluctuations in the walking pattern it could be demonstrated that dynamic stability during walking depends on gait speed and is differentially regulated for the medio-lateral and the fore-aft walking planes. Stability control in the fore-aft walking plane exhibits attractor dynamics typical for a dynamical system. Accordingly, the most stable pattern of movement coordination in terms of minimal fluctuations in the order parameter (i.e., the relative phase between the two oscillating legs) can be observed at the attractor of self-paced walking. Critical fluctuations occur at increasingly non-preferred speeds, indicating a loss of dynamic gait stability close to the speed boundaries of the walking mode. Moreover, stability control during slow walking is critically dependent on sensory feedback control, whereas dynamic stability during fast walking relies mainly on the smooth operation of cerebellar pacemaker regions. Disturbances of sensory and cerebellar locomotor control in certain gait disorders could be further linked to a loss of dynamic gait stability, in particular an increased risk of falls. Furthermore, this thesis examined alterations in the sensorimotor postural control scheme that may trigger the experience of subjective imbalance and vertigo in the conditions of phobic postural vertigo and visual height intolerance. Both conditions are characterized by an inadequate mode of balance regulation featuring increased levels of open-loop balance control and a precipitate integration of closed-loop sensory feedback into the postural control scheme. This inadequate balance control strategy is accompanied by a stiffening of the anti-gravity musculature and is elicited by specific influences of attention and sensory feedback control. The findings of this thesis contribute to the understanding of central sensorimotor mechanisms involved in the control of dynamic postural stability during standing and walking. They further provide relevant information for the differential diagnosis and fall risk estimation of certain balance and gait disorders.
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Massenzo, Trisha J. "An Investigation of Kinetic Visual Biofeedback on Dynamic Stance Symmetry." VCU Scholars Compass, 2016. http://scholarscompass.vcu.edu/etd/4661.

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The intent of the following research is to utilize task-specific, constraint-induced therapies and apply towards dynamic training for symmetrical balance. Modifications to an elliptical trainer were made to both measure weight distributions during dynamic stance as well as provide kinetic biofeedback through a man-machine interface. Following a review of the background, which includes research from several decades that are seminal to current studies, a design review is discussed to cover the design of the modified elliptical (Chapter 2). An initial study was conducted in a healthy sample population in order to determine the best visual biofeedback representation by comparing different man-machine interfaces (Chapter 3). Index of gait symmetry measures indicated that one display interface optimized participant performance during activity with the modified elliptical trainer. A second study was designed to determine the effects of manipulating the gain of the signal to encourage increased distribution towards the non-dominant weight bearing limb. The purpose of the second study was to better understand the threshold value of gain manipulation in a healthy sample set. Results analyzing percentage error as a measure of performance show that a range between 5-10% allows for a suitable threshold value to be applied for participants who have suffered a stroke. A final study was conducted to apply results/knowledge from the previous two studies to a stroke cohort to determine short-term carryover following training with the modified elliptical trainer. Data taken from force measurements on the elliptical trainer suggest that there was carryover with decreased error from pre to post training. For one participant GaitRite® data show a significant difference from pre to post measurements in single limb support. The results of the research suggest that visual biofeedback can improve symmetrical performance during dynamic patterns. For a better understanding of visual biofeedback delivery, one display representation proved to be beneficial compared to the others which resulted in improved performance. Results show that healthy human participants can minimize error with visual biofeedback and continue minimizing error until a threshold value of 10%. Finally, results have shown promise towards applying such a system for kinetic gait rehabilitation.
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Sparrow, Leah M., Emily Pellatt, Sabrina S. Yu, David A. Raichlen, Herman Pontzer, and Campbell Rolian. "Gait changes in a line of mice artificially selected for longer limbs." PEERJ INC, 2017. http://hdl.handle.net/10150/623229.

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In legged terrestrial locomotion, the duration of stance phase, i.e., when limbs are in contact with the substrate, is positively correlated with limb length, and negatively correlated with the metabolic cost of transport. These relationships are well documented at the interspecific level, across a broad range of body sizes and travel speeds. However, such relationships are harder to evaluate within species (i.e., where natural selection operates), largely for practical reasons, including low population variance in limb length, and the presence of confounding factors such as body mass, or training. Here, we compared spatiotemporal kinematics of gait in Longshanks, a long-legged mouse line created through artificial selection, and in random-bred, mass-matched Control mice raised under identical conditions. We used a gait treadmill to test the hypothesis that Longshanks have longer stance phases and stride lengths, and decreased stride frequencies in both fore- and hind limbs, compared with Controls. Our results indicate that gait differs significantly between the two groups. Specifically, and as hypothesized, stance duration and stride length are 8–10% greater in Longshanks, while stride frequency is 8% lower than in Controls. However, there was no difference in the touch-down timing and sequence of the paws between the two lines. Taken together, these data suggest that, for a given speed, Longshanks mice take significantly fewer, longer steps to cover the same distance or running time compared to Controls, with important implications for other measures of variation among individuals in whole-organism performance, such as the metabolic cost of transport.
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Wühr, Max [Verfasser], and Hans [Akademischer Betreuer] Straka. "Sensorimotor postural control in healthy and pathological stance and gait / Max Wühr. Betreuer: Hans Straka." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2014. http://d-nb.info/1066206457/34.

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Liu, Zongyi. "Gait-Based Recognition at a Distance: Performance, Covariate Impact and Solutions." Scholar Commons, 2004. https://scholarcommons.usf.edu/etd/1134.

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It has been noticed for a long time that humans can identify others based on their biological movement from a distance. However, it is only recently that computer vision based gait biometrics has received much attention. In this dissertation, we perform a thorough study of gait recognition from a computer vision perspective. We first present a parameterless baseline recognition algorithm, which bases similarity on spatio-temporal correlation that emphasizes gait dynamics as well as gait shapes. Our experiments are performed with three popular gait databases: the USF/NIST HumanID Gait Challenge outdoor database with 122 subjects, the UMD outdoor database with 55 subjects, and the CMU Mobo indoor database with 25 subjects. Despite its simplicity, the baseline algorithm shows strong recognition power. On the other hand, the outcome suggests that changes in surface and time have strong impact on recognition with significant drop in performance. To gain insight into the effects of image segmentation on recognition -- a possible cause for performance degradation, we propose a silhouette reconstruction method based on a Population Hidden Markov Model (pHMM), which models gait over one cycle, coupled with an Eigen-stance model utilizing the Principle Component Analysis (PCA) of the silhouette shapes. Both models are built from a set of manually created silhouettes of 71 subjects. Given a sequence of machine segmented silhouettes, each frame is matched into a stance by pHMM using the Viterbi algorithm, and then is projected into and reconstructed by the Eigen-stance model. We demonstrate that the system dramatically improves the silhouette quality. Nonetheless, it does little help for recognition, indicating that segmentation is not the key factor of the covariate impacts. To improve performance, we look into other aspects. Toward this end, we propose three recognition algorithms: (i) an averaged silhouette based algorithm that deemphasizes gait dynamics, which substantially reduces computation time but achieves similar recognition power with the baseline algorithm; (ii) an algorithm that normalizes gait dynamics using pHMM and then uses Euclidean distance between corresponding selected stances -- this improves recognition over surface and time; and (iii) an algorithm that also performs gait dynamics normalization using pHMM, but instead of Euclidean distances, we consider distances in shape space based on the Linear Discriminant Analysis (LDA) and consider measures that are invariant to morphological deformation of silhouettes. This algorithm statistically improves the recognition over all covariates. Compared with the best reported algorithm to date, it improves the top-rank identification rate (gallery size: 122 subjects) for comparison across hard covariates: briefcase, surface type and time, by 22%, 14%, and 12% respectively. In addition to better gait algorithms, we also study multi-biometrics combination to improve outdoor biometric performance, specifically, fusing with face data. We choose outdoor face recognition, a "known" hard problem in face biometrics, and test four combination schemes: score sum, Bayesian rule, confidence score sum, and rank sum. We find that the recognition power after combination is significantly stronger although individual biometrics are weak, suggesting another effective approach to improve biometric recognition. The fundamental contributions of this work include (i) establishing the "hard" problems for gait recognition involving comparison across time, surface, and briefcase carrying conditions, (ii) revealing that their impacts cannot be explained by silhouette segmentation, (iii) demonstrating that gait shape is more important than gait dynamics in recognition, and (iv) proposing a novel gait algorithm that outperforms other gait algorithms to date.
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Thota, Anil Kumar. "NEUROMECHANICAL CONTROL OF LOCOMOTION IN INTACT AND INCOMPLETE SPINAL CORD INJURED RATS." UKnowledge, 2004. http://uknowledge.uky.edu/gradschool_theses/195.

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Rodent models are being extensively used to investigate the effects of traumatic injuryand to develop and assess the mechanisms of repair and regeneration. We presentquantitative assessment of 2D kinematics of overground walking and for the first time3D joint angle kinematics of all four limbs during treadmill walking in the intact and inincomplete spinal cord contusion injured (iSCI) adult female Long Evans rats. Phaserelationship between joint angles on a cycle-by-cycle basis and interlimb footfalls areassessed using a simple technique. Electromyogram (EMG) data from major flexor andextensor muscles for each of the hindlimb joints and elbow extensor muscles of theforelimbs synchronized to the 3D kinematics is also obtained in intact rats. EMG activityindicates specific relationships of the neural activity to joint angle kinematics. We findthat the ankle flexors as well as the hip and elbow extensors maintain constant burstduration with changing cycle duration. Overground walking kinematics providesinformation on stance width (SW), stride length (SL) and hindfoot rotation (Rot). SW andRot increased in iSCI rats. Treadmill walking kinematics provides information on jointangle trajectories. In iSCI rats double burst pattern in ankle angle as seen in intact ratsis lost and knee extension and range are reduced. Intra and interlimb coordination isimpaired. Left-right interlimb coordination and forelimb kinematics are not alteredsignificantly. In iSCI rats, maximum flexion of the knee during swing occurs in phasewith the hip as opposed to knee flexion preceeding hip flexion in intact rats. A mildexercise regimen in intact rats over eight weeks does not alter the kinematics.
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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 "Stance phase of gait"

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A study of normal plantar pressure pattern of the foot during the support phase of walking. 1994.

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A study of normal plantar pressure pattern of the foot during the support phase of walking. 1994.

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A study of normal plantar pressure pattern of the foot during the support phase of walking. 1994.

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Nolte, David D. Introduction to Modern Dynamics. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198844624.001.0001.

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Introduction to Modern Dynamics: Chaos, Networks, Space and Time (2nd Edition) combines the topics of modern dynamics—chaos theory, dynamics on complex networks and the geometry of dynamical spaces—into a coherent framework. This text is divided into four parts: Geometric Mechanics, Nonlinear Dynamics, Complex Systems, and Relativity. These topics share a common and simple mathematical language that helps students gain a unified physical intuition. Geometric mechanics lays the foundation and sets the tone for the rest of the book by emphasizing dynamical spaces, like state space and phase space, whose geometric properties define the set of all trajectories through those spaces. The section on nonlinear dynamics has chapters on chaos theory, synchronization, and networks. Chaos theory provides the language and tools to understand nonlinear systems, introducing fixed points that are classified through stability analysis and nullclines that shepherd system trajectories. Synchronization and networks are central paradigms in this book because they demonstrate how collective behavior emerges from the interactions of many individual nonlinear elements. The section on complex systems contains chapters on neural dynamics, evolutionary dynamics, and economic dynamics. The final section contains chapters on metric spaces and the special and general theories of relativity. In the second edition, sections on conventional topics, like applications of Lagrangians, have been strengthened, as well as being updated to provide a modern perspective. Several of the introductory chapters have been rearranged for improved logical flow and there are expanded homework problems at the end of each chapter.
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Zucker, Nancy, Courtney Arena, Cortney Dable, Jasmine Hill, Caroline Hubble, Emilie Sohl, and Jee Yoon. Selective Eating. Edited by W. Stewart Agras and Athena Robinson. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190620998.013.23.

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Selective eating (also referred to as picky or fussy eating) has been described as a normative developmental phase that a significant minority experience and, potentially, “grow out of” without formal intervention. This chapter reviews the literature on selective eating from the stance that this eating pattern is a clinical condition rather than a normative developmental phase. Construing selective eating as a clinical condition, it probes questions of definition, chronicity, and impairment that would warrant intervention. It explores the phenomenology of selective eating, suggesting that the experience of disgust has been relatively neglected in understanding the experience of selective eaters and that the inclusion of this feature may offer some novel hypotheses for both necessary treatment elements and novel conceptualizations about what it means to “outgrow” selective eating. Finally, assuming the hypotheses proposed are accepted, it suggests some necessary treatment elements to expand food variety in individuals with selective eating.
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Rosman, Moshe. How Jewish is Jewish History? Liverpool University Press, 2007. http://dx.doi.org/10.3828/liverpool/9781904113348.001.0001.

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This book treats the key questions that postmodernism raises for the writing of Jewish history. What is the relationship between Jewish culture and history and those of the non-Jews among whom Jews live? Can we — in the light of postmodernist thought — speak of a continuous, coherent Jewish People, with a distinct culture and history? What in fact is Jewish cultural history, and how can it be written? How does gender transform the Jewish historical narrative? How does Jewish history fit into the multicultural paradigm? Has Jewish history entered a postmodern phase? How can Jewish history utilize the methodologies of other disciplines to accomplish its task? All these are questions that Jewish historians need to think about. While engaging with the questions raised by postmodernists, the book adopts a critical stance towards their work. The book's basic claim is that it is possible to incorporate, judiciously, postmodern innovations into historical scholarship that is still based on documentary research and critical analysis. The resulting endeavour might be termed ‘a reformed positivism’. The book presents an argument as to what considerations must be brought to bear on the writing of Jewish history today. By highlighting the issues raised by postmodernism, the book provides those in the field with a foundation from which to discuss how it should be practiced in light of this generation's challenges.
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Book chapters on the topic "Stance phase of gait"

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Łysoń-Uklańska, Barbara, Joanna Ścibek, Katarzyna Bienias, and Andrzej Wit. "Analysis of Ground Reaction Forces and Kinematic Response to Gait Perturbation During Mid- to Terminal Stance Phase of the Gait Cycle." In Innovations in Biomedical Engineering, 165–73. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-52180-6_19.

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Sijobert, B., C. Fattal, J. Pontier, and C. Azevedo Coste. "FES-Based Control of Knee Joint to Reduce Stance Phase Asymmetry in Post-stroke Gait: Feasibility Study." In Converging Clinical and Engineering Research on Neurorehabilitation III, 926–30. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01845-0_186.

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Maqbool, Hafiz F., Muhammad A. B. Husman, Mohammed I. Awad, Alireza Abouhossein, Nadeem Iqbal, and Abbas A. Dehghani-Sanij. "Stance Sub-phases Gait Event Detection in Real-Time for Ramp Ascent and Descent." In Converging Clinical and Engineering Research on Neurorehabilitation II, 191–96. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46669-9_34.

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Maqbool, Hafiz F., Muhammad A. B. Husman, Mohammed I. Awad, Alireza Abouhossein, Nadeem Iqbal, and Abbas A. Dehghani-Sanij. "Erratum to: Stance Sub-phases Gait Event Detection in Real-Time for Ramp Ascent and Descent." In Converging Clinical and Engineering Research on Neurorehabilitation II, E1. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-46669-9_247.

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Berthonnaud, E., B. Moyen, and J. Dimnet. "Correlated Kinematic and Dynamic Studies of the Knee Joint During the Stance Phase of Gait: Biomechanical Disturbances Introduced by a Knee Pathology." In Biomechanics and Biomaterials in Orthopedics, 570–84. London: Springer London, 2004. http://dx.doi.org/10.1007/978-1-4471-3774-0_50.

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Clarac, F., and A. Chrachri. "The Stance Phase and its Control by Sensory Information During Walking in Crustacea." In Stance and Motion, 93–106. Boston, MA: Springer US, 1988. http://dx.doi.org/10.1007/978-1-4899-0821-6_9.

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Suri, Vinit. "Cerebellar Examination and Examination of Posture, Stance, and Gait." In Clinical Neurological Examination and Localization, 111–17. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1228-2_9.

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Connor, Justin, and Mutlu Cobanoglu. "Stance Phase Problems in Cerebral Palsy (Strength)." In Handbook of Human Motion, 1–11. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30808-1_54-1.

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Camacho-Bello, C., and J. J. Báez-Rojas. "Krawtchouk Moments for Gait Phase Detection." In Advanced Information Systems Engineering, 787–93. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-319-12568-8_95.

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Park, S. W., R. H. Sohn, S. H. Hwang, and Y. H. Kim. "Comparison of sensor systems for gait phase detection in hemiplegic gait." In IFMBE Proceedings, 358–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03889-1_96.

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Conference papers on the topic "Stance phase of gait"

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Dasgupta, Hirak. "An algorithm for stance and swing phase detection of human gait cycle." In 2015 2nd International Conference on Electronics and Communication Systems (ICECS). IEEE, 2015. http://dx.doi.org/10.1109/ecs.2015.7124944.

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Shao, Qi, Kurt Manal, and Thomas S. Buchanan. "An EMG-Driven Forward Dynamics Model to Simulate Stance Phase of Gait." In ASME 2009 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2009. http://dx.doi.org/10.1115/sbc2009-206715.

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Simulations based on forward dynamics have been used to identify the biomechanical mechanisms how human movement is generated. They used either net joint torques [1] or muscle forces [2, 3, 4] as actuators to drive forward simulation. However, very few models used EMG-based patterns to define muscle excitations [4] or were actually driven by EMGs. Muscle activation patterns vary from subject to subject and from movement to movement, and the activations depend on the control task, sometimes quite different even for the same joint angle and joint torque [5]. Using EMG as input can account for subjects’ different muscle activation patterns and help revealing the neuromuscular control strategies.
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Tsunetomo, Kaito, Shouhei Shirafuji, and Jun Ota. "Analysis of Rockers during the Stance Phase of Gait for Feature Extraction." In 2018 International Symposium on Micro-NanoMechatronics and Human Science (MHS). IEEE, 2018. http://dx.doi.org/10.1109/mhs.2018.8887058.

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Cho, Hyeon-Seok, Gyoo-Suk Kim, Sung-Jae Kang, Jei-Chung Ryu, and Mu-Sung Mun. "Dynamic Characteristics of Stance Phase Gait with Prosthetic Foot for Trans-Tibial Amputee." In Applied Simulation and Modelling. Calgary,AB,Canada: ACTAPRESS, 2011. http://dx.doi.org/10.2316/p.2011.715-078.

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Shamaei, K., and A. M. Dollar. "On the mechanics of the knee during the stance phase of the gait." In 2011 IEEE 12th International Conference on Rehabilitation Robotics: Reaching Users & the Community (ICORR 2011). IEEE, 2011. http://dx.doi.org/10.1109/icorr.2011.5975478.

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Shamaei, K., M. Cenciarini, and A. M. Dollar. "On the mechanics of the ankle in the stance phase of the gait." In 2011 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2011. http://dx.doi.org/10.1109/iembs.2011.6092007.

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Chen, Chih-Hui, Jing-Sheng Li, Ali Hosseini, Hemanth Reddy Gadikota, Michal Kozanek, Thomas J. Gill, and Guoan Li. "Tibiofemoral Kinematics of the Knee During the Stance Phase of Gait After ACL Deficiency." In ASME 2011 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2011. http://dx.doi.org/10.1115/sbc2011-53904.

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Numerous studies have demonstrated that ACL deficiency could lead to further meniscus tear and cartilage degeneration. The post-injury joint degeneration has been mainly attributed to altered joint kinematics caused by ACL deficiency. Therefore, understanding of the effect of ACL injuries on knee joint motion is critical for development of conservative treatment or surgical reconstruction of the ACL injured knees. However, few data have been reported on the influence of ACL deficiency on knee joint motion during gait [1,2] — the most commonly performed daily activities. The objective of this study was to determine the 6DOF kinematics of the knee after ACL injuries during gait on a treadmill and to compare the kinematics data to those measured from the intact contralateral side using a combined dual fluoroscopic imaging system (DFIS) and MR image technique [3,4]. We hypothesized that the 6DOF tibiofemoral kinematics of ACL-deficient knees would be altered even under low demand activities such as walking.
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Manurung, Auralius, and Jungwon Yoon. "Fuzzy clustering of temporal parameters of gait during stance phase for walking speed estimation." In 2010 International Conference on Control, Automation and Systems (ICCAS 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccas.2010.5669795.

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Yang, Nicholas, Hamid Nayeb-Hashemi, and Paul Canavan. "The Effect of the Frontal Plane Tibiofemoral Angle on the Stress and Strain at the Knee Cartilage During the Stance Phase of the Gait Cycle." In ASME 2009 International Mechanical Engineering Congress and Exposition. ASMEDC, 2009. http://dx.doi.org/10.1115/imece2009-13220.

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Three-dimensional (3-D) finite element analysis (FEA) knee models were created to determine the effect of the frontal plane tibiofemoral angle on the stress and strain at the knee cartilage during the stance phase of the gait cycle. Knee models of three healthy subjects of different tibiofemoral angles and weight were created from sagittal view magnetic resonance images (MRI) of the knee. The loading conditions were determined from motion analysis and force platform data and a muscle force reduction model. During the stance phase, the subjects exhibited a valgus-varus-valgus knee moment pattern that determined the location and magnitude of the maximum stress and strain in the cartilage on the lateral or medial compartment of the knee. The highest values of the normal stress, Tresca shear stress and normal strain for each subject occurred at 25% of the stance phase of the gait cycle, where the maximum compressive load and varus knee moment occurred. The individual with the varus aligned knee had the largest stress and strain at the medial compartment of the knee compared to the normal aligned and valgus aligned individuals due to the larger varus knee moment exhibited during the stance phase of the gait cycle in the varus aligned individual. The results from the FEA data may be used by health care professional to identify individuals most susceptible to knee osteoarthritis (OA) and assist in developing preventive measure to slow and possibly stop the initiation and progression of OA.
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Lerner, Amy L., David L. Gushue, and Emily A. Gedbaw. "Mechanical Stress Patterns in the Human Proximal Tibial Growth Plate During the Stance Phase of Normal Gait." In ASME 2002 International Mechanical Engineering Congress and Exposition. ASMEDC, 2002. http://dx.doi.org/10.1115/imece2002-32609.

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Since the mid 1800’s clinicians and researchers have considered the effect of mechanical stresses on bone growth and the development of growth disorders [1]. However, the specifics of this relationship remain poorly understood. Both clinical and experimental evidence support the concept that magnitude, frequency and duration of loads are critical in defining the response of cartilage to pressures [2, 3]. Yet, the range of physiologic pressures in the growth plate has not been identified, and most models of growing bones have considered single quasi-static loading conditions and/or elastic material models that can not accurately represent time dependence [4, 5]. It was the goal of this study to implement loading conditions representing an entire stance phase of gait in a two-dimensional model of the proximal tibia of a normal child. A poroelastic material model was used in order to identify the variations in growth plate pressures in both time and location, and investigate the potential for fluid flow within the growth plate.
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