Human Gait Cycle Analysis Using an Adapted Mechanical Prosthesis

Moraes, C. R. L.; Aragão, E. M.; Lucena, R. J. R. S.; Cavalcanti, É. L.; Rodrigues, Marco A. B.

doi:10.1007/978-981-13-2119-1_38

Cited by 2 publications

(2 citation statements)

References 3 publications

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“…The entire movement process will only produce plantar pressure during the incomplete support stages. The main part of the full leg support stage is the forward force balance (Moraes et al, 2019). When the three supporting points form a triangle and the barycenter falls within the triangle, the stable state achieves at this time.…”

Section: Stability Analysismentioning

confidence: 99%

A Real-Time Stability Control Method Through sEMG Interface for Lower Extremity Rehabilitation Exoskeletons

et al. 2021

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Herein, we propose a real-time stable control gait switching method for the exoskeleton rehabilitation robot. Exoskeleton rehabilitation robots have been extensively developed during the past decade and are able to offer valuable motor ability to paraplegics. However, achieving stable states of the human-exoskeleton system while conserving wearer strength remains challenging. The constant switching of gaits during walking may affect the center of gravity, resulting in imbalance of human–exoskeleton system. In this study, it was determined that forming an equilateral triangle with two crutch-supporting points and a supporting leg has a positive impact on walking stability and ergonomic interaction. First, the gaits planning and stability analysis based on human kinematics model and zero moment point method for the lower limb exoskeleton are demonstrated. Second, a neural interface based on surface electromyography (sEMG), which realizes the intention recognition and muscle fatigue estimation, is constructed. Third, the stability of human–exoskeleton system and ergonomic effects are tested through different gaits with planned and unplanned gait switching strategy on the SIAT lower limb rehabilitation exoskeleton. The intention recognition based on long short-term memory (LSTM) model can achieve an accuracy of nearly 99%. The experimental results verified the feasibility and efficiency of the proposed gait switching method for enhancing stability and ergonomic effects of lower limb rehabilitation exoskeleton.

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Section: Stability Analysismentioning

confidence: 99%

A Real-Time Stability Control Method Through sEMG Interface for Lower Extremity Rehabilitation Exoskeletons

et al. 2021

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“…These methods make use of Temporal/Spatial features or Pressure measurements. In this paper gait cycle is analyzed with respect to the first method (temporal) along with its gait patterns [15], [16], [17]. This method is, by far, the most common and scientifically validated by neurologists and for which there are well-defined protocols (e.g.…”

Section: Neurodegenerative Diseases Motor Patternsmentioning

confidence: 99%

Gait Analysis for Early Neurodegenerative Diseases Classification Through the Kinematic Theory of Rapid Human Movements

2020

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Neurodegenerative diseases are particular diseases whose decline can partially or completely compromise the normal course of life of a human being. In order to increase the quality of patient's life, a timely diagnosis plays a major role. The analysis of neurodegenerative diseases, and their stage, is also carried out by means of gait analysis. Performing early stage neurodegenerative disease assessment is still an open problem. In this paper, the focus is on modeling the human gait movement pattern by using the kinematic theory of rapid human movements and its sigma-lognormal model. The hypothesis is that the kinematic theory of rapid human movements, originally developed to describe handwriting patterns, and used in conjunction with other spatio-temporal features, can discriminate neurodegenerative diseases patterns, especially in early stages, while analyzing human gait with 2D cameras. The thesis empirically demonstrates its effectiveness in describing neurodegenerative patterns, when used in conjunction with state-of-the-art pose estimation and feature extraction techniques. The solution developed achieved 99.1% of accuracy using velocity-based, angle-based and sigma-lognormal features and left walk orientation. INDEX TERMS pose-estimation, computer vision, computer aided diagnosis, gait analysis, machine learning, early neurodegenerative diseases assessment, kinematic theory of rapid human movements, sigma-lognormal

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Human Gait Cycle Analysis Using an Adapted Mechanical Prosthesis

Cited by 2 publications

References 3 publications

A Real-Time Stability Control Method Through sEMG Interface for Lower Extremity Rehabilitation Exoskeletons

A Real-Time Stability Control Method Through sEMG Interface for Lower Extremity Rehabilitation Exoskeletons

Gait Analysis for Early Neurodegenerative Diseases Classification Through the Kinematic Theory of Rapid Human Movements

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