Conventional and non conventional body motions modelling and control. Application to the handwriting process

DOI10.1002/asjc.2127zbMath1431.92009OpenAlexW2945381634MaRDI QIDQ5213822

Afef Abdelkrim, Mohamed Benrejeb

Publication date: 6 February 2020

Published in: Asian Journal of Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/asjc.2127

zbMATH Keywords

controlfuzzy logicartificial neural networksmotionelectromyographic signal (EMG)handwriting process

Mathematics Subject Classification ID

Biomedical imaging and signal processing (92C55) Neural networks for/in biological studies, artificial life and related topics (92B20) Biomechanics (92C10)

Cites Work

• Multi-model approach to characterize human handwriting motion
• A kinematic theory of rapid human movements. I: Movement representation and generation
• A kinematic theory of rapid human movements. II: Movement time and control
• Exponential Synchronization of Memristive Chaotic Recurrent Neural Networks Via Alternate Output Feedback Control
• A neural differential evolution identification approach to nonlinear systems and modelling of shape memory alloy actuator
• Constrained Nonlinear‐Based Optimisation Applied to Fuzzy PID Controllers Tuning
• Dynamical Movement Primitives: Learning Attractor Models for Motor Behaviors
• Membership Function Dependent Observer‐Based Controller Design for A T‐S Fuzzy System

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