Results 181 to 190 of about 23,187 (263)

Are the Forces and Lower Limb Kinematics Displayed During Running Associated with Medial Tibial Stress Syndrome? A Case-Control and Case Study. [PDF]

J Funct Morphol Kinesiol
Mattock JPM, Steele JR, Mickle KJ.
europepmc   +1 more source

Video‐based diagnostics supported by artificial intelligence as an opportunity to address the epilepsy diagnostic gap: A narrative review

Epilepsia, EarlyView.
Abstract Despite advancements in epilepsy care, a substantial diagnostic gap persists, particularly in resource‐limited settings. This narrative review explores the potential of video‐based diagnostics augmented by artificial intelligence (AI) to address this gap by enabling earlier and more accessible seizure detection and classification.
Gadi Miron, Robert Terziev, Maximilian Schöls, John McLaren, Tobias Loddenkemper, Jörg Wellmer, Sigrid Mues, Christian Meisel   +7 more
wiley   +1 more source

Editorial: Assessment of biomechanical mechanism in the context of sports injury prevention or rehabilitation. [PDF]

Front Bioeng Biotechnol
Innocenti B.
europepmc   +1 more source

Artificial intelligence in preclinical epilepsy research: Current state, potential, and challenges

Epilepsia Open, EarlyView.
Abstract Preclinical translational epilepsy research uses animal models to better understand the mechanisms underlying epilepsy and its comorbidities, as well as to analyze and develop potential treatments that may mitigate this neurological disorder and its associated conditions. Artificial intelligence (AI) has emerged as a transformative tool across
Jesús Servando Medel‐Matus, Cesar Santana‐Gomez, Ruby G. Escalante, Dominique Duncan, Pedro F. Viana, Giulia Sofia Cereda, Naoto Kuroda, Aristea S. Galanopoulou   +7 more
wiley   +1 more source

Prediction of Center-of-Mass Kinematics of Sensopro Exercises with Neural Network Models. [PDF]

Sensors (Basel)
Hegi H, Single M, Nef T, Kredel R.
europepmc   +1 more source

Learning Rocking Dynamics From Sparse Shake‐Table Data With Interpretable Physics‐Informed Neural Networks

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT We present a hybrid interpretable Physics‐Informed Neural Network Long‐Short Term Memory (Hybrid PINN LSTM) framework for predicting the seismic response of rocking blocks. Existing analytical models rely on uncertain idealizations, while purely data‐driven and machine‐learning approaches lack physical consistency and interpretability.
Shirley Shen, Christian Málaga‐Chuquitaype   +1 more
wiley   +1 more source

Variable admittance control algorithm for robots based on task-space boundary constraints. [PDF]

Sci Rep
Yun N, Zhou Z, Wan J, Wang K, Zhang X.
europepmc   +1 more source

Rocking and Rolling of Rigid Polygons Under Seismic Excitation

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT We present an event driven analytical framework for rigid cyclic polygons subjected to horizontal ground excitation in which uplift, impact, and successive pivot switching are treated within a unified non‐smooth dynamical description. Rolling is defined as a sequence of energetically admissible transitions between neighbouring vertices tied to
Atif Rasheed, Christian Málaga‐Chuquitaype   +1 more
wiley   +1 more source

Multiple Scales of Coordination along the Body Axis during <i>Drosophila</i> Larval Locomotion. [PDF]

J Neurosci
Greaney MR, Heckscher ES, Kaufman MT.
europepmc   +1 more source