Results 251 to 260 of about 5,885,991 (322)
Flexible Sensor‐Based Human–Machine Interfaces with AI Integration for Medical Robotics
This review explores how flexible sensing technology and artificial intelligence (AI) significantly enhance human–machine interfaces in medical robotics. It highlights key sensing mechanisms, AI‐driven advancements, and applications in prosthetics, exoskeletons, and surgical robotics.
Yuxiao Wang+5 more
wiley +1 more source
Self-supervised learning analysis of multi-FISH labeled cell-type map in thick brain slices. [PDF]
Zheng W+7 more
europepmc +1 more source
This study introduces a hybrid robot that integrates mechanical assistance by musculoskeletons (i.e., soft pneumatic muscle with rigid exoskeletal extensions), neuromuscular electrical stimulation, and vibrotactile feedback in a lightweight wearable mechatronic complex applicable to the paretic ankle–foot poststroke for gait restoration. The system can
Fuqiang Ye+16 more
wiley +1 more source
Hard‐Magnetic Soft Millirobots in Underactuated Systems
This review provides a comprehensive overview of hard‐magnetic soft millirobots in underactuated systems. It examines key advances in structural design, physics‐informed modeling, and control strategies, while highlighting the interplay among these domains.
Qiong Wang+4 more
wiley +1 more source
Evaluating masked self-supervised learning frameworks for 3D dental model segmentation tasks. [PDF]
Krenmayr L+5 more
europepmc +1 more source
Rewiring Neuroimmunity: Nanoplatform Innovations for CNS Disease Therapy
This review explores emerging nanoplatform strategies designed to modulate neuroimmune responses for treating central nervous system (CNS) disorders. It examines structural and microenvironmental barriers, advances in multifunctional and targeted nanotechnologies, and highlights clinical progress and translational challenges, offering insights into the
Muhammad Usman Akbar+7 more
wiley +1 more source
Self-supervised learning framework for efficient classification of endoscopic images using pretext tasks. [PDF]
Nezhad SA+3 more
europepmc +1 more source
Machine Learning (ML) and optimization have permeated almost every aspect of engineering applications. Recent years have seen great traction toward ML‐based GaN HEMT modelling. However, ML‐based GaN HEMT models are mostly developed using variants of Artificial Neural Network (ANN).
Saddam Husain+2 more
wiley +1 more source