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
Formation Control of Multi‐Agent System with Local Interaction and Artificial Potential Field
This article proposes a local interaction‐based formation control method for Multi‐Agent system, integrating consensus and leader‐follower strategies with a stress response mechanism—artificial potential field to reduce communication overhead and enable obstacle avoidance. Experimental results on triangular, square, and hexagonal formations confirm its
Luoyin Zhao+3 more
wiley +1 more source
Ligand discovery and virtual screening using the program LIDAEUS [PDF]
Paul Taylor+7 more
openalex +1 more source
Multi‐Material Additive Manufacturing of Soft Robotic Systems: A Comprehensive Review
This review explores the transformative role of multi‐material additive manufacturing (MMAM) in the development of soft robotic systems. It presents current techniques, materials, and design strategies that enable functionally graded and adaptive structures.
Ritik Raj+2 more
wiley +1 more source
Protein crystallization: virtual screening and optimization
Lawrence J. DeLucas+11 more
openalex +1 more source
Discovery of inhibitors of the pentein superfamily protein dimethylarginine dimethylaminohydrolase (DDAH), by virtual screening and hit analysis [PDF]
Basil Hartzoulakis+10 more
openalex +1 more source
This study introduces a textile‐based capacitive pressure sensor featuring a triangular prism microstructure, which significantly enhances sensitivity to 5.52% kPa−¹ and supports a wide sensing range up to 330 kPa. The sensor's performance is validated in a 4‐channel capacitive pressure‐based force myography (cFMG) armband for gesture recognition ...
Rayane Tchantchane+3 more
wiley +1 more source
In Silico Prediction of SARS Protease Inhibitors by Virtual High Throughput Screening [PDF]
Dariusz Plewczyński+4 more
openalex +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
Targeting Plague Virulence Factors: A Combined Machine Learning Method and Multiple Conformational Virtual Screening for the Discovery of Yersinia Protein Kinase A Inhibitors [PDF]
Xin Hu, Gerd Prehna, C. Erec Stebbins
openalex +1 more source