Results 81 to 90 of about 12,786,622 (281)

Muscle Control of an Extra Robotic Digit

Advanced Robotics Research, EarlyView.
This study compares muscle‐ and movement‐based control for operating a supernumerary robotic thumb. While movement control performs better in the proposed tasks, muscle‐based (EMG) control promotes broader motor learning. The results highlight the promise and challenges of using biosignals for human augmentation, offering new insights into intuitive ...
Julien Russ, Lucy Dowdall, Francesco Cenciarelli, Kitty Goodridge, Mabel Ziman, Hristo Dimitrov, Danielle Clode, Tamar R. Makin   +7 more
wiley   +1 more source

Merging expert and empirical data for rare event frequency estimation : pool homogenisation for empirical Bayes models [PDF]

, 2011
Empirical Bayes provides one approach to estimating the frequency of rare events as a weighted average of the frequencies of an event and a pool of events. The pool will draw upon, for example, events with similar precursors.
Hardman, Gavin, Bedford, Tim, Quigley, John, Walls, Lesley   +3 more
core   +3 more sources

Mutual Adaptation and Influence: Review of Latent Dynamics Models in Human–Robot Interaction

Advanced Robotics Research, EarlyView.
Robots are becoming better teammates by learning hidden patterns in how people act. This review covers how state‐of‐the‐art approaches leverage these patterns to help robots not only react but also anticipate and guide cooperation. Here, we synthesize a unifying framework for these approaches, classify and review existing works, and highlight key ...
Mason O. Smith, Sunny Amatya, Seyed Yousef Soltanian, Jonathan Bush, Wenlong Zhang   +4 more
wiley   +1 more source

Reverse-Bayes methods for evidence assessment and research synthesis. [PDF]

Res Synth Methods, 2022
Held L, Matthews R, Ott M, Pawel S.
europepmc   +1 more source

Intelligent Maintenance Review for Robots: Multimodal Information, Deep Diagnosis and Embodied Artificial Intelligence

Advanced Robotics Research, EarlyView.
This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao, Hongbo Wang, Naipeng Li, Shuo Wang, Yaguo Lei, Tonghai Wu, Junyi Cao   +6 more
wiley   +1 more source

pyComBat, a Python tool for batch effects correction in high-throughput molecular data using empirical Bayes methods. [PDF]

BMC Bioinformatics, 2023
Behdenna A, Colange M, Haziza J, Gema A, Appé G, Azencott CA, Nordor A.   +6 more
europepmc   +1 more source

Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges

Advanced Robotics Research, EarlyView.
This review analyzes learning‐based soft robotic grasping from a pipeline‐oriented perspective, encompassing soft gripper design, multimodal sensing, and learning‐based planning and control. It surveys key neural network architectures and benchmark datasets and identifies critical challenges such as sim‐to‐real transfer, generalization, and continual ...
Arnab Majumder, Jelizaveta Konstantinova, Graham Deacon, Kaspar Althoefer   +3 more
wiley   +1 more source

Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI

Advanced Science, EarlyView.
ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia, Martin J. Graves, Mary McLean, Carolin Pirkl, Carola‐Bibiane Schönlieb, Timo Schirmer, Florian Wiesinger, Matthias J. Ehrhardt   +7 more
wiley   +1 more source

Integrating biological knowledge into variable selection : an empirical Bayes approach with an application in cancer biology [PDF]

, 2012
Background: An important question in the analysis of biochemical data is that of identifying subsets of molecular variables that may jointly influence a biological response.
Bayani, Nora, Mukherjee, Sach, Kuo, Wen-Lin, Spellman, Paul T., Sach Mukherjee, Gray Joe W, Neve Richard M, Safiyyah Ziyad, Ziyad Safiyyah, Hill Steven M, Ziyad, Safiyyah, Mukherjee Sach, Paul T Spellman, Joe W Gray, Hill, Steven M. (Mark), Kuo Wen-Lin, Neve, Richard M., Bayani Nora, Steven M Hill, Richard M Neve, Nora Bayani, Wen-Lin Kuo, Gray, Joe W., Spellman Paul T   +23 more
core   +1 more source

An Adipocyte MKK3–p38β Axis Preserves Insulin Responsiveness in Mice and Is Reciprocally Altered in Human Obesity

Advanced Science, EarlyView.
The adipocyte MKK3–p38β axis emerges as an adaptive stress‐response pathway during obesity. Human visceral adipose tissue analyses, adipocyte‐specific mouse models, and primary adipocytes show that the MKK3–p38β axis supports insulin responsiveness by restraining p70S6K‐dependent inhibitory IRS1 feedback and preserving AKT–GLUT4 signaling. This pathway
Edgar Bernardo, Nuria Matesanz, Jorge‐Luis Torres, Alba C. Arcones, Juan Ignacio Jiménez‐Loygorri, Alfonso Mora, Leticia Herrera‐Melle, Luis Leiva‐Vega, Maria Elena Rodriguez, Lourdes Hernández‐Cosido, Marta Leon, Paula Yong González, Teresa Durán, Tamara Parracho, Francisca Mulero, Rubén Nogueiras, J. Simon C. Arthur, Angel R. Nebreda, Roger J. Davis, Miguel Marcos, Guadalupe Sabio   +20 more
wiley   +1 more source