Pranav Mamidanna
Pranav Mamidanna
Eric and Wendy Schmidt AI in Science Postdoctoral Fellow, Imperial College London
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Zitiert von
Zitiert von
DeepLabCut: markerless pose estimation of user-defined body parts with deep learning
A Mathis, P Mamidanna, KM Cury, T Abe, VN Murthy, MW Mathis, ...
Nature neuroscience 21 (9), 1281-1289, 2018
Contrasting action and posture coding with hierarchical deep neural network models of proprioception
KJ Sandbrink, P Mamidanna, C Michaelis, M Bethge, MW Mathis, ...
Elife 12, e81499, 2023
Action representation in the mouse parieto-frontal network
T Tombaz, BA Dunn, K Hovde, RJ Cubero, B Mimica, P Mamidanna, ...
Scientific reports 10 (1), 5559, 2020
The impact of objective functions on control policies in closed-loop control of grasping force with a myoelectric prosthesis
P Mamidanna, JL Dideriksen, S Dosen
Journal of Neural Engineering 18 (5), 056036, 2021
Estimating speed-accuracy trade-offs to evaluate and understand closed-loop prosthesis interfaces
P Mamidanna, JL Dideriksen, S Dosen
Journal of Neural Engineering 19 (5), 056012, 2022
Towards goal-driven deep neural network models to elucidate human arm proprioception
P Mamidanna, C Michaelis, A Mathis, M Bethge
28th Annual Meeting of the Society for the Neural Control of Movement (NCM …, 2018
Measuring and monitoring skill learning in closed-loop myoelectric hand prostheses using speed-accuracy tradeoffs
P Mamidanna, S Gholinezhad, D Farina, JL Dideriksen, S Dosen
Journal of Neural Engineering, 2024
Investigating motor skill in closed-loop myoelectric hand prostheses: Through speed-accuracy trade-offs
P Mamidanna
Skill Acquisition in Prosthesis Force Control with Supplementary EMG Feedback
P Mamidanna, S Gholinezhad, J Dideriksen, S Dosen
Myoelectric Controls Symposium, 2022
Optimizing Neural Source Extraction Algorithms: A Performance Measure Based on Neuronal Network Properties
P Mamidanna
EMG feedback for improved control of myoelectric hand prostheses
S Dosen, P Mamidanna, J Tchimino, F Gasparic, N Jorgovanovic
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