Data and code for: A 3-DoF wrist control based on natural arm movements outperforms current myoelectric prosthesis in VR

This repository contains data and code for: A 3-DoF wrist control based on natural arm movements outperforms current myoelectric prosthesis in VR Bardisbanian Lucas¹, Leconte Vincent¹, Doat Émilie¹, Klotz Rémi², de Rugy Aymar¹ ¹ University of Bordeaux, CNRS, INCIA, UMR 5287, F-33000² CSMR Tour de Gassies, F-33250 Bruges, France The acronym VCRA (Virtual Control for transRadial Amputee) is associated with this repository.It contains:a dataset (DataOnline_VCRA folder) of able-bodied participants (s10 to s29) and amputee participants(s1 to s8) performing two tasks (pick-and-place and clothespin relocation) in virtual reality.basic code files to perform data analysis and artificial neural network inference (CodeOnline_VCRAfolder).All the information needed to understand the structure of DataOnline_VCRA and CodeOnline_VCRA isprovided in the DocOnline_VCRA folder.The file GlobalDocumentation explains how to install requirements and run the data analysis andartificial neural network inference.The file VarDataExplained lists and describes all variables recorded during experiments in the phasefiles (PHASE.json). Notes: This study was supported by the ANR-PRCE grant I-Wrist (ANR-23-CE19-0031-01) and by the Frenchgovernment in the framework of the University of Bordeaux’s IdEx “Investments for the Future” program GPRBRAIN_2030.