Automated calibration of somatosensory stimulation using reinforcement learning.
Journal Information
Full Title: J Neuroeng Rehabil
Abbreviation: J Neuroeng Rehabil
Country: Unknown
Publisher: Unknown
Language: N/A
Publication Details
Subject Category: Physical and Rehabilitation Medicine
Available in Europe PMC: Yes
Available in PMC: Yes
PDF Available: No
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"availability of data and materials matlab r codes and data showing the interaction with the rl platform and its step-wise evolution are available at the following directory: https://github com/noemi-gozzi/rl-somatosensory-calibration git ( https://doi org/10 5281/zenodo 7648810 ). availability of data and materials matlab r codes and data showing the interaction with the rl platform and its step-wise evolution are available at the following directory: https://github com/noemi-gozzi/rl-somatosensory-calibration git ( https://doi org/10 5281/zenodo 7648810 )."
"availability of data and materials matlab r codes and data showing the interaction with the rl platform and its step-wise evolution are available at the following directory: https://github com/noemi-gozzi/rl-somatosensory-calibration git ( https://doi org/10 5281/zenodo 7648810 )."
"Declarations Ethics approval and consent to participateThe experiments were approved by the ETH Zurich’s ethics commission (EK 2019-N-97, Approved: 27/11/2019). The trial was registered with ClinicalTrial.gov (NCT04217005, First Posted: 03/01/2020). The experiments were performed in accordance with the proposal approved by the ETH Zurich’s ethics commission and in accordance with the Declaration of Helsinki. All subjects read and signed the informed consent including the use of identifiable images in an online open-access publication. Consent for publicationInformed consent for publication of identifying information/images was signed. Competing interestsThe authors declare no competing interests. Competing interests The authors declare no competing interests."
"Funding Open access funding provided by Swiss Federal Institute of Technology Zurich This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (FeelAgain grant agreement No. 759998), Swiss National Science Foundation (SNSF) (MOVEIT 197271) and Innosuisse ICT program (n. 47462.1 IP-ICT). The funders had no role in the experimental design, analysis, or manuscript preparation or submission."
"Trial registration : ClinicalTrial.gov (Identifier: NCT04217005)"
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Last Updated: Aug 05, 2025