https://github.com/ami-iit/paper_belli_2023_sensors_insole-calibration

Code and material associated to "Modeling and Calibration of Pressure-Sensing Insoles via a New Plenum-Based Chamber" (Belli et al.)

https://github.com/ami-iit/paper_belli_2023_sensors_insole-calibration

Science Score: 49.0%

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Repository

Code and material associated to "Modeling and Calibration of Pressure-Sensing Insoles via a New Plenum-Based Chamber" (Belli et al.)

Basic Info
  • Host: GitHub
  • Owner: ami-iit
  • License: bsd-3-clause
  • Language: MATLAB
  • Default Branch: main
  • Homepage:
  • Size: 14.6 MB
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  • Stars: 5
  • Watchers: 6
  • Forks: 0
  • Open Issues: 0
  • Releases: 1
Created almost 3 years ago · Last pushed almost 3 years ago
Metadata Files
Readme License

README.md

Modeling and Calibration of Pressure-Sensing Insoles via a New Plenum-Based Chamber

I. Belli, I. Sorrentino, S. Dussoni, G. Milani, L. Rapetti, Y. Tirupachuri, E. Valli, P. Reddy Vanteddu, M. Maggiali and D. Pucci "Modeling and Calibration of Pressure-Sensing Insoles via a New Plenum-Based Chamber" in MDPI Sensors 2023, 23(9), 4501.

This repository collects code and data needed to replicate the results reported in the paper "Modeling and Calibration of Pressure-Sensing Insoles via a New Plenum-Based Chamber". In our work, we presented a novel hardware developed for accurate calibration of pressure sensing insoles, as well as the optimization-based calibration method employed for identifying the parameters of the optimal polynomial models for each of the sensing units on the insole.

Citing this work

To cite our work or if you use our code/methods, please cite: bibtex @Article{s23094501, AUTHOR = {Belli, Italo and Sorrentino, Ines and Dussoni, Simeone and Milani, Gianluca and Rapetti, Lorenzo and Tirupachuri, Yeshasvi and Valli, Enrico and Vanteddu, Punith Reddy and Maggiali, Marco and Pucci, Daniele}, TITLE = {Modeling and Calibration of Pressure-Sensing Insoles via a New Plenum-Based Chamber}, JOURNAL = {Sensors}, VOLUME = {23}, YEAR = {2023}, NUMBER = {9}, ARTICLE-NUMBER = {4501}, URL = {https://www.mdpi.com/1424-8220/23/9/4501}, ISSN = {1424-8220}, DOI = {10.3390/s23094501} }

Owner

  • Name: Artificial and Mechanical Intelligence
  • Login: ami-iit
  • Kind: organization
  • Location: Italy

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