The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/b8098fe4-3f33-4691-9e55-54bf2cc255c3

Varkevisser, Francesc; Serdijn, Wouter A.; Costa, Tiago L. (2025): Data underlying manuscript: Analysis of Power Losses and the Efficacy of Power Minimization Strategies in Multichannel Electrical Stimulation Systems. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/b8098fe4-3f33-4691-9e55-54bf2cc255c3.v1

Dataset

• Electrical and Electronic Engineering
• Biomedical Engineering
• Engineering

Bioelectronics, Electrical Stimulation, Neuromodulation, Power Efficiency

CC BY-NC-SA 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Francesc Varkevisser , Wouter A. Serdijn , Tiago L. Costa

Data underlying the manuscript "Analysis of Power Losses and the Efficacy of Power Minimization Strategies in Multichannel Electrical Stimulation Systems". The manuscript proposes a methodology to analyze the efficacy of voltage scaling strategies in multichannel electrical stimulation systems.

This dataset contains the data and scripts used to produce the results presented in the manuscript.

'dataframes.pkl.gz' contains the data with the calculated power losses and efficiencies. Pickle format zipped with gzip.

'Power_loss_analysis.py' uses 'dataframes.pkl.gz' to produce the figures of the manuscript.

'Generate_dataframes.py' contains the functions used to calculate the associated power losses, allowing future use of the proposed methodology on different distributions.

• 2025-01-14 first online, published, posted

4TU.ResearchData

*.pkl.gz, *.py

• INTENSE (grant code 17619) NWO

TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Microelectronics, Section Bioelectronics