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Computational design and optimization of electro-physiological sensors

  • Electro-physiological sensing devices are becoming increasingly common in diverse applications. However, designing such sensors in compact form factors and for high-quality signal acquisition is a challenging task even for experts, is typically done using heuristics, and requires extensive training. Our work proposes a computational approach for designing multi-modal electro-physiological sensors. By employing an optimization-based approach alongside an integrated predictive model for multiple modalities, compact sensors can be created which offer an optimal trade-off between high signal quality and small device size. The task is assisted by a graphical tool that allows to easily specify design preferences and to visually analyze the generated designs in real-time, enabling designer-in-the-loop optimization. Experimental results show high quantitative agreement between the prediction of the optimizer and experimentally collected physiological data. They demonstrate that generated designs can achieve an optimal balance between the size of the sensor and its signal acquisition capability, outperforming expert generated solutions.

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Document Type:Article
Author:Aditya Shekhar NittalaORCiD, Andreas KarrenbauerORCiD, Arshad KhanORCiD, Tobias KrausORCiD, Jürgen SteimleORCiD
Parent Title (English):Nature Communications
First Page:6351
Year of first Publication:2021
Release Date:2022/08/16
Tag:biomedical engineering; computer Science
Impact:17.694 (2021)
Funding Information:European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 714797 ERC Starting Grant InteractiveSkin)
DDC classes:500 Naturwissenschaften und Mathematik / 570 Biowissenschaften, Biologie
600 Technik, Medizin, angewandte Wissenschaften / 610 Medizin, Gesundheit
Open Access:Open Access
Signature:INM 2021/132
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International