Wilmsdorff, Julian von ; Kuijper, Arjan (2022)
Optimizations for Passive Electric Field Sensing.
In: Sensors, 2022, 22 (16)
doi: 10.26083/tuprints-00022332
Article, Secondary publication, Publisher's Version
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| Item Type: | Article |
|---|---|
| Type of entry: | Secondary publication |
| Title: | Optimizations for Passive Electric Field Sensing |
| Language: | English |
| Date: | 12 September 2022 |
| Place of Publication: | Darmstadt |
| Year of primary publication: | 2022 |
| Publisher: | MDPI |
| Journal or Publication Title: | Sensors |
| Volume of the journal: | 22 |
| Issue Number: | 16 |
| Collation: | 10 Seiten |
| DOI: | 10.26083/tuprints-00022332 |
| Corresponding Links: | |
| Origin: | Secondary publication DeepGreen |
| Abstract: | Passive electric field sensing can be utilized in a wide variety of application areas, although it has certain limitations. In order to better understand what these limitations are and how countervailing measures to these limitations could be implemented, this paper contributes an in-depth discussion of problems with passive electric field sensing and how to bypass or solve them. The focus lies on the explanation of how commonly known signal processing techniques and hardware build-up schemes can be used to improve passive electric field sensors and the corresponding data processing. |
| Uncontrolled Keywords: | capacitive sensing, passive electric field sensing, sensors, signal processing |
| Status: | Publisher's Version |
| URN: | urn:nbn:de:tuda-tuprints-223323 |
| Additional Information: | This article belongs to the Special Issue Wireless Smart Sensors for Digital Healthcare and Assisted Living |
| Classification DDC: | 000 Generalities, computers, information > 004 Computer science |
| Divisions: | 20 Department of Computer Science > Interactive Graphics Systems 20 Department of Computer Science > Fraunhofer IGD |
| Date Deposited: | 12 Sep 2022 13:11 |
| Last Modified: | 14 Nov 2023 19:05 |
| SWORD Depositor: | Deep Green |
| URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/22332 |
| PPN: | 499561112 |
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