Recognizing Hand Gestures using Solar Cells

Dong Ma, Guohao Lan, Changshuo Hu, Mahbub Hassan, Wen Hu, Upama Mushfika, Ashraf Uddin, Moustafa Youssef

Research output: Contribution to journalArticleScientificpeer-review

4 Citations (Scopus)
9 Downloads (Pure)

Abstract

We design a system, SolarGest, which can recognize hand gestures near a solar-powered device by analyzing the patterns of the photocurrent. SolarGest is based on the observation that each gesture interferes with incident light rays on the solar panel in a unique way, leaving its discernible signature in harvested photocurrent. Using solar energy harvesting laws, we develop a model to optimize design and usage of SolarGest. To further improve the robustness of SolarGest under non-deterministic operating conditions, we combine dynamic time warping with Z-score transformation in a signal processing pipeline to pre-process each gesture waveform before it is analyzed for classification. We evaluate SolarGest with both conventional opaque solar cells as well as emerging see-through transparent cells. Our experiments demonstrate that SolarGest achieves 99% for six gestures with a single cell and 95%for fifteen gesture with a22solar cell array. The power measurement study suggests that SolarGest consume 44% less power compared to light sensor based systems.

Original languageEnglish
Pages (from-to)4223 - 4235
Number of pages13
JournalIEEE Transactions on Mobile Computing
Volume22
Issue number7
DOIs
Publication statusPublished - 2023

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • Solar energy harvesting
  • visible light sensing
  • gesture recognition

Fingerprint

Dive into the research topics of 'Recognizing Hand Gestures using Solar Cells'. Together they form a unique fingerprint.

Cite this