J
Justyna Skibinska
Researcher at Brno University of Technology
Publications - 7
Citations - 306
Justyna Skibinska is an academic researcher from Brno University of Technology. The author has contributed to research in topics: Fourier transform & Wearable technology. The author has an hindex of 3, co-authored 7 publications receiving 45 citations. Previous affiliations of Justyna Skibinska include Polish Academy of Sciences & AGH University of Science and Technology.
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Journal ArticleDOI
A Survey on Wearable Technology: History, State-of-the-Art and Current Challenges
Aleksandr Ometov,Viktoriia Shubina,Lucie Klus,Justyna Skibinska,Salwa Saafi,Pavel Pascacio,Laura Flueratoru,Darwin Quezada Gaibor,Nadezhda Chukhno,Olga Chukhno,Asad Ali,Asma Channa,Ekaterina Svertoka,Ekaterina Svertoka,Waleed Bin Qaim,Raúl Casanova-Marqués,Raúl Casanova-Marqués,Sylvia Holcer,Sylvia Holcer,Joaquín Torres-Sospedra,Sven Casteleyn,Giuseppe Ruggeri,Giuseppe Araniti,Radim Burget,Jiri Hosek,Elena Simona Lohan +25 more
TL;DR: An extensive and diverse classification of wearables, based on various factors, a discussion on wireless communication technologies, architectures, data processing aspects, and market status, as well as a variety of other actual information on wearable technology are provided.
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The Rise of Wearable Devices during the COVID-19 Pandemic: A Systematic Review.
TL;DR: In this paper, a comprehensive review of wearable systems for the remote management and automated assessment of COVID-19, taking into account the reliability and acceptability of the implemented technologies is presented.
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Comparison of spectral and spatial denoising techniques in the context of High Definition FT-IR imaging hyperspectral data
Paulina Koziol,Magda K. Raczkowska,Magda K. Raczkowska,Justyna Skibinska,Justyna Skibinska,Slawka Urbaniak-Wasik,Czesława Paluszkiewicz,Wojciech M. Kwiatek,Tomasz P. Wrobel +8 more
TL;DR: The results presented here clearly show the benefit of using hyperspectral denoising schemes such as PCA and MNF which outperform other methods.
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Denoising influence on discrete frequency classification results for quantum cascade laser based infrared microscopy
Paulina Koziol,Magda K. Raczkowska,Justyna Skibinska,Nicholas J. McCollum,Slawka Urbaniak-Wasik,Czesława Paluszkiewicz,Wojciech M. Kwiatek,Tomasz P. Wrobel +7 more
TL;DR: This work is the first to show the effects of denoising on classification accuracy of QCL data and is likely to be transferable to other QCL microscopes and other modalities using DF imaging, e.g. AFM-IR or CARS/SRS imaging.
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COVID-19 Diagnosis at Early Stage Based on Smartwatches and Machine Learning Techniques
TL;DR: In this paper, a non-invasive method for detecting COVID-19 positive people using wearable devices and for the analysis of bio-markers using artificial intelligence was proposed.