Best Paper Award

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4.6CiteScore
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Signals Best Paper Award is granted annually to highlight publications of high quality, scientific significance, and extensive influence. The evaluation committee members choose 2 articles of exceptional quality that were published in the journal the year before the previous year and announce them online by the end of June.

The Prize:
–1 research articles and 1 reviews will be selected.
– Each winner will receive CHF 300, a certificate, and a voucher to waive the Article Processing Charges (APCs) for one submission in the journal (subject to peer review)—valid for one year.

Signals Best Paper Award

Winner announcement date: 30 June 2026

Eligibility and Requirements:

– All papers published in Signals will be eligible (both regular and Special Issue submissions).

Selection Criteria:

– Scientific merit and broad impact;
– Originality of the research objectives and/or the ideas presented;
– Creativity of the study design or uniqueness of the approaches and concepts;
– Clarity of presentation;
– Citations and downloads.

Past Winners

Winner

Article
30 Citations
4,169 Views
18 Pages
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Development of an Integrated System of sEMG Signal Acquisition, Processing, and Analysis with AI Techniques
Filippo Laganà,
Danilo Pratticò,
Giovanni Angiulli,
Giuseppe Oliva,
Salvatore A. Pullano,
Mario Versaci and
Fabio La Foresta
Signals2024, 5(3), 476-493;https://doi.org/10.3390/signals5030025
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26 July 2024
The development of robust circuit structures remains a pivotal milestone in electronic device research. This article proposes an integrated hardware–software system designed for the acquisition, processing, and analysis of surface electromyogra...
Full Article
Article
6 Citations
5,001 Views
28 Pages
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EEG-TCNTransformer: A Temporal Convolutional Transformer for Motor Imagery Brain–Computer Interfaces
Anh Hoang Phuc Nguyen,
Oluwabunmi Oyefisayo,
Maximilian Achim Pfeffer and
Sai Ho Ling
Signals2024, 5(3), 605-632;https://doi.org/10.3390/signals5030034
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23 September 2024
In brain–computer interface motor imagery (BCI-MI) systems, convolutional neural networks (CNNs) have traditionally dominated as the deep learning method of choice, demonstrating significant advancements in state-of-the-art studies. Recently, T...
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