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Signals, Volume 5, Issue 2

June 2024 - 11 articles

Cover Story: The balance between dissipative and nonlinear forces allows widespread traveling waves termed solitons to preserve their shape and energy for long distances without steepening and flattening out. We suggest that the electric oscillations detectable by scalp electroencephalography (EEG) could be assessed in terms of solitons. We argue that solitons bear striking similarities with the electric activity recorded for medical conditions like epilepsies and encephalopathies. Emerging from the noisy background of normal electric activity, high-amplitude, low-frequency EEG soliton-like waves with relatively uniform morphology and duration can be observed, characterized by repeated, stereotyped patterns propagating on the brain hemispheric surface over relatively large distances. The theoretical possibility of treating pathological brain oscillations using solitons is discussed in this paper. View this paper
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Articles (11)

  • Article
  • Open Access
1,909 Views
15 Pages

4 June 2024

(1) Problem Statement: The development of clustering algorithms for neural recordings has significantly evolved, reaching a mature stage with predominant approaches including partitional, hierarchical, probabilistic, fuzzy logic, density-based, and l...

  • Article
  • Open Access
2,054 Views
20 Pages

3 June 2024

Collaborative virtual environment (CVE)-based teamwork training offers a promising avenue for inclusive teamwork training. The incorporation of a feedback mechanism within virtual training environments can enhance the training experience by scaffoldi...

  • Review
  • Open Access
9 Citations
4,266 Views
39 Pages

31 May 2024

Effective management of EEG artifacts is pivotal for accurate neurological diagnostics, particularly in detecting early stages of Alzheimer’s disease. This review delves into the cutting-edge domain of fuzzy logic techniques, emphasizing intuit...

  • Article
  • Open Access
2 Citations
1,995 Views
17 Pages

Vibration Suppression of Graphene Reinforced Laminates Using Shunted Piezoelectric Systems and Machine Learning

  • Georgios Drosopoulos,
  • Georgia Foutsitzi,
  • Maria-Styliani Daraki and
  • Georgios E. Stavroulakis

23 May 2024

The implementation of a machine learning approach to predict vibration suppression, as derived from nanocomposite laminates with piezoelectric shunted systems, is studied in this article. Datasets providing the vibration response and vibration attenu...

  • Article
  • Open Access
3 Citations
4,286 Views
30 Pages

8 May 2024

Analyzing brain activity during mental arithmetic tasks provides insight into psychological disorders such as ADHD, dyscalculia, and autism. While most research is conducted on the static functional connectivity of the brain while performing a cognit...

  • Review
  • Open Access
1 Citations
2,463 Views
15 Pages

1 May 2024

A delicate balance between dissipative and nonlinear forces allows traveling waves termed solitons to preserve their shape and energy for long distances without steepening and flattening out. Solitons are so widespread that they can generate both des...

  • Article
  • Open Access
3 Citations
2,304 Views
17 Pages

CNN-Based Pattern Classifiers for Precise Identification of Perinatal EEG Biomarkers of Brain Injury in Preterm Neonates

  • Hamid Abbasi,
  • Malcolm R. Battin,
  • Deborah Rowe,
  • Robyn Butler,
  • Alistair J. Gunn and
  • Laura Bennet

28 April 2024

Electroencephalographic (EEG) monitoring is important for the diagnosis of hypoxic-ischemic (HI) brain injury in high-risk preterm infants. EEG monitoring is limited by the reliance on expert clinical observation. However, high-risk preterm infants o...

  • Review
  • Open Access
3 Citations
4,062 Views
20 Pages

A Systematic Review of Electroencephalography-Based Emotion Recognition of Confusion Using Artificial Intelligence

  • Dasuni Ganepola,
  • Madduma Wellalage Pasan Maduranga,
  • Valmik Tilwari and
  • Indika Karunaratne

25 April 2024

Confusion emotion in a learning environment can motivate the learner, but prolonged confusion hinders the learning process. Recognizing confused learners is possible; nevertheless, finding them requires a lot of time and effort. Due to certain restri...

  • Article
  • Open Access
11 Citations
8,563 Views
28 Pages

Learning with Errors: A Lattice-Based Keystone of Post-Quantum Cryptography

  • Maria E. Sabani,
  • Ilias K. Savvas and
  • Georgia Garani

13 April 2024

The swift advancement of quantum computing devices holds the potential to create robust machines that can tackle an extensive array of issues beyond the scope of conventional computers. Consequently, quantum computing machines create new risks at a v...

  • Article
  • Open Access
4 Citations
2,231 Views
14 Pages

1 April 2024

Dynamic mode decomposition (DMD) is a powerful tool for separating the background and foreground in videos. This algorithm decomposes a video into dynamic modes, called DMD modes, to facilitate the extraction of the near-zero mode, which represents t...

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Signals - ISSN 2624-6120