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A portable EEG signal acquisition system and a limited-electrode channel classification network for SSVEP.
Front Neurorobot
January 2025
College of Engineering, Qufu Normal University, Rizhao, China.
Brain-computer interfaces (BCIs) have garnered significant research attention, yet their complexity has hindered widespread adoption in daily life. Most current electroencephalography (EEG) systems rely on wet electrodes and numerous electrodes to enhance signal quality, making them impractical for everyday use. Portable and wearable devices offer a promising solution, but the limited number of electrodes in specific regions can lead to missing channels and reduced BCI performance.
View Article and Find Full Text PDFECA-FusionNet: A hybrid EEG-fNIRS signals network for MI classification.
J Neural Eng
January 2025
Shanghai Dianji University, shnaghai, Shanghai, Shanghai, 201306, CHINA.
Objective: Among all BCI paradigms, motion imagery (MI) has gained favor among researchers because it allows users to control external devices by imagining movements rather than actually performing actions. This property holds important promise for clinical applications, especially in areas such as stroke rehabilitation. Electroencephalogram (EEG) signals and functional near-infrared spectroscopy (fNIRS) signals are two of the more popular neuroimaging techniques for obtaining MI signals from the brain.
View Article and Find Full Text PDFBioaugmented design and functional evaluation of low damage implantable array electrodes.
Bioact Mater
May 2025
State Key Laboratory for Manufacturing System Engineering, School of Mechanical Engineering, Xi'an Jiaotong University, China.
Implantable neural electrodes are key components of brain-computer interfaces (BCI), but the mismatch in mechanical and biological properties between electrode materials and brain tissue can lead to foreign body reactions and glial scarring, and subsequently compromise the long-term stability of electrical signal transmission. In this study, we proposed a new concept for the design and bioaugmentation of implantable electrodes (bio-array electrodes) featuring a heterogeneous gradient structure. Different composite polyaniline-gelatin-alginate based conductive hydrogel formulations were developed for electrode surface coating.
View Article and Find Full Text PDFZinc oxide nanoparticle-embedded tannic acid/chitosan-based sponge: A highly absorbent hemostatic agent with enhanced antimicrobial activity.
Int J Biol Macromol
January 2025
Nanotechnology Research Center, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran 1416634793, Iran; Wound Care Solution, Nano Fanavaran Narin Teb Co., Tehran, P.O. Box 19177-53531, Iran; Physical Chemistry I, Department of Chemistry and Biology & Research Center of Micro and Nanochemistry and Engineering (Cμ), University of Siegen, 57076 Siegen, Germany. Electronic address:
This study reports the development of a highly absorbent Chitosan (CS)/Tannic Acid (TA) sponge, synthesized via chemical cross-linking with Epichlorohydrin (ECH) and integrated with zinc oxide nanoparticles (ZnO NPs) as a novel hemostatic anti-infection agent. The chemical properties of the sponges were characterized using Fourier-transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), thermogravimetric analysis (TGA), and zeta potential measurements. Morphological and elemental analyses conducted through scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDAX) revealed a uniform distribution of ZnO NPs, with particle sizes below 20 nm.
View Article and Find Full Text PDFEmotion analysis of EEG signals using proximity-conserving auto-encoder (PCAE) and ensemble techniques.
Cogn Neurodyn
December 2025
Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Chennai, TamilNadu India.
Emotion recognition plays a crucial role in brain-computer interfaces (BCI) which helps to identify and classify human emotions as positive, negative, and neutral. Emotion analysis in BCI maintains a substantial perspective in distinct fields such as healthcare, education, gaming, and human-computer interaction. In healthcare, emotion analysis based on electroencephalography (EEG) signals is deployed to provide personalized support for patients with autism or mood disorders.
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