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Conventional scalp-based EEG systems are cumbersome to use, requiring extensive setup, restrictive wiring, and conductive gels that can dry out and limit long-term monitoring, while also carrying social stigma. As a result, there is…

Neurons and Cognition · Quantitative Biology 2026-04-27 Min Suk Lee , Abhinav Uppal , Ananya Thota , Chetan Pathrabe , Rommani Mondal , Akshay Paul , Yuchen Xu , Gert Cauwenberghs

Integrating Brain-Machine Interfaces into non-clinical applications like robot motion control remains difficult - despite remarkable advancements in clinical settings. Specifically, EEG-based motor imagery systems are still error-prone,…

Computational modelling offers a cost-effective and time-efficient alternative to experimental studies in biomedical engineering. In cardiac electro-mechanics, finite element method (FEM)-based simulations provide valuable insights into…

Computational Engineering, Finance, and Science · Computer Science 2025-08-20 Tan Tran , Denisa Martonova , Sigrid Leyendecker

Conductive elastomers present desirable qualities for sensing pressure in-vivo, such as high piezoresistance in tiny volumes, conformability and, biocompatibility. Many PDMS-based electrically conductive nanocomposites however, are…

A novel technique for Electroencephalogram (EEG) compression is proposed in this article. This technique models the intrinsic dependency inherent between the different EEG channels. It is based on dipole fitting that is usually used in…

Information Theory · Computer Science 2024-10-30 Hoda Daou , Fabrice Labeau

Soft electronics are a promising and revolutionary alternative for traditional electronics when safe physical interaction between machines and the human body is required. Among various materials architectures developed for producing soft…

Applied Physics · Physics 2021-04-16 Kaveh Alizadeh

Fatigue, sleepiness and disturbed sleep are important factors in health and safety in modern society and there is considerable interest in developing technologies for routine monitoring of associated physiological indicators.…

All data modalities are not created equal, even when the signal they measure comes from the same source. In the case of the brain, two of the most important data modalities are the scalp electroencephalogram (EEG), and the intracranial…

Signal Processing · Electrical Eng. & Systems 2025-02-26 Francesco Stefano Carzaniga , Gary Tom Hoppeler , Michael Hersche , Kaspar Anton Schindler , Abbas Rahimi

Phantom devices allow the human variable to be controlled for in order to allow clear comparison and validation of biomedical imaging hardware and software. There is currently no standard phantom for electroencephalography (EEG). To be…

Medical Physics · Physics 2016-09-27 W. David Hairston , Geoffrey A. Slipher , Alfred B. Yu

Dry-electrode Motor Imagery Electroencephalography (MI-EEG) enables fast, comfortable, real-world Brain Computer Interface by eliminating gels and shortening setup for at-home and wearable use.However, dry recordings pose three main issues:…

Human-Computer Interaction · Computer Science 2026-01-27 Tianyi Gong , Can Han , Junxi Wu , Dahong Qian

Carbon nanofibres (CNF) were dispersed into an epoxy resin using a combination of ultrasonication and mechanical mixing. The electronic transport properties of the resulting composites were investigated by means of impedance spectroscopy.…

Materials Science · Physics 2008-02-29 Aïssa Allaoui , Suong V. Hoa , Martin D. Pugh

Electroencephalography (EEG) is an integral tool in neurocognitive research worldwide. However, research grade EEG (32/64ch) systems are expensive and have cumbersome setup designed for clinical usage not suited for rugged environment of…

Neurons and Cognition · Quantitative Biology 2022-09-27 Manvi Jain , C. M. Markan

Piezoelectricity, the generation of electric charge in response to mechanical stress, is a key property in both natural and synthetic materials. This study significantly boosts the piezoelectric response of chitosan, a biodegradable…

Electrocardiogram (ECG) signals are often degraded by various noise sources such as baseline wander, motion artifacts, and electromyographic interference, posing a major challenge in clinical settings. This paper presents a lightweight deep…

Signal Processing · Electrical Eng. & Systems 2025-11-18 Mahdi Pirayesh Shirazi Nejad , David Hicks , Matt Valentine , Ki H. Chon

Electroencephalography (EEG) is a neuroimaging technique that records brain neural activity with high temporal resolution. Unlike other methods, EEG does not require prohibitively expensive equipment and can be easily set up using…

Human-Computer Interaction · Computer Science 2024-10-01 Arash Akbarinia

Electroencephalogram (EEG) data compression is necessary for wireless recording applications to reduce the amount of data that needs to be transmitted. In this paper, an asymmetrical sparse autoencoder with a discrete cosine transform (DCT)…

Signal Processing · Electrical Eng. & Systems 2023-09-22 Xin Zhu , Hongyi Pan , Shuaiang Rong , Ahmet Enis Cetin

The adoption of high-density electrode systems for human-machine interfaces in real-life applications has been impeded by practical and technical challenges, including noise interference, motion artifacts and the lack of compact electrode…

Robotics · Computer Science 2024-04-01 Rejin John Varghese , Matteo Pizzi , Aritra Kundu , Agnese Grison , Etienne Burdet , Dario Farina

Electrocorticography (ECoG) or intracranial electroencephalography (iEEG) monitors electric potential directly on the surface of the brain and can be used to inform treatment planning for epilepsy surgery when paired with numerical…

The wearable EEG device sector is advancing rapidly, enabling fast and reliable detection of brain activity for investigating brain function and pathology. However, many current EEG systems remain challenging for users with neurological…

Emerging Technologies · Computer Science 2026-01-23 Komal Komal , Frances Cleary , Ram Prasadh Narayanan , John Wells , Marco Buiatti , Louise Bennett

Intracranial electrocorticography (ECoG) offers high-signal-to-noise access to cortical activity for brain-computer interfaces, yet limited per-patient data has led most prior work to rely on small, subject-specific decoders that neglect…

Artificial Intelligence · Computer Science 2026-05-12 Liuyin Yang , Qiang Sun , Bob Van Dyck , Eva Calvo Merino , Marc M. Van Hulle
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