Results 51 to 60 of about 5,224,879 (222)

Multidimensional and Multifunctional Laser‐Induced Graphene (LIG) for Point‐of‐Care and Wearable Biosensing, Theranostics, and Bioactive Interfaces Toward Personalized Healthcare and Regenerative Medicine

Advanced Science, EarlyView.
Multidimensional laser‐induced graphene (LIG) spanning from 0D to 3D architectures is comprehensively reviewed for multifunctional biomedical platforms, including biosensing, theranostics, and bioactive interface applications, which highlights its potentials for point‐of‐care diagnostics, wearable health monitoring, smart drug delivery, and tissue ...
Li Zhang, Yurou Yuan, Xiaohong Ding, Wing Cheung Mak   +3 more
wiley   +1 more source

Brain-actuated functional electrical stimulation elicits lasting arm motor recovery after stroke

Nature Communications, 2018
Brain-computer interface (BCI) can improve motor skills on stroke patients. This study shows that BCI-controlled neuromuscular electrical stimulation therapy can cause cortical reorganization due to activation of efferent and afferent pathways, and this ...
A. Biasiucci, R. Leeb, I. Iturrate, S. Perdikis, A. Al-Khodairy, T. Corbet, A. Schnider, T. Schmidlin, H. Zhang, M. Bassolino, D. Viceic, P. Vuadens, A. G. Guggisberg, J. d. R. Millán   +13 more
doaj   +1 more source

A flexible neural implant with ultrathin substrate for low-invasive brain–computer interface applications

Microsystems & Nanoengineering, 2022
Implantable brain–computer interface (BCI) devices are an effective tool to decipher fundamental brain mechanisms and treat neural diseases. However, traditional neural implants with rigid or bulky cross-sections cause trauma and decrease the quality of ...
Zhejun Guo, Fang Wang, Longchun Wang, Kejun Tu, Chunpeng Jiang, Ye Xi, Wen Hong, Qingda Xu, Xiaolin Wang, Bin Yang, Bomin Sun, Zude Lin, Jingquan Liu   +12 more
doaj   +1 more source

Brain‐Computer Interface Training Fosters Perceptual Skills to Detect Errors

Advanced Science, EarlyView.
Accurate perception of visuomotor errors underpins motor precision and learning, yet conventional behavioral training fails to improve sensitivity to subtle errors. Real‐time EEG‐based brain‐computer interface feedback targeting the error positivity component enhances perceptual learning of small errors.
Deland H. Liu, Fumiaki Iwane, Minsu Zhang, Leonardo G. Cohen, José del R. Millán   +4 more
wiley   +1 more source

A Novel Quick-Response Eigenface Analysis Scheme for Brain–Computer Interfaces

Sensors, 2022
The brain–computer interface (BCI) is used to understand brain activities and external bodies with the help of the motor imagery (MI). As of today, the classification results for EEG 4 class BCI competition dataset have been improved to provide better ...
Hojong Choi, Junghun Park, Yeon-Mo Yang
doaj   +1 more source

Preserving Motor Features by Alternative Re‐Referencing to Remove Heart Artifact on the Stentrode

Advanced Science, EarlyView.
Endovascular brain‐computer interfaces record neural activity from within cerebrovasculature, at the expense of electrocardiogram contamination. Band‐limited independent component analysis separates this heart‐based artifact from task‐relevant neural activity in each frequency band, enabling the reconstruction of cleaner neural recordings without the ...
Ariel K. Feldman, Kriti Kacker, Rahyun Yun, Nikole Chetty, James Bennett, Peter E. Yoo, Raul G. Nogueira, Jennifer L. Collinger, Nicholas L. Opie, Thomas J. Oxley, David F. Putrino, Douglas J. Weber   +11 more
wiley   +1 more source

Monitoraggio dell'attività cerebrale tramite brain-computer-interface(BCI) [PDF]

, 2022
Un’interfaccia cervello-computer (in inglese, Brain-Computer Interface, abbreviato in BCI, o anche Brain-Machine Interface, BMI) è un sistema di comunicazione in cui i messaggi o i comandi che l’utente normalmente invia per agire sul mondo esterno non ...
Gnamteu Sottang, Fabrice
core  

Toward High‐Resolution Polymeric Neural Interfaces: A Practical Guide for Electron Beam Lithography

Advanced Science, EarlyView.
Electron beam lithography (EBL) enables sub‐micron patterning of polymer‐based neural implants, overcoming the resolution limits of optical lithography. By addressing challenges such as charging, non‐planarity, and substrate heating, it supports higher channel density, improved miniaturization, and better long‐term tissue integration.
Hanna Karlsson‐Fernberg, Maria Asplund
wiley   +1 more source

Evolution of the Brain Computing Interface (BCI) and Proposed Electroencephalography (EEG) Signals Based Authentication Model

MATEC Web of Conferences, 2018
With current advancements in the field of Brain Computer interface it is required to study how it will affect the other technologies currently in use. In this paper, the authors motivate the need of Brain Computing Interface in the era of IoT (Internet ...
Ramzan Qaseem, Shidlovskiy Stanislav
doaj   +1 more source

A review of artificial intelligence for EEG‐based brain−computer interfaces and applications

Brain Science Advances, 2020
The advancement in neuroscience and computer science promotes the ability of the human brain to communicate and interact with the environment, making brain–computer interface (BCI) top interdisciplinary research.
Zehong Cao
doaj   +1 more source