Results 71 to 80 of about 616,724 (329)

AR-PCA-HMM approach for sensorimotor task classification in EEG-based brain-computer interfaces [PDF]

, 2010
We propose an approach based on Hidden Markov models (HMMs) combined with principal component analysis (PCA) for classification of four-class single trial motor imagery EEG data for brain computer interfacing (BCI) purposes. We extract autoregressive (AR)
Argunsah, Ali Ozgur, Argunşah, Ali Özgür, Cetin, Mujdat, Çetin, Müjdat   +3 more
core   +1 more source

Seeing inside the Body Using Wearable Sensing and Imaging Technologies

Advanced Healthcare Materials, EarlyView.
This review explores wearable technologies for noninvasive internal health monitoring. It categorizes approaches into indirect sensing (e.g., bioelectrical and biochemical signals) and direct imaging (e.g., wearable ultrasound and EIT), highlighting multimodal integration and system‐level innovation toward personalized, continuous healthcare.
Sumin Kim, Seunghun Han, Sehwan Park, Jahyun Koo   +3 more
wiley   +1 more source

Deltagende borgere i Energibyen Frederikshavn

Akademisk Kvarter, 2012
Anders Horsbøl and Lisbeth Eeg Deltagende borgere i Energibyen Frederikshavn (Participating citizen in the Energy City of Frederikshavn). Denmark has some experience with local participation of citizens in projects in which energy saving "green" or ...
Anders Horsbøl, Lisbeth Eeg
doaj   +1 more source

Scale-invariance of human EEG signals in sleep [PDF]

, 2007
We investigate the dynamical properties of electroencephalogram (EEG) signals of human in sleep. By using a modified random walk method, We demonstrate that the scale-invariance is embedded in EEG signals after a detrending procedure.
A. L. Goldberger, A. Rechschaffen, Bing-Hong Wang, E. R. Kandel, Hui-Jie Yang, J. Fell, P. Bak, P. Lévy, Pei-Ling Zhou, S. Abe, Shi-Min Cai, Tao Zhou, Zhao-Hui Jiang   +12 more
core   +2 more sources

Unperceivable Designs of Wearable Electronics

Advanced Materials, EarlyView.
Unperceivable wearable technologies seamlessly integrate into everyone's daily life, for healthcare and Internet‐of‐Things applications. By remaining completely unnoticed both visually and tactilely, by the user and others, they ensure medical privacy and allow natural social interactions.
Yijun Liu, Séverine De Mulatier, Naoji Matsuhisa   +2 more
wiley   +1 more source

Performance‐Recoverable Closed‐Loop Neuroprosthetic System

Advanced Materials, EarlyView.
A self‐healing and stretchable bilayer (SSB) electrode with spontaneous performance recovery consists of a nanomembrane (closely packed aligned Pt‐coated Ag nanowires embedded in the self‐healing polymer) and a nanocomposite (Pt‐coated Ag flakes in the self‐healing polymer).
Yewon Kim, Kyumin Kang, Ja Hoon Koo, Yoonyi Jeong, Sungjun Lee, Dongjun Jung, Duhwan Seong, Hyeok Kim, Hyung‐Seop Han, Minah Suh, Dae‐Hyeong Kim, Donghee Son   +11 more
wiley   +1 more source

Deep Learning of Human Perception in Audio Event Classification

, 2018
In this paper, we introduce our recent studies on human perception in audio event classification by different deep learning models. In particular, the pre-trained model VGGish is used as feature extractor to process audio data, and DenseNet is trained by
Beuret, Samuel, Oyama, Keizo, Yu, Yi, Zeng, Donghuo   +3 more
core   +1 more source

Flexible Sensor‐Based Human–Machine Interfaces with AI Integration for Medical Robotics

Advanced Robotics Research, EarlyView.
This review explores how flexible sensing technology and artificial intelligence (AI) significantly enhance human–machine interfaces in medical robotics. It highlights key sensing mechanisms, AI‐driven advancements, and applications in prosthetics, exoskeletons, and surgical robotics.
Yuxiao Wang, Zhipeng Jiang, Sun Hwa Kwon, Matthew Ibrahim, Alexander Dang, Lin Dong   +5 more
wiley   +1 more source

A large-scale evaluation framework for EEG deep learning architectures

, 2018
EEG is the most common signal source for noninvasive BCI applications. For such applications, the EEG signal needs to be decoded and translated into appropriate actions.
Ball, Tonio, Behncke, Joos, Fiederer, Lukas D. J., Heilmeyer, Felix A., Schirrmeister, Robin T., Völker, Martin   +5 more
core   +1 more source

Bioelectronic Sensors for Neuromuscular Perception in Human‐Machine Interfaces

Advanced Robotics Research, EarlyView.
This review summarizes recent advances in bioelectronic sensors for neuromuscular perception in human‐machine interfaces. By integrating biopotential, electrical impedance, and electrochemical sensing strategies with flexible electrode interfaces, these bioelectronic sensing systems enable intuitive, real‐time detection of muscle and nerve activity ...
Junwei Li, Bangyan Niu, Kunlin Wu, Jingcheng Xiao, Xiaoyan Liu, Yifan Wang   +5 more
wiley   +1 more source