Results 141 to 150 of about 169,837 (295)

M-ECG: extracting heart signals with a novel computational analysis of magnetoencephalography data

Frontiers in Neuroimaging
Magnetoencephalography (MEG) captures neural activity with high temporal and spatial resolution, but it typically discards other biopotentials, such as cardiac signals, as noise. Here, we demonstrate the feasibility of extracting cardiac signals from MEG
Aqil Izadysadr, Hamideh Sadat Bagherzadeh, Jennifer R. Stapleton-Kotloski, Gautam S. Popli, Cormac A. O'Donovan, Dwayne W. Godwin, Dwayne W. Godwin   +6 more
doaj   +1 more source

A Machine Learning Approach for the Detection of QRS Complexes in Electrocardiogram (ECG) Using Discrete Wavelet Transform (DWT) Algorithm. [PDF]

Comput Intell Neurosci, 2022
Rizwan A, Priyanga P, Abualsauod EH, Zafrullah SN, Serbaya SH, Halifa A.   +5 more
europepmc   +1 more source

A smart headband for multimodal physiological monitoring in human exercises

Advanced Science, EarlyView.
A novel smart headband incorporating a thermal‐sensation‐based electronic skin is presented for continuous and accurate multimodal physiological monitoring, including pulse waveforms, total metabolic energy expenditure, heart rate, and forehead temperature, across both static and dynamic daily activities.
Shiqiang Liu, Guanxing Chen, Jingyi Peng, Shuo Tian, Qian Mao, Caise Wei, Jinfeng Yuan, Rong Zhu   +7 more
wiley   +1 more source

Cardiac arrhythmia ,Electrocardiogram(ECG), GNU octave.

, 2019
We propose a model for detail that captures oscillations and we use the local extrema of the input image to extract information about oscillations..We propose a simple algorithm for decomposing images into multiple scales. Currently used edge-preserving image decomposition techniques consider image detail to be of low contrast variation.
openaire   +1 more source

Model‐Inversion‐Resistant Physical Unclonable Neural Network Using Vertical NAND Flash Memory

Advanced Science, EarlyView.
Schematic and key features of the proposed forward‐forward physical unclonable neural network (FF‐PUNN), incorporating a concealable physical unclonable function (PUF) layer and forward‐forward (FF) learning. ABSTRACT The growing use of neural networks in privacy‐sensitive applications necessitates architectures that inherently protect both data and ...
Sung‐Ho Park, Ryun‐Han Koo, Jonghyun Ko, Jiseong Im, Yeongheon Yang, Mingyun Oh, Dongbeen Shin, Gyuweon Jung, Jong‐Ho Lee   +8 more
wiley   +1 more source

ST-segment elevation myocardial infarction mimics: The differential diagnosis of nonacute coronary syndrome causes of ST-segment/T-wave abnormalities in the chest pain patient

Turkish Journal of Emergency Medicine
The evaluation of adult patients suspected of ST-segment elevation myocardial infarction (STEMI) includes a focused history and examination, 12-lead electrocardiogram (ECG), and cardiac serum marker analysis.
James H. Moak, Andrew E. Muck, William J. Brady   +2 more
doaj   +1 more source

Electrocardiogram-based feature extraction for machine learning classification of obstructive sleep apnea [PDF]

, 2016
Mitiche, Imene, Morison, Gordon, Stewart, Brian G.   +2 more
core   +1 more source

A Shallow U-Net Architecture for Reliably Predicting Blood Pressure (BP) from Photoplethysmogram (PPG) and Electrocardiogram (ECG) Signals. [PDF]

Sensors (Basel), 2022
Mahmud S, Ibtehaz N, Khandakar A, Tahir AM, Rahman T, Islam KR, Hossain MS, Rahman MS, Musharavati F, Ayari MA, Islam MT, Chowdhury MEH.   +11 more
europepmc   +1 more source

Optical Charge Trap Memory Based on Graphene/ZnO Heterostructures for Long‐Term Retention and Adaptive Learning

Advanced Electronic Materials, EarlyView.
A biocompatible graphene/ZnO optical charge trap memory (CTM) is reported with over 54 h retention, enabled by interfacial photodoping. Using transient absorption spectroscopy and electrical analysis, charge transfer quenching is elucidated and reveal that a large energy barrier at the interface is responsible for long‐term memory retention.
Seungmin Shin, Junhyung Kim, Hyungdoh Lee, Yixuan Dou, Jacob T. Heiden, Seung Eun Lee, Jinwoo Song, Lina Quan, Giulia Tagliabue, Min Seok Jang, Himchan Cho   +10 more
wiley   +1 more source

Ergonomic Sponge Electrodes From Recycled PEDOT:PSS

Advanced Electronic Materials, EarlyView.
ABSTRACT Emerging technologies in human–machine interfacing increasingly aim to develop solutions that naturally conform to the body's unique characteristics. Ergonomics and electrical performance in cutaneous sensing are crucial for accurate and reliable translation of biosignals.
Matías Ceballos, Wei‐Ting Ting, Susanne Thümmler, Esma Ismailova   +3 more
wiley   +1 more source