Results 51 to 60 of about 456,367 (154)

The application of multiscale joint permutation entropy on multichannel sleep electroencephalography [PDF]

AIP Advances, 2019
Sleep quantification and automatic scoring of sleep stages via electroencephalogram (EEG) signals has been a challenge for years. It is crucial to investigate the correlation of brain waves by sleep EEG analysis due to the association between rhythmic oscillations of neuronal activity and neocortical synchronization.
Yi Yin, Chung-Kang Peng, Fengzhen Hou, He Gao, Pengjian Shang, Qiang Li, Yan Ma   +6 more
openaire   +2 more sources

Fault Diagnosis of ME Marine Diesel Engine Fuel Injector with Novel IRCMDE Method

Polish Maritime Research, 2023
As an important component of the fuel injection system, the fuel injector is crucial for ensuring the power, economy, and emissions for a whole ME (machine electronically-controlled) marine diesel engine.
Shi Qingguo, Hu Yihuai, Yan Guohua
doaj   +1 more source

The Refined Composite Downsampling Permutation Entropy Is a Relevant Tool in the Muscle Fatigue Study Using sEMG Signals

Entropy, 2021
Surface electromyography (sEMG) is a valuable technique that helps provide functional and structural information about the electric activity of muscles. As sEMG measures output of complex living systems characterized by multiscale and nonlinear behaviors,
Philippe Ravier, Antonio Dávalos, Meryem Jabloun, Olivier Buttelli   +3 more
doaj   +1 more source

Matlab codes for "Improved Multiscale Permutation Entropy for Biomedical Signal Analysis: Interpretation and Application to Electroencephalogram Recordings"

, 2015
Permutation entropy (PE) is a well-known and fast method extensively used in many physiological signal processing applications to measure the irregularity of time series.
Azami, Hamed, Escudero, Javier
core   +2 more sources

Tsallis Entropy-Based Complexity-IPE Casualty Plane: A Novel Method for Complex Time Series Analysis

Entropy
Due to its capacity to unveil the dynamic characteristics of time series data, entropy has attracted growing interest. However, traditional entropy feature extraction methods, such as permutation entropy, fall short in concurrently considering both the ...
Zhe Chen, Changling Wu, Junyi Wang, Hongbing Qiu   +3 more
doaj   +1 more source

Consciousness Detection in a Complete Locked-in Syndrome Patient through Multiscale Approach Analysis

Entropy, 2020
Completely locked-in state (CLIS) patients are unable to speak and have lost all muscle movement. From the external view, the internal brain activity of such patients cannot be easily perceived, but CLIS patients are considered to still be conscious and ...
Shang-Ju Wu, Nicoletta Nicolaou, Martin Bogdan   +2 more
doaj   +1 more source

Evaluation of Acute Tonic Cold Pain From Microwave Transcranial Transmission Signals Using Multi-Entropy Machine Learning Approach

IEEE Access, 2020
This study aims to improve the accuracy of detecting acute tonic cold pain (CP) perception from microwave transcranial transmission (MTT) signals. Two different types of CP and no-pain (NP) MTT signals are obtained from 15 subjects. Four features, namely,
Daoshuang Geng, Daoguo Yang, Miao Cai, Weidong Hao   +3 more
doaj   +1 more source

Comparison of Multiscale Entropy for Lung Sound Classification

, 2018
Lung sound is a biological signal that can be used to determine the health level of the respiratory tract. Various digital signal processing techniques have been developed for automatic classification of lung sounds. Entropy is one of the parameters used
Rizal, Achmad, Nugroho, Hanung Adi, Hidayat, Risanuri   +2 more
core   +1 more source

A multi-level analysis of motor and behavioural dynamics in 9-month-old preterm and term-born infants during changing emotional and interactive contexts

Scientific Reports
Computational analysis of infant movement has significant potential to reveal markers of developmental health. We report two studies employing dynamic analyses of motor kinematics and motor behaviours, which characterise movement at two levels, in 9 ...
Yu Wei Chua, Lorena Jiménez-Sánchez, Victoria Ledsham, Sinéad O’Carroll, Ralf F. A. Cox, Ivan Andonovic, Christos Tachtatzis, James P. Boardman, Sue Fletcher-Watson, Philip Rowe, Jonathan Delafield-Butt   +10 more
doaj   +1 more source

Bearings fault diagnosis based on adaptive local iterative filtering–multiscale permutation entropy and multinomial logistic model with group-lasso

Advances in Mechanical Engineering, 2019
Bearing fault diagnosis attracts great attention because the bearing condition has direct effects on productivity and safety in industry. To accurately identify the operating condition of bearings, a novel bearing fault diagnosis method based on adaptive
Jinbao Zhang, Yongqiang Zhao, Ming Liu, Lingxian Kong   +3 more
doaj   +1 more source