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Analysis of biceps brachii sEMG signal using Multiscale Fuzzy Approximate Entropy
2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015In this work, an attempt has been made to differentiate sEMG signals under muscle fatigue and non-fatigue conditions using multiscale features. Signals are recorded from biceps brachii muscle of 50 normal adults during repetitive dynamic contractions. After preprocessing, the signal is divided into six segments, out of which first and last segments are
Navaneethakrishna Makaram +2 more
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Analysis of Complex Time Series Using a Modified Multiscale Fuzzy Entropy Algorithm
2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI), 2016Multiscale fuzzy entropy (MFE) is an effective algorithm which has been successfully applied in many fields for measuring the complexity of a time series. Though, MFE can yield inaccurate entropy estimations as the coarse-graining procedure used by the algorithm reduces the length of the time series under investigation.
Tian Han 0004 +3 more
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2016 IEEE Region 10 Conference (TENCON), 2016
Recognition of human body posture from the signals of wearable sensor has attracted a great interests in many applications, such as health care, aged care and sports. Main aim of the presented work is to recognize the basic activities of daily living (ADL) and detection of fall using two triaxial accelerometer located at the chest and thigh of the ...
Alok Verma +3 more
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Recognition of human body posture from the signals of wearable sensor has attracted a great interests in many applications, such as health care, aged care and sports. Main aim of the presented work is to recognize the basic activities of daily living (ADL) and detection of fall using two triaxial accelerometer located at the chest and thigh of the ...
Alok Verma +3 more
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2025 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE)
Mild Cognitive Impairment (MCI) is a transitional phase between normal aging and Alzheimer's Disease (AD), necessitating early and precise detection for effective intervention. Recently, electroencephalography (EEG) has gained importance as a non-invasive tool to capture the complex nonlinear and multivariate nature of neural signals.
Arpaia P. +8 more
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Mild Cognitive Impairment (MCI) is a transitional phase between normal aging and Alzheimer's Disease (AD), necessitating early and precise detection for effective intervention. Recently, electroencephalography (EEG) has gained importance as a non-invasive tool to capture the complex nonlinear and multivariate nature of neural signals.
Arpaia P. +8 more
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ISA Transactions
To improve the physical interpretability and multiscale stability of entropy-based methods in nonlinear vibration analysis, a composite multiscale fuzzy extreme position entropy (CMFEPE) is proposed. The method characterizes fault-induced structural distortion by modeling the positional deviation of local extreme via phase space reconstruction.
Qintao Lv +3 more
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To improve the physical interpretability and multiscale stability of entropy-based methods in nonlinear vibration analysis, a composite multiscale fuzzy extreme position entropy (CMFEPE) is proposed. The method characterizes fault-induced structural distortion by modeling the positional deviation of local extreme via phase space reconstruction.
Qintao Lv +3 more
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Multiscale Fuzzy-Entropy Approach for Vascular Network Delineation in Retinal Images
2021Temitope Mapayi, Pius A. Owolawi
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Multimodal loosening detection for threaded fasteners based on multiscale cross fuzzy entropy
Mechanical Systems and Signal Processing, 2023Jiayu Huang +3 more
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