High frequency oscillations (HFO) in limbic epilepsy represent a marked difference between abnormal and normal brain activity. Faced with the difficult of visually detecting HFOs in large amounts of intracranial EEG data, it is necessary to develop an automated process. This paper presents Teager Energy as a method of finding HFOs. Teager energy is an ideal measure because unlike conventional energy it takes into account the frequency component of the signal as well as signal amplitude. This greatly aids in the dissection of HFOs out of the noise and other signals contained in the EEG. Therein, Teager energy analysis is able to detect high-frequency, low-amplitude components that conventional energy measurements would miss.
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http://dx.doi.org/10.1109/IEMBS.2006.259694 | DOI Listing |
Sci Rep
December 2024
Xi'an Key Laboratory of Wellbore Integrity Evaluation, Xi'an Shiyou University, Xi'an, 710065, China.
Rolling bearings of the vibration exciter are prone to failure due to long-term high amplitude alternating impact loads, causing economic losses and threatening production safety. The heavy environmental noise during the operation of the vibration exciter and the high vibration level generated by the eccentric block make the weak bearing fault features submerged and difficult to extract. Teager-Kaiser energy operator is a popular method for extracting bearing fault features.
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August 2024
Civil Engineering Department, University of Technology- Iraq, Baghdad, Iraq.
Fault detection and isolation in unmanned aerial vehicle (UAV) propellers are critical for operational safety and efficiency. Most existing fault diagnosis techniques rely basically on traditional statistical-based methods that necessitate better approaches. This study explores the application of untraditional feature extraction methodologies, namely Permutation Entropy (PE), Lempel-Ziv Complexity (LZC), and Teager-Kaiser Energy Operator (TKEO), on the PADRE dataset, which encapsulates various rotor fault configurations.
View Article and Find Full Text PDFBiomed Tech (Berl)
December 2024
Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China.
Objectives: To overcome the limitations of traditional diagnosis of orbicularis oris muscle function in mouth-breathing patients, this study aims to propose a surface electromyographic (sEMG) based method for reliable and accurate quantitative assessment of lip closure ability.
Methods: A total of 21 volunteers (16 patients and 5 healthy subjects, aged 8-16) were included in the study. Three nonlinear onset detection algorithms - Teager-Kaiser Energy (TKE) operator, Sample Entropy (SampEn), and Fuzzy Entropy (FuzzyEn) - were compared for their ability to identify lip closure in sEMG signals.
IEEE Trans Neural Syst Rehabil Eng
June 2024
In Huntington's disease (HD), wearable inertial sensors could capture subtle changes in motor function. However, disease-specific validation of methods is necessary. This study presents an algorithm for walking bout and gait event detection in HD using a leg-worn accelerometer, validated only in the clinic and deployed in free-living conditions.
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May 2024
Department of Electrical Engineering, College of Engineering, King Saud University, Riyadh, Saudi Arabia.
Effective management of dementia requires the timely detection of mild cognitive impairment (MCI). This paper introduces a multi-objective optimization approach for selecting EEG channels (and features) for the purpose of detecting MCI. Firstly, each EEG signal from each channel is decomposed into subbands using either variational mode decomposition (VMD) or discrete wavelet transform (DWT).
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