This paper introduces a wavelet packet algorithm based on a new wavelet like filter created by a neural mass model in place of wavelet. The hypothesis is that the performance of an ERP based BCI system can be improved by choosing an optimal wavelet derived from underlying mechanism of ERPs. The wavelet packet transform has been chosen for its generalization in comparison to wavelet. We compared the performance of proposed algorithm with existing standard wavelets as Db4, Bior4.4 and Coif3 in wavelet packet platform. The results showed a lowest cross validation error for the new filter in classification of two different kinds of ERP datasets via a SVM classifier.
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http://dx.doi.org/10.1109/IEMBS.2007.4352681 | DOI Listing |
Sci Rep
January 2025
Department of Theoretical Electrical Engineering and Diagnostics of Electrical Equipment, Institute of Electrodynamics, National Academy of Sciences of Ukraine, Beresteyskiy, 56, Kyiv-57, Kyiv, 03680, Ukraine.
Power quality (PQ) disturbances, such as voltage sags, are significant issues that can lead to damage in electrical equipment and system downtime. Detecting and classifying these disturbances accurately is essential for maintaining reliable power systems. This paper introduces a novel approach to voltage sag analysis by employing wavelet packet analysis combined with energy-based feature extraction to enhance PQ monitoring.
View Article and Find Full Text PDFSensors (Basel)
December 2024
College of Civil Engineering and Architecture, Xiamen University of Technology, Xiamen 361024, China.
Sensors (Basel)
December 2024
School of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan 430064, China.
Two identically sized RC beams were fabricated to investigate the effects of explosive loads on the flexural behaviour of Reinforced Concrete (RC) beams. One of the beams was subjected to an explosive load to induce post-explosion damage, and subsequently, both beams underwent flexural capacity testing. Integrating piezoelectric smart aggregates (SAas) within the beams facilitated continuous observation of the damage conditions, allowing for the assessment of internal concrete deterioration from explosive impacts to bending failures.
View Article and Find Full Text PDFBioengineering (Basel)
December 2024
Biomedical Sensors & Systems Lab, University of Memphis, Memphis, TN 38152, USA.
A battery-operated biomedical wearable device gradually assists in clinical tasks to monitor patients' health states regarding early diagnosis and detection. This paper presents the development of a self-powered portable electronic module by integrating an onboard energy-harvesting facility for electrocardiogram (ECG) signal processing and personalized health monitoring. The developed electronic module provides a customizable approach to power the device using a lithium-ion battery, a series of silicon photodiode arrays, and a solar panel.
View Article and Find Full Text PDFRev Sci Instrum
December 2024
School of Mechatronic Engineering, Southwest Petroleum University, Chendu 610500, China.
The early fault characteristics of rolling bearings are weak, especially in a strong noise environment, which are more difficult to extract; therefore, a method based on wavelet packet decomposition, multi-verse optimizer, and maximum correlated kurtosis deconvolution for weak fault feature extraction of rolling bearings is proposed. First, the original vibration signal is decomposed using wavelet packet decomposition, followed by proposing a signal reconstruction method combining the Pearson correlation coefficient and energy ratio to effectively remove noise from the original signal. Second, the parameters L and M of Maximum Correlated Kurtosis Deconvolution (MCKD) are optimized using the multi-verse optimizer algorithm to obtain optimal filter settings.
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