In this paper, a novel pre-treatment technique Hilbert Huang Transformation with filtering (HHTF) that is coupling of the Hilbert Huang Transformation and the digital filtering is proposed for the measurement of glucose from near infrared spectroscopy. HHTF comprises of the Empirical Mode Decomposition (EMD) and the Hilbert Spectral Analysis. In Hilbert spectral analysis, Butterworth filtering was used to eliminate the noise present in the Intrinsic Mode Functions (IMFs). The traditional Partial Least squares Regression (PLSR) has been used as the regression method. The proposed HHTF with the PLSR method has been assessed to determine the concentration of glucose from near infrared spectra of two distinct compositions that are prepared by mixing triacetin, urea and glucose in a phosphate buffer solution (PBS) and another composition of glucose and human serum albumin in a PBS. The efficiency of the proposed method has been compared with the standard normal variate and the 1 derivative preprocessing methods and is shown to outperform both.
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http://dx.doi.org/10.1109/EMBC44109.2020.9175234 | DOI Listing |
Cogn Neurodyn
December 2024
Key Laboratory of Measurement Technology and Instrumentation of Hebei Province, Institute of Electric Engineering, Yanshan University, Qinhuangdao, Hebei China.
Functional corticomuscular coupling (FCMC), a phenomenon describing the information interaction between the cortex and muscles, plays an important role in assessing hand movements. However, related studies mainly focused on specific actions by one-to-one mapping between the brain and muscles, ignoring the global synchronization across the motor system. Little research has been done on the FCMC difference between the brain and different muscle groups in terms of precise grip tasks.
View Article and Find Full Text PDFSensors (Basel)
November 2024
School of Transportation Engineering, East China Jiaotong University, Nanchang 330013, China.
In long-span bridges and high-rise buildings, closely spaced modes are commonly observed, which greatly increases the challenge of identifying modal parameters. Hilbert-Huang transform (HHT), a widely used method for modal parameter identification, first applies empirical mode decomposition (EMD) to decompose the acquired response and then uses the Hilbert transform (HT) to identify the modal parameters. However, the problem is that the deficiency of mode separation of EMD in HHT limits its application for structures with closely spaced modes.
View Article and Find Full Text PDFSci Rep
November 2024
Sichuan Highway Planning, Survey, Design and Research Institute Ltd, Chengdu, China.
Vibratory rollers are generally used in the process of highway subgrade compaction. In the paper, the vibratory roller-subgrade finite element model was established to simulate the field construction by using ABAQUS. We used Hilbert-Huang Transform to analyze the compaction in the field test from the time-frequency domain.
View Article and Find Full Text PDFStat Med
December 2024
Department of Epidemiology and Biostatistics, University of Georgia, Athens, GA, USA.
Bioengineering (Basel)
September 2024
Department of Artificial Intelligence Convergence, Hallym University, Chuncheon 24252, Republic of Korea.
Electroencephalography (EEG) helps to assess the electrical activities of the brain so that the neuronal activities of the brain are captured effectively. EEG is used to analyze many neurological disorders, as it serves as a low-cost equipment. To diagnose and treat every neurological disorder, lengthy EEG signals are needed, and different machine learning and deep learning techniques have been developed so that the EEG signals could be classified automatically.
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