Spectral analysis of near-infrared spectroscopy signals measured from prefrontal lobe in subjects at risk for stroke

2012 ◽  
Vol 39 (4) ◽  
pp. 2179-2185 ◽  
Author(s):  
Zengyong Li ◽  
Ming Zhang ◽  
Qing Xin ◽  
Guoqiang Chen ◽  
Feifei Liu ◽  
...  
Planta Medica ◽  
2021 ◽  
Author(s):  
Sophia Mayr ◽  
Simon Strasser ◽  
Christian G. Kirchler ◽  
Florian Meischl ◽  
Stefan Stuppner ◽  
...  

AbstractThe content of the flavonolignan mixture silymarin and its individual components (silichristin, silidianin, silibinin A, silibinin B, isosilibinin A, and isosilibinin B) in whole and milled milk thistle seeds (Silybi mariani fructus) was analyzed with near-infrared spectroscopy. The analytical performance of one benchtop and two handheld near-infrared spectrometers was compared. Reference analysis was performed with HPLC following a Soxhlet extraction (European Pharmacopoeia) and a more resource-efficient ultrasonic extraction. The reliability of near-infrared spectral analysis determined through partial least squares regression models constructed independently for the spectral datasets obtained by the three spectrometers was as follows. The benchtop device NIRFlex N-500 performed the best both for milled and whole seeds with a root mean square error of CV between 0.01 and 0.17%. The handheld spectrometer MicroNIR 2200 as well as the microPHAZIR provided a similar performance (root mean square error of CV between 0.01 and 0.18% and between 0.01 and 0.23%, respectively). We carried out quantum chemical simulation of near-infrared spectra of silichristin, silidianin, silibinin, and isosilibinin for interpretation of the results of spectral analysis. This provided understanding of the absorption regions meaningful for the calibration. Further, it helped to better separate how the chemical and physical properties of the samples affect the analysis. While the study demonstrated that milling of samples slightly improves the performance, it was deemed to be critical only for the analysis carried out with the microPHAZIR. This study evidenced that rapid and nondestructive quantification of silymarin and individual flavonolignans is possible with miniaturized near-infrared spectroscopy in whole milk thistle seeds.


Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3072
Author(s):  
Qitao Tan ◽  
Yan Wang ◽  
Zengyong Li ◽  
Daifa Wang ◽  
Wing-Kai Lam ◽  
...  

Spectral analysis of blood flow or blood volume oscillations can help to understand the regulatory mechanisms of microcirculation. This study aimed to explore the relationship between muscle hemodynamic response in the recovery period and exercise quantity. Fifteen healthy subjects were required to perform two sessions of submaximal plantarflexion exercise. The blood volume fluctuations in the gastrocnemius lateralis were recorded in three rest phases (before and after two exercise sessions) using near-infrared spectroscopy. Wavelet transform was used to analyze the total wavelet energy of the concerned frequency range (0.005–2 Hz), which were further divided into six frequency intervals corresponding to six vascular regulators. Wavelet amplitude and energy of each frequency interval were analyzed. Results showed that the total energy raised after each exercise session with a significant difference between rest phases 1 and 3. The wavelet amplitudes showed significant increases in frequency intervals I, III, IV, and V from phase 1 to 3 and in intervals III and IV from phase 2 to 3. The wavelet energy showed similar changes with the wavelet amplitude. The results demonstrate that local microvascular regulators contribute greatly to the blood volume oscillations, the activity levels of which are related to the exercise quantity.


1999 ◽  
Author(s):  
Jiongjiong Yang ◽  
Shaoqun Zeng ◽  
Qingming Luo ◽  
Linchu Guan ◽  
Peizi Kuang ◽  
...  

2014 ◽  
Vol 15 (8) ◽  
pp. 735-741 ◽  
Author(s):  
Ashish K. Patel ◽  
David A. Lazar ◽  
Douglas G. Burrin ◽  
E. O’Brian Smith ◽  
Thomas J. Magliaro ◽  
...  

2015 ◽  
Vol 32 (06) ◽  
pp. 555-564 ◽  
Author(s):  
Shuo Peng ◽  
Elodie Boudes ◽  
Xianming Tan ◽  
Christine Saint-Martin ◽  
Michael Shevell ◽  
...  

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