scholarly journals Near-Infrared Spectroscopy and the Forest Products Industry / La spectroscopie proche infrarouge et le secteur des produits forestiers

2013 ◽  
Vol 89 (05) ◽  
pp. 575-576 ◽  
Author(s):  
Brigitte Leblon ◽  
Satoru Tsuchikawa
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Forest Products ◽  
Forest Products Industry

Potential of near-infrared spectroscopy to characterize wood products1This article is a contribution to the series The Role of Sensors in the New Forest Products Industry and Bioeconomy.

2011 ◽  
Vol 41 (11) ◽  
pp. 2150-2157 ◽  
Author(s):  
P.A. Cooper ◽  
D. Jeremic ◽  
S. Radivojevic ◽  
Y.T. Ung ◽  
B. Leblon
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Wood Species ◽  
Near Infrared ◽  
Abies Balsamea ◽  
Forest Products ◽  
Tsuga Heterophylla ◽  
Thuja Plicata ◽  
Species Differentiation ◽  
Specific Response

Near infrared spectroscopy (NIRS) has high potential as a rapid nondestructive approach to identifying wood species and estimating properties that affect their utilization. This study found that NIRS could differentiate certain wood species groups. True firs (balsam fir ( Abies balsamea (L.) Mill.) and subalpine fir ( Abies lasiocarpa (Hook.) Nutt.)) could be distinguished from pine and spruce in eastern and western spruce–pine–fir, respectively, more than 95% of the time. Western hemlock ( Tsuga heterophylla (Raf.) Sarg.) could be differentiated from amabilis fir ( Abies amabilis Douglas ex J. Forbes) in the Hem–Fir species group with about 90% accuracy. Average wood moisture content (MC) of air-dried southern pine and western redcedar ( Thuja plicata Donn ex D. Don) samples wood could be estimated by NIRS ±10%–30% at high moisture contents and more accurately (±2%–5%) below 30% MC. Conditioned samples of amabilis fir had predicted MCs within 2%–3% of measured values in the 0%–30% MC range. However, the broad applicability and response of NIRS to a number of factors may be its greatest weakness, since measurements for a specific response, such as MC or species differentiation, may be confounded by the effects of other variables, such as surface roughness and localized density differences. It is recommended that instrumentation with a relatively large probe (large illumination area) be used to average such variables in the sample.

Near-infrared spectroscopy (NIRS) – a promising brain imaging method in Psychiatry?

2008 ◽  
Vol 39 (01) ◽  
Author(s):  
AJ Fallgatter ◽  
AC Ehlis ◽  
MM Richter ◽  
M Schecklmann ◽  
MM Plichta
Keyword(s):  
Infrared Spectroscopy ◽  
Brain Imaging ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Imaging Method

A Study of Frontal Signals in Brain Computer Interfaces: Interpretation of EEG & FNIRS

2020 ◽  
pp. 136-142
Author(s):  
S. Srilekha ◽  
B. Vanathi
Keyword(s):  
Infrared Spectroscopy ◽  
Healthy Subject ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Economic Conditions ◽  
Brain Computer Interfaces ◽  
Functional Near Infrared Spectroscopy ◽  
Computer Interfaces ◽  
Rehabilitation Devices

This paper focuses on electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) comparison to help the rehabilitation patients. Both methods have unique techniques and placement of electrodes. Usage of signals are different in application based on the economic conditions. This study helps in choosing the signal for the betterment of analysis. Ten healthy subject datasets of EEG & FNIRS are taken and applied to plot topography separately. Accuracy, Sensitivity, peaks, integral areas, etc are compared and plotted. The main advantages of this study are to prompt their necessities in the analysis of rehabilitation devices to manage their life as a typical individual.

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