How to compare NIRS spectra between each other?

In summary: And NIRS stands for near-infrared spectroscopy, a non-invasive optical imaging technique used to measure changes in blood oxygenation levels in the brain.
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groot44
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What would be the best practices for comparing multiple NIRS spectra between each other? I’m working with NIRS data of multiple samples from different subjects, measured with the same measurement setup. The aim is in the end to analyse correlation between signals and anatomical differences between subjects.

Based on what I have found so far, I’m considering either absolute power or absolute intensity of the spectrum (not sure if they are the same or not). I’m fairly new with NIRS signal analysis and thus wanted to ask for opinions with the matter. Thanks in advance!
 
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  • #2
groot44 said:
What would be the best practices for comparing multiple NIRS spectra between each other? I’m working with NIRS data of multiple samples from different subjects, measured with the same measurement setup. The aim is in the end to analyse correlation between signals and anatomical differences between subjects.

Based on what I have found so far, I’m considering either absolute power or absolute intensity of the spectrum (not sure if they are the same or not). I’m fairly new with NIRS signal analysis and thus wanted to ask for opinions with the matter. Thanks in advance!
Welcome to PF.

What does your typical spectra data look like as a function of time and subject task? I'm not familiar with the bandwidth of the NIRS spectrum -- how wide is it, and what is the significance of the different regions in the spectrum?

What tasks do you have the subjects performing, and are the recordings synchronized? Or are the scans just resting scans and you want to compare them?

I've worked with EEG and EKG pads and recordings a fair amount -- Is hair an issue with NIRS sensing, or do you shave the probe sites?

1619395143812.png

https://cortechsolutions.com/product/ni-br-sym54/
 
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  • #3
You could, for example do a PCR.
 
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berkeman said:
Welcome to PF.

What does your typical spectra data look like as a function of time and subject task? I'm not familiar with the bandwidth of the NIRS spectrum -- how wide is it, and what is the significance of the different regions in the spectrum?

What tasks do you have the subjects performing, and are the recordings synchronized? Or are the scans just resting scans and you want to compare them?

I've worked with EEG and EKG pads and recordings a fair amount -- Is hair an issue with NIRS sensing, or do you shave the probe sites?

View attachment 282060
https://cortechsolutions.com/product/ni-br-sym54/

Thanks for the answer! I haven't worked with EEG yet but hopefully in the future. To answer your question about hair, I believe it could be issue but we used light sources on forehead to avoid the issue.

The bandwidth is given as electromagnetic spectrum from approximately 300nm to 1200nm (wavelength), measurement done by spectrometer utilising charge-coupled device (CCD). The most important wavelengths are 830nm and 905nm due to oxyhemoglobin and deoxyhemoglobin absorption qualities.

The integration time of the samples is same. These are only resting measurements and would like to further analyse them for correlation. So I have been considering how to quantify the results.
 
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DrDu said:
You could, for example do a PCR.
What is PCR? Or do you mean principle component analysis PCA?
 
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groot44 said:
What is PCR? Or do you mean principle component analysis PCA?
I tell you if you tell me what NIRS means :cool:
 
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1. How do you normalize NIRS spectra for comparison?

Normalization is the process of adjusting the intensity of a spectrum to a standard level for comparison. This can be done by dividing each data point by the highest intensity value in the spectrum, or by using a reference standard for calibration.

2. What is the best way to compare NIRS spectra from different instruments?

To compare NIRS spectra from different instruments, it is important to first calibrate the instruments to a common reference standard. This can be done by using a set of known samples that have been measured on both instruments, or by using a certified reference material.

3. Can NIRS spectra be compared across different sample types?

Yes, NIRS spectra can be compared across different sample types. However, it is important to note that different sample types may have different spectral characteristics, so it is necessary to account for these differences when comparing spectra.

4. How do you account for baseline variations when comparing NIRS spectra?

Baseline variations can be accounted for by subtracting a baseline correction from the spectra. This can be done manually, by selecting a baseline region and subtracting the average intensity from the entire spectrum, or automatically using software algorithms.

5. What statistical methods are commonly used to compare NIRS spectra?

Some commonly used statistical methods for comparing NIRS spectra include principal component analysis (PCA), partial least squares (PLS), and discriminant analysis. These methods can help identify differences and similarities between spectra and can be used to classify samples based on their spectral characteristics.

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