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IR Frequency Region: Fingerprint Region

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IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the C=O, C=N, and C=C occur between 1600–1850 cm−1.
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IR Spectrum

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When infrared (IR) radiation passes through a molecule, the bonds stretch or bend by absorbing the radiation. This absorption creates the molecule's absorption spectrum, which is the plot of its percentage transmittance versus wavenumber.
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Related Experiment Video

Updated: Jul 10, 2026

High-definition Fourier Transform Infrared (FT-IR) Spectroscopic Imaging of Human Tissue Sections towards Improving Pathology

High-definition Fourier Transform Infrared (FT-IR) Spectroscopic Imaging of Human Tissue Sections towards Improving Pathology

Published on: January 21, 2015

Classification of cervical cancer cells using FTIR data.

Erick Njoroge¹, Stephen R Alty, Mahbub R Gani

¹King's College, London, Centre for Digital Signal Processing Research, Strand, London, UK.

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference

|October 20, 2007

Summary

Fourier-Transform Infra-Red (FTIR) spectroscopy combined with Support Vector Machines (SVM) offers a promising automated approach to cervical cancer screening. This method significantly improved accuracy compared to the traditional Pap smear test.

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Nanotopology of Cell Adhesion upon Variable-Angle Total Internal Reflection Fluorescence Microscopy (VA-TIRFM)

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Published on: October 2, 2012

Area of Science:

Biomedical Engineering
Spectroscopy
Machine Learning

Background:

The Papanicolauo (Pap) smear test has high false-negative rates.
A shortage of colposcopists necessitates alternative cervical cancer screening methods.
Fourier-Transform Infra-Red (FTIR) spectroscopy shows potential for improving test accuracy.

Purpose of the Study:

To apply machine learning (Support Vector Machines - SVM) with FTIR data for improved cervical smear analysis.
To enhance the accuracy of cervical cancer detection beyond the standard Pap test.
To evaluate an automated FTIR-based classifier against traditional methods.

Main Methods:

Utilized Fourier-Transform Infra-Red (FTIR) spectroscopy to collect spectral data from cervical smears.
Applied Support Vector Machines (SVM) machine learning algorithm for data classification.
Compared the performance of the FTIR-SVM method against the Pap smear test and colposcopist findings in a cohort of 53 subjects.

Main Results:

The FTIR-based SVM classifier achieved a 72% classification rate.
The traditional Pap smear test achieved a 43% classification rate in the same cohort.
The FTIR-SVM method demonstrated superior performance in identifying cervical abnormalities.

Conclusions:

FTIR spectroscopy combined with SVM offers a more accurate automated method for cervical cancer screening.
This approach has the potential to overcome limitations of the standard Pap test.
Further research can validate this technique for clinical application in cervical cancer diagnostics.