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Related Concept Videos

NMR Spectrometers: Resolution and Error Correction01:14

NMR Spectrometers: Resolution and Error Correction

When magnetic nuclei in a sample achieve resonance and undergo relaxation, the signal detected in NMR is an approximately exponential free induction decay. Fourier transform of an exponential decay yields a Lorentzian peak in the frequency domain. Lorentzian peaks in an NMR spectrum are defined by their amplitude, full width at half maximum, and position, where the peak width is governed by the spin-spin relaxation time alone. In real experiments, however, the applied magnetic field is rendered...
¹³C NMR: ¹H–¹³C Decoupling01:04

¹³C NMR: ¹H–¹³C Decoupling

The probability of having two carbon-13 atoms next to each other is negligible because of the low natural abundance of carbon-13. Consequently, peak splitting due to carbon-carbon spin-spin coupling is not observed in spectra. However, protons up to three sigma bonds away split the carbon signal according to the n+1 rule, resulting in complicated spectra.
A broadband decoupling technique is used to simplify these complex, sometimes overlapping, signals. Broadband decoupling relies on a...
Double Resonance Techniques: Overview01:12

Double Resonance Techniques: Overview

Double resonance techniques in Nuclear Magnetic Resonance (NMR) spectroscopy involve the simultaneous application of two different frequencies or radiofrequency pulses to manipulate and observe two distinct nuclear spins. One important application of double resonance is spin decoupling, which selectively suppresses coupling with one type of nucleus while observing the NMR signal from another nucleus, simplifying the spectrum and enhancing resolution.
Spin decoupling is usually achieved by...
IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations01:08

IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations

Identical bonds within a polyatomic group can stretch symmetrically (in-phase) or asymmetrically (out-of-phase). Similar to hydrogen bonding, these vibrations also influence the shape of the IR peak. Generally, asymmetric stretching frequencies are higher than symmetric stretching frequencies. For example, primary amines exhibit two distinct IR peaks between 3300–3500 cm−1 corresponding to the symmetric and asymmetric N-H stretching, while secondary amines exhibit a single stretching vibration...
IR Spectroscopy: Molecular Vibration Overview01:24

IR Spectroscopy: Molecular Vibration Overview

When Infrared (IR) radiation passes through a covalently bonded molecule, the bonds transition from lower to higher vibrational levels. The fundamental vibrational motions that result in infrared absorption can be classified as stretching or bending vibrations.
Stretching vibrations are vibrational motions that occur along the bond line, changing the bond length or distance between two bonded atoms. They are further distinguished as symmetric or asymmetric. In symmetric stretching, the...
IR Spectroscopy: Hooke's Law Approximation of Molecular Vibration01:16

IR Spectroscopy: Hooke's Law Approximation of Molecular Vibration

A covalently bonded heteronuclear diatomic molecule can be modeled as two vibrating masses connected by a spring. The vibrational frequency of the bond can be expressed using an equation derived from Hooke's law, which describes how the force applied to stretch or compress a spring is proportional to the displacement of the spring. In this case, the atoms behave like masses, and the bond acts like a spring.
According to Hooke's law, the vibrational frequency is directly proportional to the...

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Using MazeSuite and Functional Near Infrared Spectroscopy to Study Learning in Spatial Navigation
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Motion artifact cancellation in NIR spectroscopy using discrete Kalman filtering.

Meltem Izzetoglu1, Prabhakar Chitrapu, Scott Bunce

  • 1School of Biomedical Eng, Science and Health Sys, Drexel University, Philadelphia, PA 19104, USA. meltem@cbis.ece.drexel.edu

Biomedical Engineering Online
|March 11, 2010
PubMed
Summary

A new Kalman filtering algorithm effectively removes motion artifacts from Near Infrared spectroscopy (NIR) signals. This method improves signal quality for brain activity assessment in real-world applications without extra sensors.

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Functional Near Infrared spectroscopy (fNIR) is susceptible to motion artifacts, particularly in real-world scenarios like pilot or child studies.
  • Head movements introduce noise unrelated to cognitive activity, compromising the accuracy of metabolic change assessments.
  • Reliable evaluation of brain activity using fNIR necessitates effective removal of these motion-induced artifacts.

Purpose of the Study:

  • To introduce and evaluate a Kalman filtering-based algorithm for eliminating motion artifacts in Near Infrared spectroscopy (NIR) measurements.
  • To compare the efficacy of the proposed Kalman filtering approach against previously studied adaptive and Wiener filtering methods.

Main Methods:

  • Utilized a dataset with induced motion artifacts from previous studies.
  • Employed Kalman filtering for artifact removal and compared its performance against adaptive and Wiener filtering.
  • Statistical analysis involved paired t-tests on data from eleven subjects, focusing on signal-to-noise ratio improvement.

Main Results:

  • The Kalman filtering method demonstrated superior signal-to-noise ratio gains compared to adaptive filtering.
  • Results showed Kalman filtering performance comparable to Wiener filtering.
  • The proposed method is well-suited for real-time applications and does not require additional sensor measurements.

Conclusions:

  • A novel Kalman filtering approach effectively addresses motion artifact removal in NIR recordings.
  • This algorithm integrates benefits of adaptive and Wiener filtering for efficient real-time use.
  • The method offers a practical solution for motion artifact reduction in fNIR studies without supplementary sensors.