Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Empirical Method to Interpret Standard Deviation01:09

Empirical Method to Interpret Standard Deviation

The empirical rule, also known as the three-sigma rule, allows a statistician to interpret the standard deviation in a normally distributed dataset. The rule states that 68% of the data lies within one standard deviation from the mean, 95% lies within two standard deviations from the mean, and 99.7% lies within three standard deviations from the mean. Additionally, this rule is also called the 68-95-99.7 rule.
This rule is used widely in statistics to calculate the proportion of data values...
Estimation of the Physical Quantities01:05

Estimation of the Physical Quantities

On many occasions, physicists, other scientists, and engineers need to make estimates of a particular quantity. These are sometimes referred to as guesstimates, order-of-magnitude approximations, back-of-the-envelope calculations, or Fermi calculations. The physicist Enrico Fermi was famous for his ability to estimate various kinds of data with surprising precision. Estimating does not mean guessing a number or a formula at random. Instead, estimation means using prior experience and sound...
Dynamic Modulus of Elasticity of Concrete01:16

Dynamic Modulus of Elasticity of Concrete

The dynamic modulus of elasticity assesses how a concrete structure deforms under impact or dynamic loads. It is typically higher than the static modulus of elasticity, measured under slow, steady loading conditions.
The sonic test is a common method to determine the dynamic modulus. In this test, a concrete beam, sized either 6 x 6 x 30 inches or 4 x 4 x 20 inches, is clamped at its center. Vibrations are initiated at one end of the beam by an electromagnetic exciter unit powered by a...
Determination of Expected Frequency01:08

Determination of Expected Frequency

Suppose one wants to test independence between the two variables of a contingency table. The values in the table constitute the observed frequencies of the dataset. But how does one determine the expected frequency of the dataset? One of the important assumptions is that the two variables are independent, which means the variables do not influence each other. For independent variables, the statistical probability of any event involving both variables is calculated by multiplying the individual...
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
What are Estimates?01:06

What are Estimates?

It isn't easy to measure a parameter such as the mean height or the mean weight of a population. So, we draw samples from the population and calculate the mean height or mean weight of the individuals in the sample. This sample data acts as a representative measure of the population parameter. These sample statistics are known as estimates. 
The estimate for the mean of a sample is denoted by ͞x, whereas the mean of the population is designated as μ. Further, parameters such as the mean,...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

[Application of EMD algorithm to the dynamic spectrum non-invasive measurement of hemoglobin].

Guang pu xue yu guang pu fen xi = Guang pu·2014
Same author

[Application of EMD and SPA algorithm in the detection of benzoyl peroxide addition in flour by spectroscopy].

Guang pu xue yu guang pu fen xi = Guang pu·2013
Same author

[Noninvasive measurement of the human RBC concentration based on BP NN model].

Guang pu xue yu guang pu fen xi = Guang pu·2012
Same author

[Noninvasive measurement of serum total protein content by near-infrared reflection spectra with tongue inspection].

Guang pu xue yu guang pu fen xi = Guang pu·2012
Same author

[Improving component analysis ability of the complex mixed solutions by multi-dimensional diffuse transmittance spectrometry].

Guang pu xue yu guang pu fen xi = Guang pu·2012
Same author

[The effects of signal to noise ratio of instrument and number of wavelengths on the accuracy of spectral analysis].

Guang pu xue yu guang pu fen xi = Guang pu·2012

Related Experiment Video

Updated: May 14, 2026

Quantifying Cytoskeleton Dynamics Using Differential Dynamic Microscopy
06:37

Quantifying Cytoskeleton Dynamics Using Differential Dynamic Microscopy

Published on: June 15, 2022

[D-value estimation of dynamic spectrum based on the statistical methods].

Ling Lin1, Yong-Cheng Li, Meng-Jun Wang

  • 1State Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin 300072, China. linling@tju.edu.cn

Guang Pu Xue Yu Guang Pu Fen Xi = Guang Pu
|February 8, 2013
PubMed
Summary

A new D-value estimation method improves noninvasive blood component detection by enhancing dynamic spectrum (DS) extraction. This statistical approach offers better denoising and significantly faster data processing compared to traditional methods.

More Related Videos

Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band
06:43

Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band

Published on: May 2, 2018

Application of Voltage in Dynamic Light Scattering Particle Size Analysis
07:51

Application of Voltage in Dynamic Light Scattering Particle Size Analysis

Published on: January 24, 2020

Related Experiment Videos

Last Updated: May 14, 2026

Quantifying Cytoskeleton Dynamics Using Differential Dynamic Microscopy
06:37

Quantifying Cytoskeleton Dynamics Using Differential Dynamic Microscopy

Published on: June 15, 2022

Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band
06:43

Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band

Published on: May 2, 2018

Application of Voltage in Dynamic Light Scattering Particle Size Analysis
07:51

Application of Voltage in Dynamic Light Scattering Particle Size Analysis

Published on: January 24, 2020

Area of Science:

  • Biomedical Engineering
  • Spectroscopy
  • Data Analysis

Context:

  • Noninvasive blood component analysis is crucial for diagnostics.
  • Current time-domain single-trial dynamic spectrum (DS) estimation methods have limitations.
  • Improving the accuracy and efficiency of DS extraction is essential.

Purpose:

  • To introduce a novel D-value estimation method for dynamic spectrum (DS) analysis.
  • To address the drawbacks of existing time-domain single-trial estimation techniques.
  • To enhance the noninvasive concentration detection of blood components.

Summary:

  • The D-value estimation method utilizes statistical properties by calculating the absolute difference between corresponding wavelength values to form DS.
  • Valid DSs are selected using statistical methods and then superimposed and averaged for the final output.
  • This method was compared to the single-trial estimation using data from 48 volunteers.

Impact:

  • The D-value method demonstrated improved denoising capabilities.
  • It significantly increased the average number of valid DSs from 48 to 130.
  • Mean square error was reduced from 0.39 to 0.006, and processing speed increased nearly 20-fold, enhancing DS extraction quality.