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

Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

732
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
732
Overview of Microsoft Excel as a Data Analysis Tool01:13

Overview of Microsoft Excel as a Data Analysis Tool

1.5K
Microsoft Excel is a cornerstone tool for data analysis and statistical operations, offering a wide array of functionalities to manage, analyze, and visualize data efficiently. Recognized for its versatility, Excel facilitates the performance of basic to complex statistical operations, serving as an indispensable asset for analysts, researchers, and students alike. Excel's significance in data analysis emanates from its spreadsheet environment, where data can be organized in rows and...
1.5K
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

1.5K
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
1.5K
Performing a Simple Data Analysis using MS-Excel Function01:17

Performing a Simple Data Analysis using MS-Excel Function

995
Microsoft Excel offers a suite of functions and tools ideal for statistical analysis, making it accessible to students and researchers. This article outlines fundamental Excel functions pivotal for data analysis.
SUM: This function calculates the total sum of a range of values. It's the foundation for aggregating data, essential for determining overall trends and totals in datasets.
AVERAGE: It computes the mean value of a given set of numbers, providing a quick insight into the central...
995
Constant Volume Calorimetry02:41

Constant Volume Calorimetry

30.7K
Calorimeters are useful to determine the heat released or absorbed by a chemical reaction. Coffee cup calorimeters are designed to operate at constant (atmospheric) pressure and are convenient to measure heat flow (or enthalpy change) accompanying processes that occur in solution at constant pressure. A different type of calorimeter that operates at constant volume, colloquially known as a bomb calorimeter, is used to measure the energy produced by reactions that yield large amounts of heat and...
30.7K
Volume of Distribution01:20

Volume of Distribution

1.2K
The apparent volume of distribution (Vd) is a crucial pharmacokinetic parameter representing the hypothetical body fluid volume into which a drug disperses. It is calculated based on the total amount of drug in the body (estimated from the administered dose and bioavailability) divided by the plasma drug concentration. The total amount of drug in the body does not directly refer to the dose given but is derived by accounting for absorption, distribution, metabolism, and excretion processes.
1.2K

You might also read

Related Articles

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

Sort by
Same author

Corrigendum to "Prospective association between descriptive accelerometer-derived physical behaviour metrics and cardiometabolic risk indicators in Dutch children: The ABCD study" [J Exerc Sci Fitness 24 (2026) 200431].

Journal of exercise science and fitness·2026
Same author

Evaluating School-Based Obesity Prevention Interventions in 6- to 12-Year-Old Children: A Scoping Review of All Reported Outcomes and Expert Consultation.

Obesity reviews : an official journal of the International Association for the Study of Obesity·2026
Same author

Promoting active outdoor play and healthy dietary behaviours through the co-creation of supporting physical and social environments for and with primary school-aged children living in underserved neighbourhoods in Europe: the protocol of the B-Challenged project.

BMJ open·2026
Same author

Your project or our project? Evaluating the participatory development of an adolescent healthy sleep intervention.

BMC public health·2025
Same author

Exploring the Multivariate Association Between Physical Fitness and Cardiometabolic Risk in Children and Adolescents.

Pediatric exercise science·2025
Same author

Tracking of device-measured sedentary time, cardiorespiratory fitness, and cardiometabolic risk factors from childhood to young adulthood.

American journal of preventive cardiology·2025

Related Experiment Video

Updated: Jan 27, 2026

Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance
04:58

Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance

Published on: December 13, 2024

4.1K

From Total Volume to Sequence Maps: Sophisticated Accelerometer Data Analysis.

Mai J Chinapaw1, Xinhui Wang1,2, Lars Bo Andersen3

  • 1Department of Public and Occupational Health and Amsterdam Public Health Research Institute, VU University Medical Center, Amsterdam, THE NETHERLANDS.

Medicine and Science in Sports and Exercise
|March 19, 2019
PubMed
Summary

New algorithms analyze physical activity (PA) and sedentary behavior (SB) patterns from accelerometer data. Understanding how PA and SB accumulate throughout the day is crucial for health outcomes.

More Related Videos

High-Throughput Analysis of Optical Mapping Data Using ElectroMap
07:36

High-Throughput Analysis of Optical Mapping Data Using ElectroMap

Published on: June 4, 2019

10.1K
Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens
09:14

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

Published on: June 28, 2018

7.5K

Related Experiment Videos

Last Updated: Jan 27, 2026

Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance
04:58

Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance

Published on: December 13, 2024

4.1K
High-Throughput Analysis of Optical Mapping Data Using ElectroMap
07:36

High-Throughput Analysis of Optical Mapping Data Using ElectroMap

Published on: June 4, 2019

10.1K
Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens
09:14

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

Published on: June 28, 2018

7.5K

Area of Science:

  • Biomedical Engineering
  • Epidemiology
  • Public Health

Background:

  • Epidemiological studies traditionally focus on the total volume of physical activity (PA) and sedentary behavior (SB).
  • Accumulation patterns of PA and SB throughout the day may significantly influence health outcomes, independent of total volume.
  • Existing methods lack the granularity to capture these sequential patterns.

Purpose of the Study:

  • To develop a sophisticated algorithm for translating accelerometer data into detailed sequence maps.
  • To analyze how physical activity and sedentary behavior are accumulated throughout the day.
  • To create a foundation for future research linking behavioral patterns to health.

Main Methods:

  • A novel algorithm was developed to convert raw accelerometer counts into sequence maps.
  • Behavioral states were defined by intensity (SB, light, moderate, vigorous) and duration (sporadic vs. bouts).
  • Hierarchical cluster analysis identified distinct groups of children based on their behavioral sequence maps.

Main Results:

  • Seven distinct clusters of children with similar PA and SB sequence maps were identified.
  • The largest clusters included an 'average' group (33%) and a 'SB and PA bouters' group (31%).
  • Other clusters represented variations in sporadic activity and bout accumulation, including 'light activity breakers' (26%).

Conclusions:

  • The developed algorithm represents a significant advancement in analyzing accelerometer data.
  • It enables more sophisticated examination of PA and SB accumulation patterns.
  • Future research should investigate the association between these identified patterns and health outcomes.