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

Holter Monitor: 24-Hour Monitoring01:23

Holter Monitor: 24-Hour Monitoring

Holter monitoring is a continuous electrocardiography (ECG) recording that tracks the heart's electrical activity over an extended period, generally 24 to 48 hours. This noninvasive diagnostic tool detects irregular heart rhythms that may not be captured during a standard ECG performed in a clinical setting.DeviceThe Holter monitor is a portable, small device connected to several electrodes on the patient's chest. These electrodes detect the heart's electrical signals and transmit them to the...
Pulse rhythm01:30

Pulse rhythm

Pulse rhythm refers to the pattern of pulsations within specific intervals, offering valuable insights into the regularity or irregularity of the heart's beats as observed through the pattern of pulsation within specific intervals. A regular pulse exhibits a consistent heart rate with uniform waveforms and pulsation force, variations of which can be classified as normal, weak, or bounding.
Conversely, an irregular pulse pattern is termed dysrhythmia, stemming from disruptions in cardiac muscle...

You might also read

Related Articles

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

Sort by
Same author

The Physical Activity Assessment Using Wearable Sensors (PAAWS) Dataset: Labeled Laboratory and Free-living Accelerometer Data.

Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies·2026
Same author

Towards Practical, Best Practice Video Annotation to Support Human Activity Recognition.

Annotation of real-world data for artificial intelligence systems : 9th international workshop, ARDUOUS 2025, Bologna Italy, October 25-26, 2025, proceedings. International Workshop on Annotation of Real-World Data for Artificial Intell...·2026
Same author

Toward AI-Driven Precision Measurement of Cognition, Behavior, and Psychological Function in Aging and Alzheimer's Disease and Alzheimer's Disease-Related Dementias.

The journals of gerontology. Series B, Psychological sciences and social sciences·2025
Same author

An Examination of Efficiency during Walking in Children and Adults.

Pediatric exercise science·2025
Same author

Feasibility and Costs of Monitoring Physical Activity in Young Children Using the Caltrac Accelerometer.

Pediatric exercise science·2025
Same author

Validity of the Caltrac Accelerometer in Estimating Energy Expenditure and Activity in Children and Adults.

Pediatric exercise science·2024

Related Experiment Video

Updated: May 7, 2026

Home-Based Monitor for Gait and Activity Analysis
07:24

Home-Based Monitor for Gait and Activity Analysis

Published on: August 8, 2019

ActiGraph™ activity monitors: "the firmware effect".

Dinesh John1, Jeffer Sasaki, Amanda Hickey

  • 11Northeastern University, Boston, MA; and 2University of Massachusetts, Amherst, MA.

Medicine and Science in Sports and Exercise
|September 18, 2013
PubMed
Summary
This summary is machine-generated.

Firmware version 1.1.0 for ActiGraph monitors showed higher activity counts, especially during sedentary tasks. This highlights the need for rigorous testing of new firmware to ensure consistent data comparability.

More Related Videos

Assessment of Physical Activity Intensity with Accelerometers and Oxygen Consumption
08:45

Assessment of Physical Activity Intensity with Accelerometers and Oxygen Consumption

Published on: June 20, 2025

A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program
04:24

A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program

Published on: April 19, 2019

Related Experiment Videos

Last Updated: May 7, 2026

Home-Based Monitor for Gait and Activity Analysis
07:24

Home-Based Monitor for Gait and Activity Analysis

Published on: August 8, 2019

Assessment of Physical Activity Intensity with Accelerometers and Oxygen Consumption
08:45

Assessment of Physical Activity Intensity with Accelerometers and Oxygen Consumption

Published on: June 20, 2025

A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program
04:24

A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program

Published on: April 19, 2019

Area of Science:

  • Wearable sensor technology
  • Biomedical engineering
  • Physical activity monitoring

Background:

  • ActiGraph devices are widely used for objective physical activity assessment.
  • Variations in device firmware can potentially impact data accuracy.
  • Ensuring consistency across firmware versions is crucial for reliable research findings.

Purpose of the Study:

  • To evaluate the impact of different ActiGraph firmware versions on activity count data.
  • To compare firmware performance across laboratory, free-living, and mechanical shaker tests.
  • To identify potential discrepancies in data output due to firmware variations.

Main Methods:

  • Compared activity counts from GT3X and GT1M devices with various firmware versions.
  • Participants engaged in treadmill activities and simulated free-living tasks.
  • Mechanical shaker tests were conducted at multiple frequencies.
  • Statistical analyses included ANOVA and post hoc pairwise comparisons.

Main Results:

  • Firmware version 1.1.0 on GT1M devices yielded significantly higher vertical counts during slow walking compared to version 1.3.0.
  • Mechanical shaker tests indicated significant differences in vertical and lateral counts across firmware versions.
  • Firmware 1.1.0 produced the highest vertical counts during free-living activities, though not statistically significant.

Conclusions:

  • Firmware version 1.1.0 demonstrated increased sensitivity to low-frequency sedentary activities, leading to higher counts.
  • ActiGraph should implement both human and mechanical shaker testing before firmware releases.
  • Verification of output comparability between new and previous firmware versions is recommended.