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

Measuring Acceleration Due to Gravity01:12

Measuring Acceleration Due to Gravity

1.1K
Consider a coffee mug hanging on a hook in a pantry. If the mug gets knocked, it oscillates back and forth like a pendulum until the oscillations die out.
A simple pendulum can be described as a point mass and a string. Meanwhile, a physical pendulum is any object whose oscillations are similar to a simple pendulum, but cannot be modeled as a point mass on a string because its mass is distributed over a larger area. The behavior of a physical pendulum can be modeled using the principles of...
1.1K
Relative Motion Analysis - Acceleration01:10

Relative Motion Analysis - Acceleration

749
A slider-crank mechanism converts rotational motion from the crank into linear motion of the slider or vice versa. This mechanism consists of three main parts: the crank, the connecting rod, and the slider. The movement of the slider-crank is an example of general plane motion as the fluctuating angle between the crank and the connecting rod. Consider a segment AB where point A is at the end of the slider and point B is on the diametrically opposite end to point A, on a crack. The variance in...
749
Types of Global Positioning System Surveys01:30

Types of Global Positioning System Surveys

262
GPS surveying methods vary in application, accuracy, and data collection techniques, catering to diverse surveying and mapping needs. Static GPS, kinematic GPS, and real-time kinematic (RTK) surveying are widely used. Each technique offers distinct advantages.Static GPS involves placing one receiver at a known reference point and another at the target point. It collects exact positional data by observing multiple satellite ranges over an extended period, achieving centimeter-level accuracy for...
262
Relative Motion Analysis using Rotating Axes - Acceleration01:22

Relative Motion Analysis using Rotating Axes - Acceleration

695
Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame. The absolute velocity of point B is determined by adding the absolute velocity of point A, the relative velocity of point B in the rotating frame, and the effects caused by the angular velocity within the rotating frame.
Time differentiation is...
695
Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device01:30

Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device

320
Surveyors use Global Positioning System (GPS) technology to measure the precise location and elevation of points on Earth. In a recent survey, GPS receivers were used to determine the coordinates and elevations of two park monuments. The process involved careful mission planning, data collection, and correction to ensure accuracy. The survey began with mission planning to identify optimal satellite visibility and minimize Position Dilution of Precision (PDOP). A geodetic control point...
320
Field Application of Global Positioning System01:28

Field Application of Global Positioning System

250
The Global Positioning System (GPS) has become an indispensable tool in fieldwork, offering unparalleled precision and efficiency for surveying, navigation, and infrastructure development. By harnessing signals from a constellation of satellites, GPS receivers determine the location of objects with remarkable speed and accuracy, often completing calculations within a second.Advantages of Modern GPS TechnologyContemporary GPS receivers are designed to meet the practical demands of field...
250

You might also read

Related Articles

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

Sort by
Same author

A global and interoperable dataset of linguistic distributions derived from the Atlas of the World's Languages.

Scientific data·2025
Same author

Personalised, GIS-based counselling to promote habitual walking in mobility-limited and chronically ill older adults: protocol of the MOBITEC-Routes randomised controlled trial.

BMC geriatrics·2025
Same author

Avian spring migration at the east Adriatic coast: coastal and sea-crossing dynamics of intensity, timing, and flight directions.

Movement ecology·2025
Same author

Distance from home and working memory: daily associations varying by neighborhood environments in community-dwelling older adults.

European journal of ageing·2025
Same author

Modeling the effect of climate change on the distribution of plant communities in Zayandeh-Rud basin, Iran.

Environmental monitoring and assessment·2025
Same author

Evaluation of early warning signals for soil erosion using remote sensing indices in northeastern Iran.

Scientific reports·2025

Related Experiment Video

Updated: Dec 30, 2025

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
06:49

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Published on: December 11, 2015

9.3K

Using Accelerometer and GPS Data for Real-Life Physical Activity Type Detection.

Hoda Allahbakhshi1, Lindsey Conrow1,2, Babak Naimi3

  • 1Department of Geography, Geographic Information Systems Unit, University of Zurich (UZH), Winterthurerstrasse 190, 8057 Zurich, Switzerland.

Sensors (Basel, Switzerland)
|January 25, 2020
PubMed
Summary
This summary is machine-generated.

Adding global positioning system (GPS) sensor data to accelerometer data improves physical activity (PA) detection, especially when using combined training data. A knee-mounted sensor configuration offers reliable accuracy for real-life PA classification.

Keywords:
GISGPSphysical activity typereal-life

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

416
Home-Based Monitor for Gait and Activity Analysis
07:24

Home-Based Monitor for Gait and Activity Analysis

Published on: August 8, 2019

7.2K

Related Experiment Videos

Last Updated: Dec 30, 2025

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
06:49

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Published on: December 11, 2015

9.3K
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

416
Home-Based Monitor for Gait and Activity Analysis
07:24

Home-Based Monitor for Gait and Activity Analysis

Published on: August 8, 2019

7.2K

Area of Science:

  • Sports Science
  • Wearable Technology
  • Biomedical Engineering

Background:

  • Accurate physical activity (PA) detection is crucial for health monitoring and research.
  • Wearable sensors like accelerometers are widely used, but their effectiveness in real-world settings can be limited.
  • Integrating Global Positioning System (GPS) data offers potential to enhance PA classification accuracy.

Purpose of the Study:

  • To investigate the utility of GPS sensor data in improving real-life physical activity type detection.
  • To compare the performance of different sensor placements and model configurations for PA classification.
  • To assess the transferability of trained models to real-world activity scenarios.

Main Methods:

  • Thirty-three participants engaged in semi-structured and real-life physical activities while wearing devices with GPS and accelerometer sensors at five body positions.
  • Random Forest (RF) models were trained using data from all sensors or individual sensor positions.
  • Models were evaluated under two scenarios: semi-structured data only (Scenario 1) and combined semi-structured and real-life data (Scenario 2).

Main Results:

  • Incorporating GPS features (speed, elevation difference) alongside accelerometer data significantly improved PA classification, particularly for walking activities.
  • Models trained with combined data (Scenario 2) demonstrated strong transferability to real-life activity data.
  • Individual sensor models, specifically those using knee-mounted sensors, achieved comparable classification performance (over 80%) to general models.

Conclusions:

  • Global positioning system (GPS) data enhances real-life physical activity type classification when integrated into training datasets.
  • A minimal device configuration using a knee-mounted sensor provides reliable accuracy for detecting diverse real-life physical activities.
  • The findings support the use of GPS-enhanced wearable systems for more accurate and context-aware physical activity monitoring.