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

You might also read

Related Articles

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

Sort by
Same author

Towards the Simulation of a Realistic Large-Scale Spiking Network on a Desktop Multi-GPU System.

Bioengineering (Basel, Switzerland)·2022
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Jun 10, 2025

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

2.6K

Artificial Intelligence for the Evaluation of Postures Using Radar Technology: A Case Study.

Davide De Vittorio1, Antonio Barili1, Giovanni Danese1

  • 1Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy.

Sensors (Basel, Switzerland)
|October 16, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a privacy-preserving radar system using artificial intelligence (AI) to monitor daily activities and detect postures. Long short-term memory (LSTM) and GRU networks show promise for embedded systems monitoring elderly individuals.

Keywords:
LSTMartificial intelligenceembedded systemsfall detectionposture analysisradar technology

More Related Videos

Author Spotlight: Assessing Brain Activity in Robotic-Assisted Lower Limb Rehabilitation Using fNIRS
05:25

Author Spotlight: Assessing Brain Activity in Robotic-Assisted Lower Limb Rehabilitation Using fNIRS

Published on: June 7, 2024

1.2K
A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation
11:06

A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation

Published on: April 12, 2016

10.4K

Related Experiment Videos

Last Updated: Jun 10, 2025

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

2.6K
Author Spotlight: Assessing Brain Activity in Robotic-Assisted Lower Limb Rehabilitation Using fNIRS
05:25

Author Spotlight: Assessing Brain Activity in Robotic-Assisted Lower Limb Rehabilitation Using fNIRS

Published on: June 7, 2024

1.2K
A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation
11:06

A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation

Published on: April 12, 2016

10.4K

Area of Science:

  • Biomedical Engineering
  • Artificial Intelligence
  • Signal Processing

Background:

  • Aging population necessitates advanced health monitoring solutions.
  • Need for unobtrusive, privacy-preserving technologies to support independent living.
  • Radar sensors offer a potential method for activity and posture analysis in domestic settings.

Purpose of the Study:

  • To develop and evaluate an AI-based system using millimeter-wave radar for posture detection.
  • To assess the performance of various algorithms and neural networks for posture recognition.
  • To identify suitable AI models for implementation in embedded monitoring systems.

Main Methods:

  • Utilized millimeter-wave radar technology combined with artificial intelligence (AI).
  • Evaluated multiple algorithms and neural network methodologies, including Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU).
  • Conducted experimental acquisitions with healthy subjects to gather posture data.

Main Results:

  • All evaluated methods demonstrated high performance in posture detection.
  • LSTM and GRU networks exhibited the most consistent results.
  • These models maintained reduced computational complexity, suitable for embedded systems.

Conclusions:

  • The developed radar-based AI system effectively detects various postures.
  • LSTM and GRU are strong candidates for embedded systems due to their performance and efficiency.
  • This technology can enhance the independence and safety of frail individuals.