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

IoT-Simulated Digital Twin with AI Traffic Signal Control for Real-Time Traffic Optimization in SUMO.

Sensors (Basel, Switzerland)·2026
Same author

SpiKon-E: Hybrid Soft Artificial Muscle Control Using Hardware Spiking Neural Network.

Biomimetics (Basel, Switzerland)·2025
Same author

Optimizing Urban Traffic Efficiency and Safety via V2X: A Simulation Study Using the MOSAIC Platform.

Sensors (Basel, Switzerland)·2025
Same author

Vehicular Sensing for Improved Urban Mobility.

Sensors (Basel, Switzerland)·2024
Same author

Neuromorphic Sensor Based on Force-Sensing Resistors.

Biomimetics (Basel, Switzerland)·2024
Same author

Control Architecture for Connected Vehicle Platoons: From Sensor Data to Controller Design Using Vehicle-to-Everything Communication.

Sensors (Basel, Switzerland)·2023
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: Nov 7, 2025

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision
08:15

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

Published on: March 28, 2025

903

Adaptive SNN for Anthropomorphic Finger Control.

Mircea Hulea1, George Iulian Uleru1, Constantin Florin Caruntu1

  • 1Faculty of Automatic Control and Computer Engineering, Gheorghe Asachi Technical University of Iasi, 700050 Iasi, Romania.

Sensors (Basel, Switzerland)
|April 30, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces an adaptive spiking neural network (SNN) for controlling robotic hands. The bio-inspired system learns to adapt hand motions unsupervised, mimicking human dexterity.

Keywords:
Hebbian learninganthropomorphic fingerneuromorphic hardwarespiking neural networks

More Related Videos

The Bionic Clicker Mark I & II
08:23

The Bionic Clicker Mark I & II

Published on: August 14, 2017

16.6K
Author Spotlight: Enhancing Grasping Abilities for Hemiplegic Patients with Flexible Robotic Limbs
03:55

Author Spotlight: Enhancing Grasping Abilities for Hemiplegic Patients with Flexible Robotic Limbs

Published on: October 27, 2023

2.4K

Related Experiment Videos

Last Updated: Nov 7, 2025

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision
08:15

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

Published on: March 28, 2025

903
The Bionic Clicker Mark I & II
08:23

The Bionic Clicker Mark I & II

Published on: August 14, 2017

16.6K
Author Spotlight: Enhancing Grasping Abilities for Hemiplegic Patients with Flexible Robotic Limbs
03:55

Author Spotlight: Enhancing Grasping Abilities for Hemiplegic Patients with Flexible Robotic Limbs

Published on: October 27, 2023

2.4K

Area of Science:

  • Robotics
  • Neuroscience
  • Artificial Intelligence

Background:

  • Anthropomorphic hands require biologically plausible control for smooth, human-like motion.
  • Adaptability is key for robotic systems to learn and execute complex movements.
  • Spiking neural networks (SNNs) offer a bio-inspired approach to artificial control systems.

Purpose of the Study:

  • To present a simple, adaptive SNN implemented in analog hardware for controlling robotic finger motion.
  • To enable unsupervised learning of motion control using Hebbian learning mechanisms.
  • To demonstrate a bio-inspired control system for anthropomorphic robots.

Main Methods:

  • Developed an adaptive SNN using analog hardware and Hebbian learning.
  • Utilized shape memory alloy actuators and neuromorphic sensors for robotic finger control.
  • Implemented angle-specific neural paths to learn motion intervals and external force interactions.

Main Results:

  • The adaptive SNN successfully trained to rotate a robotic finger's metacarpophalangeal joint towards target angles.
  • The system learned to stop the finger within specific angle intervals based on learned associations.
  • Unsupervised learning allowed the robotic finger to adapt its motion control without external guidance.

Conclusions:

  • The proposed adaptive SNN provides a biologically plausible control unit for anthropomorphic robots.
  • This approach enables robots to learn motions unsupervised, enhancing adaptability and dexterity.
  • The system demonstrates the potential for advanced robotic control inspired by neural principles.