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

Open and closed-loop control systems01:17

Open and closed-loop control systems

1.2K
Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
An open-loop control system operates without feedback from the output. It consists of two primary elements: the controller and the controlled process. The controller receives an input signal...
1.2K
PD Controller: Design01:26

PD Controller: Design

425
In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
425
PI Controller: Design01:24

PI Controller: Design

706
Proportional Integral (PI) controllers are a fundamental component in modern control systems, widely used to enhance performance and mitigate steady-state errors. They are particularly effective in applications such as automatic brightness adjustment on smartphones, where they excel at mitigating steady-state errors for step-function inputs. Unlike PD controllers, which require time-varying errors to function optimally, PI controllers leverage their integral component to address residual...
706
Feedback control systems01:26

Feedback control systems

533
Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
533
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

215
Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
Consider the example of control of motor torque. Initially, a positive...
215
Time and frequency -Domain Interpretation of PI Control01:27

Time and frequency -Domain Interpretation of PI Control

246
Proportional-Integral (PI) controllers are essential in many control systems to improve stability and performance. They are commonly used in everyday devices like thermostats to enhance system damping and reduce steady-state error. When the zero in the controller's transfer function is optimally placed, the system benefits significantly in terms of stability and accuracy.
Acting as a low-pass filter, the PI controller slows the system's response and extends settling times. This requires...
246

You might also read

Related Articles

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

Sort by
Same author

Sound-evoked auditory neurophysiological signals are a window into prodromal functional differences in a preclinical model of Alzheimer's disease.

Scientific reports·2026
Same author

Facial micro-movements as a proxy of increasingly erratic heart rate variability while experiencing pressure pain.

Frontiers in neuroscience·2026
Same author

IMAGINE Personalities: Augmenting Digital Character Workflows Using Motion Capture, Wearable Sensors, and Live Coding.

Sensors (Basel, Switzerland)·2025
Same author

Setting Up Our Lab-in-a-Box: Paving the Road Towards Remote Data Collection for Scalable Personalized Biometrics.

Journal of personalized medicine·2025
Same author

Editorial: Autism: the movement (sensing) perspective a decade later.

Frontiers in integrative neuroscience·2025
Same author

Hidden social and emotional competencies in autism spectrum disorders captured through the digital lens.

Frontiers in psychiatry·2025
Same journal

A Video Protocol of a Randomized Controlled Clinical Trial - Electrochemotherapy of Cutaneous Metastases with Reduced Dose Bleomycin (BLESS Trial).

Journal of visualized experiments : JoVE·2026
Same journal

A Standardized Ex Vivo Porcine Oromucosal Model for Evaluating Peptide Fluxes.

Journal of visualized experiments : JoVE·2026
Same journal

Lightweight English Text Classification with Deep Learning Based on Complex System Theory.

Journal of visualized experiments : JoVE·2026
Same journal

Integrating Artificial Intelligence-Assisted Translation Support into English Courses: Effects on Translation Accuracy, Perceived Stress, and Anxiety.

Journal of visualized experiments : JoVE·2026
Same journal

A Toxin-Based Counter-Selection System for Markerless Gene Deletion and High-Density Tn5 Transposon Mutagenesis in Pectobacterium brasiliense.

Journal of visualized experiments : JoVE·2026
Same journal

Seamless Multimodal Human-Robot Communication: Integration Techniques in Human-Computer Interaction.

Journal of visualized experiments : JoVE·2026
See all related articles

Related Experiment Video

Updated: Nov 4, 2025

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

4.8K

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface.

Vilelmini Kalampratsidou1, Steven Kemper2, Elizabeth B Torres3

  • 1Center for Cognitive Science, Rutgers University; Department of Computer Science, Rutgers University; vilelmini.kalabratsidou@gmail.com.

Journal of Visualized Experiments : Jove
|May 24, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a novel co-adaptive interface for sensory augmentation, enabling real-time steering of one agent's body-heart-brain rhythms by another through biofeedback. This advances human-computer interaction and understanding of somatic-sensory-motor control.

More Related Videos

The Muscle Cuff Regenerative Peripheral Nerve Interface for the Amplification of Intact Peripheral Nerve Signals
07:30

The Muscle Cuff Regenerative Peripheral Nerve Interface for the Amplification of Intact Peripheral Nerve Signals

Published on: January 13, 2022

2.2K
An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
10:51

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

Published on: March 10, 2011

14.0K

Related Experiment Videos

Last Updated: Nov 4, 2025

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

4.8K
The Muscle Cuff Regenerative Peripheral Nerve Interface for the Amplification of Intact Peripheral Nerve Signals
07:30

The Muscle Cuff Regenerative Peripheral Nerve Interface for the Amplification of Intact Peripheral Nerve Signals

Published on: January 13, 2022

2.2K
An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
10:51

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

Published on: March 10, 2011

14.0K

Area of Science:

  • Neuroscience
  • Human-Computer Interaction
  • Bioengineering

Background:

  • Sensory substitution and augmentation typically focus on external goals using central nervous system (CNS) signals.
  • Protocols for updating external signals based on self-generated motion in interactive bodies are less common.
  • Combining body-heart-brain biorhythms for dyadic steering presents challenges due to multimodal bio-signal complexity.

Purpose of the Study:

  • To develop a co-adaptive interface that integrates and updates bio-signals from interacting agents.
  • To enable real-time steering of one agent's physiological and motor outputs by another.
  • To explore new methods for measuring external input's influence on internal somatic-sensory-motor control.

Main Methods:

  • Utilized wearable biosensors to capture multimodal bio-signals (kinematics, heart rate).
  • Developed a co-adaptive interface to parameterize stochastic bio-signals and sonify output.
  • Implemented a feedback loop providing re-parameterized visuo/audio-kinesthetic reafferent input.

Main Results:

  • Demonstrated the interface's functionality in dyadic interactions between two humans.
  • Showcased the system's effectiveness in human-avatar interactions in near real-time.
  • Successfully updated efferent somatic-motor output based on biosensor data.

Conclusions:

  • The co-adaptive interface offers a novel approach to sensory augmentation and dyadic interaction.
  • This method facilitates the real-time exchange and steering of body-heart-brain biorhythms.
  • The study opens new avenues for investigating the interplay between external stimuli and internal motor control.