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

Load-frequency control01:28

Load-frequency control

165
Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...
165
Biasing of FET01:22

Biasing of FET

278
Biasing a Junction Field Effect Transistor (JFET) is crucial for setting operational parameters and ensuring efficient functioning in electronic circuits. JFETs are characterized by using a single carrier type in N-channel or P-channel configurations, where the channel is surrounded by PN junctions. These junctions are central to the device's ability to control current flow.
In an N-channel JFET, the structure consists of N-type material forming the channel on a P-type substrate, with the...
278
Mass Analyzers: Common Types01:19

Mass Analyzers: Common Types

612
The quadrupole mass analyzer consists of four cylindrical metal rods arranged in a diamond carrying a DC voltage and a radio-frequency AC voltage. The motion of ions through the quadrupole depends on the field strength, causing only ions of a certain m/z to resonate successfully and strike the detector at a given field strength. Though the transmission rate for these analyzers is high, the exact elemental composition of the sample is not determined because of low resolution; however, they are...
612
Bandpass Sampling01:17

Bandpass Sampling

181
In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2....
181
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

197
Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
197
Time and frequency -Domain Interpretation of PI Control01:27

Time and frequency -Domain Interpretation of PI Control

129
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...
129

You might also read

Related Articles

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

Sort by
Same author

In vivo evolution of tigecycline resistance in ST540 carbapenem-resistant Acinetobacter baumannii: Mechanisms and global epidemiological perspective.

International journal of antimicrobial agents·2026
Same author

Endogenous Fe-N co-doped biochar for persulfate activation: Synergistic enhancement of persulfate adsorption by porous structure and p-d orbital coupling.

Bioresource technology·2026
Same author

625 mJ, 1 kHz picosecond pulsed laser amplifier based on cascaded zig-zag slabs.

Optics express·2026
Same author

Distribution patterns and ecological networks of pathogenic microorganisms in a tropical urban river: insights from the Mirongo River, Tanzania.

Environmental pollution (Barking, Essex : 1987)·2026
Same author

Comparative between eravacycline and best available therapy in carbapenem-resistant Acinetobacter baumannii HAP/VAP in China: a retrospective real-world multicenter cohort study.

International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases·2026
Same author

Environmental Behavior of 2,4,6-Trichlorophenol in the Sediment-Overlying Water System with the Presence of Tubificid Worms.

Toxics·2026

Related Experiment Video

Updated: Jul 4, 2025

Real-Time DC-dynamic Biasing Method for Switching Time Improvement in Severely Underdamped Fringing-field Electrostatic MEMS Actuators
11:44

Real-Time DC-dynamic Biasing Method for Switching Time Improvement in Severely Underdamped Fringing-field Electrostatic MEMS Actuators

Published on: August 15, 2014

10.3K

Iontronic Dynamic Sensor with Broad Bandwidth and Flat Frequency Response Using Controlled Preloading Strategy.

Haoyu Guo1, Jianxing Liu1, Haiyang Liu1

  • 1State Key Lab for Strength and Vibration of Mechanical Structures, Soft Machines Lab, Department of Engineering Mechanics, Xi'an Jiaotong University, Xi'an 710049, China.

ACS Nano
|February 5, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a novel hydrogel sensor for dynamic signals, enhancing human-machine interaction. The advanced soft mechanical sensor records complex sounds with high fidelity for wearable electronics.

Keywords:
broad bandwidthdynamic signaliontronic sensingpreloadingsoft mechanical sensor

More Related Videos

Design and Characterization Methodology for Efficient Wide Range Tunable MEMS Filters
15:25

Design and Characterization Methodology for Efficient Wide Range Tunable MEMS Filters

Published on: February 4, 2018

6.1K
Frequency Mixing Magnetic Detection Scanner for Imaging Magnetic Particles in Planar Samples
07:01

Frequency Mixing Magnetic Detection Scanner for Imaging Magnetic Particles in Planar Samples

Published on: June 9, 2016

9.6K

Related Experiment Videos

Last Updated: Jul 4, 2025

Real-Time DC-dynamic Biasing Method for Switching Time Improvement in Severely Underdamped Fringing-field Electrostatic MEMS Actuators
11:44

Real-Time DC-dynamic Biasing Method for Switching Time Improvement in Severely Underdamped Fringing-field Electrostatic MEMS Actuators

Published on: August 15, 2014

10.3K
Design and Characterization Methodology for Efficient Wide Range Tunable MEMS Filters
15:25

Design and Characterization Methodology for Efficient Wide Range Tunable MEMS Filters

Published on: February 4, 2018

6.1K
Frequency Mixing Magnetic Detection Scanner for Imaging Magnetic Particles in Planar Samples
07:01

Frequency Mixing Magnetic Detection Scanner for Imaging Magnetic Particles in Planar Samples

Published on: June 9, 2016

9.6K

Area of Science:

  • Materials Science
  • Biomedical Engineering
  • Robotics

Background:

  • Existing soft mechanical sensors primarily detect quasi-static signals like pressure, limiting their use in advanced wearable electronics.
  • Rapid progress in human-machine interaction and voice biometrics necessitates soft sensors capable of capturing complex dynamic signals.
  • Current sensors lack the bandwidth and sensitivity required for emerging applications in voice control and biometrics.

Purpose of the Study:

  • To develop a hydrogel-based soft mechanical sensor for recording a wide range of dynamic human signals.
  • To enhance sensor performance by integrating a preloading design strategy with an iontronic sensing mechanism.
  • To enable high-fidelity recording of dynamic signals for applications in human-machine interaction and wearable technology.

Main Methods:

  • A hydrogel-based sensor was designed incorporating a preloading strategy and an iontronic sensing mechanism.
  • The sensor's working bandwidth was significantly increased through microstructured hydrogel parameter tuning and preload adjustments.
  • The sensor's performance was evaluated by recording various sound types, including instrumental music and human voice commands.

Main Results:

  • The proposed sensor achieved a working bandwidth up to 1000 Hz, two orders of magnitude greater than existing soft sensors.
  • The sensor demonstrated high sensitivity (-23 dB), surpassing that of common commercial microphones.
  • Precise tuning of amplitude-frequency characteristics was achieved by adjusting preloads and hydrogel parameters, enabling high-fidelity sound recording.

Conclusions:

  • The developed hydrogel sensor effectively records dynamic signals with superior bandwidth and sensitivity.
  • The sensor's tunable characteristics make it suitable for diverse applications, including voice user interfaces in human-machine interactions.
  • Demonstrated use in a skin-mountable configuration for voice-controlled devices highlights its potential in advanced wearable electronics and interactive systems.