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

Spherical and Cylindrical Capacitor01:26

Spherical and Cylindrical Capacitor

A spherical capacitor consists of two concentric conducting spherical shells of radii R1 (inner shell) and R2 (outer shell). The shells have equal and opposite charges of +Q and −Q, respectively. For an isolated conducting spherical capacitor, the radius of the outer shell can be considered to be infinite.
Conventionally, considering the symmetry, the electric field between the concentric shells of a spherical capacitor is directed radially outward. The magnitude of the field, calculated by...
Design Example: Capacitance Multiplier Circuit01:20

Design Example: Capacitance Multiplier Circuit

In integrated circuit technology, a capacitance multiplier is often utilized to produce a larger capacitance value when a small physical capacitance falls short. This is achieved by a circuit that multiplies capacitance values by a factor of up to 1000, such that a 10-pF capacitor can replicate the performance of a 100-nF capacitor.
The circuit illustrated in Figure 1 below incorporates two op-amps, with the first operating as a voltage follower and the second acting as an inverting amplifier.

You might also read

Related Articles

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

Sort by
Same author

Embedding textile capacitive sensing into smart wearables as a versatile solution for human motion capturing.

Scientific reports·2024
Same author

Regulation of microtubule dynamics by DIAPH3 influences amoeboid tumor cell mechanics and sensitivity to taxanes.

Scientific reports·2015
Same author

Aberrant Functional Connectivity Architecture in Alzheimer's Disease and Mild Cognitive Impairment: A Whole-Brain, Data-Driven Analysis.

BioMed research international·2015
Same author

Alternative NF-κB Isoforms in the Drosophila Neuromuscular Junction and Brain.

PloS one·2015
Same author

Grape seed proanthocyanidin protects liver against ischemia/reperfusion injury by attenuating endoplasmic reticulum stress.

World journal of gastroenterology·2015
Same author

Serum Levels of Progranulin Are Closely Associated with Microvascular Complication in Type 2 Diabetes.

Disease markers·2015

Related Experiment Video

Updated: Jun 23, 2026

Origami Inspired Self-assembly of Patterned and Reconfigurable Particles
12:33

Origami Inspired Self-assembly of Patterned and Reconfigurable Particles

Published on: February 4, 2013

21.7K

Origami single-end capacitive sensing for continuous shape estimation of morphing structures.

Lala Ray1, Daniel Geißler2, Bo Zhou2,3

  • 1German Research Center for Artificial Intelligence (DFKI), Embedded Intelligence, Kaiserslautern, Germany. lala_shakti_swarup.ray@dfki.de.

Scientific Reports
|July 29, 2024
PubMed
Summary
This summary is machine-generated.

We developed FxC, a novel morphing capacitive sensing method using origami structures for shape tracking. This approach accurately detects structural motion by analyzing changes in single-end capacitive sensors embedded in origami, achieving up to 95% R-squared correlation.

More Related Videos

Folding and Characterization of a Bio-responsive Robot from DNA Origami
07:59

Folding and Characterization of a Bio-responsive Robot from DNA Origami

Published on: December 3, 2015

14.5K
Author Spotlight: Microfluidic Channel-Based Soft Electrodes and Their Application in Capacitive Pressure Sensing
05:57

Author Spotlight: Microfluidic Channel-Based Soft Electrodes and Their Application in Capacitive Pressure Sensing

Published on: March 17, 2023

2.1K

Related Experiment Videos

Last Updated: Jun 23, 2026

Origami Inspired Self-assembly of Patterned and Reconfigurable Particles
12:33

Origami Inspired Self-assembly of Patterned and Reconfigurable Particles

Published on: February 4, 2013

21.7K
Folding and Characterization of a Bio-responsive Robot from DNA Origami
07:59

Folding and Characterization of a Bio-responsive Robot from DNA Origami

Published on: December 3, 2015

14.5K
Author Spotlight: Microfluidic Channel-Based Soft Electrodes and Their Application in Capacitive Pressure Sensing
05:57

Author Spotlight: Microfluidic Channel-Based Soft Electrodes and Their Application in Capacitive Pressure Sensing

Published on: March 17, 2023

2.1K

Area of Science:

  • Robotics and Mechanical Engineering
  • Sensor Technology
  • Materials Science

Background:

  • Traditional shape tracking methods often struggle with complex, morphing structures.
  • Existing capacitive sensing techniques for origami typically involve double-plate capacitors, limiting design flexibility.
  • There is a need for novel sensing methods capable of real-time shape reconstruction of dynamic, foldable structures.

Purpose of the Study:

  • To introduce FxC, a novel single-end morphing capacitive sensing method for accurate shape tracking.
  • To demonstrate the efficacy of combining folding origami structures with capacitive sensing for motion detection.
  • To develop a robust pipeline for reconstructing dynamic structural geometry from sensor data.

Main Methods:

  • Developed FxC by integrating conductive materials into origami structures as single-end capacitive sensing patches.
  • Utilized 3D geometry simulation and physics-based deduction to understand the operational principles of morphing single-end capacitors.
  • Created a software pipeline employing deep neural network regression for dynamic shape reconstruction from sensor signals and vision tracking data.
  • Validated the approach using various origami folding patterns (Accordion, Chevron, Sunray, V-Fold) with paper-based and textile-based materials.

Main Results:

  • Sensor signals showed coherent changes with the morphing structural motions.
  • Physics-based simulations corroborated experimental observations of the single-end capacitor behavior.
  • The deep learning model achieved a strong correlation (R-squared up to 95%) between predicted geometry primitives and visual ground truth.
  • Demonstrated a low tracking error of 6.5 mm for sensing patches.

Conclusions:

  • FxC offers a unique solution for shape tracking by leveraging origami's mechanical properties and capacitive sensing.
  • The method enables accurate dynamic shape reconstruction through a synergistic approach of simulation and machine learning.
  • Single-end capacitive sensing integrated with origami presents a promising avenue for advanced structural monitoring and robotics.