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

Design Example: Resistive Touchscreen01:14

Design Example: Resistive Touchscreen

387
A device engineer plays a crucial role in designing user interfaces for mobile devices. One such interface is the resistive touchscreen, which fundamentally consists of two metallic layers: a flexible upper layer and a rigid lower layer, separated by a narrow gap. The high resistance between these two layers is a key characteristic of this design.
When a user touches the screen, the two layers make contact at a specific point known as the touchpoint. This contact reduces the resistance between...
387

You might also read

Related Articles

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

Sort by
Same author

Perioperative management of anticoagulation.

The British journal of surgery·2026
Same author

Accelerated Porosity Screening Using a Multichannel Colorimetric Array.

Angewandte Chemie (International ed. in English)·2025
Same author

Modelling immunity gaps to quantify infection resurgences.

Royal Society open science·2025
Same author

Modelling the initial stages of biocontrol of the invasive herb <i>Tradescantia fluminensis</i> by beetles.

Royal Society open science·2025
Same author

Incorporating Behavioral Science in Medication Adherence Communication: A Randomized Clinical Trial.

JAMA network open·2025
Same author

Modelling transmission and control of <i>Toxoplasma gondii</i> in New Zealand farmland.

Royal Society open science·2025

Related Experiment Video

Updated: Aug 9, 2025

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses
05:21

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses

Published on: January 7, 2019

8.0K

Rapid prototyping mixed-signal development kit for tactile neural computing.

Vasudev S Mallan1, Anitha Gopi1, Chithra Reghuvaran2

  • 1School of Electronics Systems and Automation, Digital University Kerala, Thiruvananthapuram, Kerala, India.

Frontiers in Neuroscience
|February 24, 2023
PubMed
Summary

We developed a rapid prototyping method for analog neural computing using Field-Programmable Analog Arrays (FPAA) and Field-Programmable Gate Arrays (FPGA). This approach accelerates the design of intelligent sensor systems for the Internet of Things (IoT).

Keywords:
computing arraysfield programmable analog arraysfield programmable gate arraysleaky integrate and fire neurontactile sensing system

More Related Videos

High Throughput Microfluidic Rapid and Low Cost Prototyping Packaging Methods
07:51

High Throughput Microfluidic Rapid and Low Cost Prototyping Packaging Methods

Published on: December 23, 2013

7.5K
A Tactile Automated Passive-Finger Stimulator TAPS
19:44

A Tactile Automated Passive-Finger Stimulator TAPS

Published on: June 3, 2009

13.8K

Related Experiment Videos

Last Updated: Aug 9, 2025

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses
05:21

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses

Published on: January 7, 2019

8.0K
High Throughput Microfluidic Rapid and Low Cost Prototyping Packaging Methods
07:51

High Throughput Microfluidic Rapid and Low Cost Prototyping Packaging Methods

Published on: December 23, 2013

7.5K
A Tactile Automated Passive-Finger Stimulator TAPS
19:44

A Tactile Automated Passive-Finger Stimulator TAPS

Published on: June 3, 2009

13.8K

Area of Science:

  • Computer Engineering
  • Artificial Intelligence
  • Sensor Technology

Background:

  • Intelligent sensor systems are crucial for Internet of Things (IoT) applications.
  • Analog neural computing offers efficient, near-sensor intelligence.
  • Rapid prototyping of analog/mixed-signal spiking neural computing is challenging.

Purpose of the Study:

  • To introduce mixed-mode neural computing arrays for efficient near-sensor intelligent computing.
  • To enable rapid prototyping and design optimization for analog/mixed-signal neural networks.
  • To present a scalable framework for neural network testing and sensor integration.

Main Methods:

  • Implementation using Field-Programmable Analog Arrays (FPAA) and Field-Programmable Gate Arrays (FPGA).
  • Utilizing FPAA and FPGA pipelines for accelerated design cycles.
  • Developing a scalable neural network testing framework with sensor integration.
  • Experimental validation using a tactile sensing system.

Main Results:

  • Demonstrated rapid prototyping capabilities for analog neural computing.
  • Validated real-time implementation on FPAA and FPGA hardware.
  • Successful integration of neural computing with tactile sensing.

Conclusions:

  • The proposed mixed-mode neural computing array architecture facilitates efficient near-sensor intelligence.
  • FPAA and FPGA combinations significantly reduce prototyping time for intelligent sensor systems.
  • The framework supports scalable development and testing of neuromorphic computing applications for IoT.