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Related Concept Videos

Temperature Measurement Sites01:14

Temperature Measurement Sites

A thermometer measures body temperature. The common sites for measuring body temperature are the oral cavity, axillary region, temporal artery, and skin surface, such as the forehead, abdomen, and axilla. True core body temperature is assessed in the rectum, tympanic membrane, pulmonary artery, esophagus, and urinary bladder.
Oral: When assessing oral temperature, the thermometer tip should be placed under the tongue in the posterior sublingual pocket. It offers accurate readings and can be...

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  2. Multimodal Pcsc Sensors For Real-time Temperature And Force Detection Using Lrtnet.
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  2. Multimodal Pcsc Sensors For Real-time Temperature And Force Detection Using Lrtnet.

Related Experiment Video

Method for Simultaneous fMRI/EEG Data Collection during a Focused Attention Suggestion for Differential Thermal Sensation
06:33

Method for Simultaneous fMRI/EEG Data Collection during a Focused Attention Suggestion for Differential Thermal Sensation

Published on: January 5, 2014

Multimodal PCSC Sensors for Real-Time Temperature and Force Detection Using LRTNet.

Zhiqiang Gao1, Bing Ren2, Jing Han3

  • 1Department of Automation, Taiyuan Institute of Technology, Taiyuan 030008, China.

Sensors (Basel, Switzerland)
|June 12, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

A novel multimodal sensor using carbon quantum dots and spiropyran effectively separates force and temperature signals. A lightweight ResNet-Transformer network (LRTNet) enhances temperature sensing accuracy for robotics.

Keywords:
LRTNetmultimodal sensorsreal-time PCSC sensorsignal crosstalk

More Related Videos

Fiber Optic Distributed Sensors for High-resolution Temperature Field Mapping
09:48

Fiber Optic Distributed Sensors for High-resolution Temperature Field Mapping

Published on: November 7, 2016

Related Experiment Videos

Method for Simultaneous fMRI/EEG Data Collection during a Focused Attention Suggestion for Differential Thermal Sensation
06:33

Method for Simultaneous fMRI/EEG Data Collection during a Focused Attention Suggestion for Differential Thermal Sensation

Published on: January 5, 2014

Fiber Optic Distributed Sensors for High-resolution Temperature Field Mapping
09:48

Fiber Optic Distributed Sensors for High-resolution Temperature Field Mapping

Published on: November 7, 2016

Area of Science:

  • Materials Science
  • Robotics
  • Sensor Technology

Background:

  • Multimodal sensors are crucial for robotics but face challenges like signal crosstalk and slow real-time performance.
  • Accurate detection of pressure and temperature is vital for measurement precision in sensing applications.

Purpose of the Study:

  • To develop a multimodal sensor with reduced signal crosstalk and improved real-time performance for simultaneous force and temperature detection.
  • To introduce a novel algorithm for enhanced temperature sensing accuracy by fusing multimodal sensor data.

Main Methods:

  • A multimodal PCSC sensor was designed utilizing carbon quantum dots (CQDs) for pressure sensing (resistance variation) and spiropyran (SP) for temperature sensing (thermochromic properties).
  • A lightweight ResNet-Transformer network (LRTNet) was developed to fuse resistance and color signals for accurate temperature detection.
  • The sensor and LRTNet were tested on a robotic manipulator for dual force and temperature recognition.
  • Main Results:

    • The PCSC sensor demonstrated signal separation, with force detection showing a 0.4 s response time and temperature detection stabilizing within 7.5 s.
    • LRTNet achieved a runtime of 152.08 ms and a temperature sensing accuracy of 95% on the robotic manipulator.
    • LRTNet improved overall performance by at least 11% compared to traditional algorithms, enhancing reliability.

    Conclusions:

    • The developed multimodal PCSC sensor effectively mitigates signal crosstalk and provides reliable force and temperature measurements.
    • The LRTNet algorithm significantly improves temperature sensing accuracy and processing speed in multimodal sensor applications.
    • This integrated sensor and algorithm approach advances the performance and dependability of multimodal sensing systems in robotics.