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Related Concept Videos

Tactile and Chemical Senses01:27

Tactile and Chemical Senses

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Tactile senses encompass touch, temperature, and pain, each mediated by specific receptors. Touch receptors detect mechanical energy or pressure against the skin. Sensory fibers from these receptors enter the spinal cord and relay information to the brain stem. Here, most fibers cross over to the opposite side of the brain. The touch information then moves to the thalamus, which projects a map of the body's surface onto the somatosensory areas of the parietal lobes in the cerebral cortex.
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Design Example01:23

Design Example

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The innovation of touch-tone telephony revolutionized the telecommunications industry by replacing the traditional rotary dial with a dual-tone multi-frequency (DTMF) signaling system. This system uses a matrix-style keypad with buttons arranged in four rows and three columns, creating 12 distinct signals each assigned to a pair of frequencies. Each button press results in a simultaneous generation of two sinusoidal tones – one from a low-frequency group (697 to 941 Hz) and one from a...
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Perceiving Loudness, Pitch, and Location01:21

Perceiving Loudness, Pitch, and Location

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The human brain perceives pitch through two primary mechanisms reflected in place theory and frequency theory. Each mechanism describes how sound waves are interpreted as specific pitches by the brain, offering insights into the intricate processes of auditory perception.
Place theory, or place coding, suggests that different pitches are heard because various sound waves activate specific locations along the cochlea's basilar membrane. The brain determines the pitch of a sound by...
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Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

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Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
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Design Example: Resistive Touchscreen01:14

Design Example: Resistive Touchscreen

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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.
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Somatosensation01:33

Somatosensation

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The somatosensory system relays sensory information from the skin, mucous membranes, limbs, and joints. Somatosensation is more familiarly known as the sense of touch. A typical somatosensory pathway includes three types of long neurons: primary, secondary, and tertiary. Primary neurons have cell bodies located near the spinal cord in groups of neurons called dorsal root ganglia. The sensory neurons of ganglia innervate designated areas of skin called dermatomes.
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Asthma Detection Research Based on Voice Signal Processing and Machine Learning
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A Machine Learning-Combined Flexible Sensor for Tactile Detection and Voice Recognition.

Jiawang Xie1, Yuzhi Zhao1, Dezhi Zhu1

  • 1State Key Laboratory of Tribology in Advanced Equipment, Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China.

ACS Applied Materials & Interfaces
|February 22, 2023
PubMed
Summary

A new flexible sensor uses machine learning for real-time tactile sensing and voice recognition. This intelligent sensor, based on laser-induced graphitization, offers a multifunctional platform for advanced human-machine interactions and wearable devices.

Keywords:
flexible sensorhuman−machine interactionlaser processingmachine learningtactile sensing

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Area of Science:

  • Materials Science
  • Electrical Engineering
  • Artificial Intelligence

Background:

  • Intelligent sensors are crucial for wearable electronics, AI, healthcare, and human-machine interaction.
  • Developing multifunctional sensing systems for complex signal detection remains a challenge.

Purpose of the Study:

  • To develop a machine learning-combined flexible sensor for real-time tactile sensing and voice recognition.
  • To create a smart human-machine interaction system using a patterned touch panel.
  • To demonstrate the sensor's capability for accurate voice monitoring and recognition.

Main Methods:

  • Fabrication of a flexible sensor using laser-induced graphitization with a triboelectric layer.
  • Utilizing contact electrification for pressure-to-electrical signal conversion without external bias.
  • Implementing machine learning algorithms for signal analysis and pattern recognition.

Main Results:

  • The sensor exhibits characteristic responses to various mechanical stimuli.
  • A digital arrayed touch panel system was successfully constructed for controlling electronic devices.
  • High-accuracy real-time voice monitoring and recognition were achieved using machine learning.

Conclusions:

  • The developed machine learning-empowered flexible sensor is a promising platform for tactile sensing and voice recognition.
  • This technology enables advancements in human-machine interaction and intelligent wearable devices.
  • The sensor shows potential for real-time health detection applications.