the past few decades, roboticists and computer scientists have
developed artificial systems that replicate biological functions and
human abilities in increasingly realistic ways. This includes artificial
intelligence systems, as well as sensors that can capture various types
of sensory data.
trying to understand properties of objects and how to grasp them or
handle them, humans often rely on their sense of touch. Artificial
sensing systems that replicate human touch can thus be of great value,
as they could enable the development of better performing and more
responsive robots or prosthetic limbs.
at Sungkyunkwan University and Hanyang University in South Korea have
recently created an artificial tactile sensing system that mimics the
way in which humans recognize objects in their surroundings via their
sense of touch. This system, presented in a paper published in Nature Electronics, uses sensors to capture data associated with the tactile properties of objects.
report an artificial neural tactile skin system that mimics the human
tactile recognition process using particle-based polymer composite
sensors and a signal-converting system," Sungwoo Chun and his colleagues
wrote in their paper.
sensory systems convert tactile stimuli into action potentials through a
process known as somatosensory transduction. Subsequently, they
transmit these signals to the brain via afferent nerves.
emulate the human tactile system, the artificial neural tactile skin
created by Chun and his colleagues utilizes sensors that respond to
pressure and vibration, replicating the function of slow adaptive and
fast adaptive mechanoreceptors in the human skin.
The data they collect resembles information gathered by human sensory
neurons; thus they ultimately produce signals that look like human
tactile nerve signals.
system created by the researchers is made up of T-skin films with
conductive piezoresistive and piezoelectric particles arranged in an
elastic polymer matrix. The films are ultrathin (<120μm), lightweight
(15 mg cm-2) and adhesive, thus they highly resemble real human skin.
evaluate their artificial skin system and prove that it can be
integrated within real biological systems, the researchers evaluated it
in a series of experiments on mice. These experiments included an ex
vivo transmission test in an afferent nerve and an in vivo muscle
response test through the stimulation of an efferent nerve. The results
of both these experiments were very promising, confirming the
possibility of integrating the system within real biological systems.
show in an ex vivo test that undistorted transmission of the output
signals through an afferent tactile mouse nerve fiber is possible, and
in an in vivo test that the signals can stimulate a rat motor nerve to
induce the contraction of a hindlimb muscle," Chun and his colleagues
explained in their paper.
addition to testing their artificial skin by integrating it with real
biological systems, the researchers evaluated its ability to analyze and
recognize the texture of surfaces. To do this, they laminated
artificial ridges that mimic the structure of a human fingertip on their
T-skin device. They found that this system could sense complex textural
patterns. In addition, the team combined it with a deep learning
technique that can classify surface structures, achieving a remarkable
texture classification accuracy of 99.1%.
use our tactile sensing system to develop an artificial finger that can
learn to classify fine and complex textures by integrating the sensor
signals with a deep learning technique," the researchers explained in
their paper. "The approach can also be used to predict unknown textures
on the basis of the trained model."
the future, the artificial tactile sensing system developed by this
team of researchers could be integrated with existing or newly developed
robotic systems to replicate the human sense of touch. This could
significantly improve their performance on tasks that involve touching,
grasping and manipulating objects.