Booth Id:
ENBM030
Category:
Biomedical Engineering
Year:
2021
Finalist Names:
Kung, Catherine (School: Indian Springs School)
Abstract:
Artificial skin is a synthetic membrane structure that mimics the flexibility and sensory
functions of biological skin. Similar to receptors in biological skin sending signals to
neurons in the brain, an artificial skin needs sensors capable of converting information
into electrical signals and transmitting them. Artificial skins are of increasing interest
for prosthetics, soft robotics, virtual reality, wearable devices, and emerging medical
applications. They can also potentially help reduce the number of amputations due to
foot ulcers found in 25% of diabetic individuals.
The goal of this research project is to demonstrate a method based on Kohonen
artificial neural networks to map a temperature-sensitive artificial skin and pinpoint the
location of a hot spot placed randomly on its surface, while using only a limited
number of electrodes placed at the periphery of the large area film. Doing so would
demonstrate the ability of this method to mimic how a brain functions when interpreting
information from multiple-sensors.
The artificial skins used were optimized previously from low-methoxyl pectin, a
natural substance found in many fruits and vegetables. They resulted into flexible films
whose electrical conductivity increased with temperature. A Kohonen artificial neural
network is now trained with the electrical measurement data collected from the
periphery of the artificial skin as a hot object is placed randomly on the sample surface
to heat it locally. A representative two-dimensional map of the artificial skin sample is
obtained in the topology of the resulting trained neural network, with the location of the
hot object identified.