AIMC Topic: Electric Conductivity

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A Zwitterionic-Aromatic Motif-Based ionic skin for highly biocompatible and Glucose-Responsive sensor.

Journal of colloid and interface science
Electronic skins that can sense external stimuli have been of great significance in artificial intelligence and smart wearable devices in recent years. However, most of current skin materials are unable to achieve high biocompatibility and anti-bacte...

Improving phase-based conductivity reconstruction by means of deep learning-based denoising of phase data for 3T MRI.

Magnetic resonance in medicine
PURPOSE: To denoise phase using a deep learning method for phase-based in vivo electrical conductivity reconstruction in a 3T MR system.

Recycled Iontronic from Discarded Chewed Gum for Personalized Healthcare Monitoring and Intelligent Information Encryption.

ACS applied materials & interfaces
With the explosive development of smart wearable devices, a serious situation that a large amount of energy waste and environmental pollution caused by electronic discarding needs to be solved urgently. Here, as a throwaway waste material, a chewed g...

Janus-like Jagged Structure with Nanocrystals for Self-Sorting Wearable Tactile Sensor.

ACS applied materials & interfaces
In this study, a self-sorting sensor was developed with the ability to distinguish between different pressure regimes and translate the pressure to electrical signals. Specifically, the self-sorting sensor can distinguish between soft and hard pressu...

Time-resolved neurotransmitter detection in mouse brain tissue using an artificial intelligence-nanogap.

Scientific reports
The analysis of neurotransmitters in the brain helps to understand brain functions and diagnose Parkinson's disease. Pharmacological inhibition experiments, electrophysiological measurement of action potentials, and mass analysers have been applied f...

Investigating the challenges and generalizability of deep learning brain conductivity mapping.

Physics in medicine and biology
To investigate deep learning electrical properties tomography (EPT) for application on different simulated and in-vivo datasets, including pathologies for brain conductivity reconstructions, 3D patch-based convolutional neural networks were trained t...

Alloying conducting channels for reliable neuromorphic computing.

Nature nanotechnology
A memristor has been proposed as an artificial synapse for emerging neuromorphic computing applications. To train a neural network in memristor arrays, changes in weight values in the form of device conductance should be distinct and uniform. An elec...

Fabrication of Carbon-Based Ionic Electromechanically Active Soft Actuators.

Journal of visualized experiments : JoVE
Ionic electromechanically active capacitive laminates are a type of smart material that move in response to electrical stimulation. Due to the soft, compliant and biomimetic nature of this deformation, actuators made of the laminate have received inc...

Identification of Upper-Limb Movements Based on Muscle Shape Change Signals for Human-Robot Interaction.

Computational and mathematical methods in medicine
Towards providing efficient human-robot interaction, surface electromyogram (EMG) signals have been widely adopted for the identification of different limb movement intentions. Since the available EMG signal sensors are highly susceptible to external...

A proposed soft pneumatic actuator control based on angle estimation from data-driven model.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
This article proposes a bending angle controller for soft pneumatic actuators, which could be implemented in soft robotic rehabilitation gloves to assist patients with hand impairment, such as stroke survivors. A data-driven model is used to estimate...