AIMC Topic: Electrodes

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Fully nondestructive analysis of capsaicinoids electrochemistry data with deep neural network enables portable system.

Food chemistry
Electrochemical methods have been extensively applied for the detection of chemical information from food or other analytes. However, existing electrochemical methods are limited to focusing solely on the absorption peaks and disregard much of the hi...

An Extended Spatial Transformer Convolutional Neural Network for Gesture Recognition and Self-Calibration Based on Sparse sEMG Electrodes.

IEEE transactions on biomedical circuits and systems
sEMG-based gesture recognition is widely applied in human-machine interaction system by its unique advantages. However, the accuracy of recognition drops significantly as electrodes shift. Besides, in applications such as VR, virtual hands should be ...

Leveraging Multiple Distinct EEG Training Sessions for Improvement of Spectral-Based Biometric Verification Results.

Sensors (Basel, Switzerland)
Most studies on EEG-based biometry recognition report results based on signal databases, with a limited number of recorded EEG sessions using the same single EEG recording for both training and testing a proposed model. However, the EEG signal is hig...

MSFF-Net: Multi-Stream Feature Fusion Network for surface electromyography gesture recognition.

PloS one
In the field of surface electromyography (sEMG) gesture recognition, how to improve recognition accuracy has been a research hotspot. The rapid development of deep learning provides a new solution to this problem. At present, the main applications of...

Organizing Reliable Polymer Electrode Lines in Flexible Neural Networks via Coffee Ring-Free Micromolding in Capillaries.

ACS applied materials & interfaces
With an increase in the demand for smart wearable systems, artificial synapse arrays for flexible neural networks have received considerable attention. A synaptic device with a two-terminal configuration is promising for complex neural networks becau...

An open-source deep learning model for predicting effluent concentration in capacitive deionization.

The Science of the total environment
To effectively evaluate the performance of capacitive deionization (CDI), an electrochemical ion separation technology, it is necessary to accurately estimate the number of ions removed (effluent concentration) according to energy consumption. Herein...

Computer-Vision-Based Approach to Classify and Quantify Flaws in Li-Ion Electrodes.

Small methods
X-ray computed tomography (X-ray CT) is a non-destructive characterization technique that in recent years has been adopted to study the microstructure of battery electrodes. However, the often manual and laborious data analysis process hinders the ex...

Enhanced artificial intelligence for electrochemical sensors in monitoring and removing of azo dyes and food colorant substances.

Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association
It is necessary to determine whether synthetic dyes are present in food since their excessive use has detrimental effects on human health. For the simultaneous assessment of tartrazine and Patent Blue V, a novel electrochemical sensing platform was d...