AIMC Topic: Electric Impedance

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Physics Informed Neural Networks for Electrical Impedance Tomography.

Neural networks : the official journal of the International Neural Network Society
Electrical Impedance Tomography (EIT) is an imaging modality used to reconstruct the internal conductivity distribution of a domain via boundary voltage measurements. In this paper, we present a novel EIT approach for integrated sensing of composite ...

Automated Electrical Detection of Proteins for Oral Squamous Cell Carcinoma in an Integrated Microfluidic Chip Using Multi-Frequency Impedance Cytometry and Machine Learning.

Sensors (Basel, Switzerland)
Proteins can act as suitable biomarkers for the prognosis and diagnosis of certain conditions and can help us gain an understanding of the fundamental processes that occur inside an organism. In this work, we present a fully automated machine learnin...

Impedance for Assistance: Upper-Limb Assistive Soft Robotic Suit Using Linked-Layer Jamming Mechanisms.

Soft robotics
Wearable robots, especially those composed of soft materials, are increasingly attracting interest due to their comfort, ease of donning and doffing, and their ability to provide assistance across various applications. In wearable robotics, striking ...

In-hospital bioimpedance-derived total body water predicts short-term cardiovascular mortality and re-hospitalizations in acute decompensated heart failure patients.

Clinical research in cardiology : official journal of the German Cardiac Society
BACKGROUND: Hospital re-admissions in heart failure (HF) patients are mostly caused by an acute exacerbation of their chronic congestion. Bioimpedance analysis (BIA) has emerged as a promising non-invasive method to assess the volume status in HF. Ho...

Neural Network-Enabled Multiparametric Impedance Signal Templating for High throughput Single-Cell Deformability Cytometry Under Viscoelastic Extensional Flows.

Small (Weinheim an der Bergstrasse, Germany)
Cellular biophysical metrics exhibit systematic alterations during processes, such as metastasis and immune cell activation, which can be used to identify and separate live cell subpopulations for targeting drug screening. Image-based biophysical cyt...

Machine learning-enhanced electrical impedance myography to diagnose and track spinal muscular atrophy progression.

Physiological measurement
To evaluate electrical impedance myography (EIM) in conjunction with machine learning (ML) to detect infantile spinal muscular atrophy (SMA) and disease progression.. Twenty-six infants with SMA and twenty-seven healthy infants had been enrolled and ...

Repetitive Impedance Learning-Based Physically Human-Robot Interactive Control.

IEEE transactions on neural networks and learning systems
Model-based impedance learning control can provide variable impedance regulation for robots through online impedance learning without interaction force sensing. However, the existing related results only guarantee the closed-loop control systems to b...

Deep Learning Enhanced Label-Free Action Potential Detection Using Plasmonic-Based Electrochemical Impedance Microscopy.

Analytical chemistry
Measuring neuronal electrical activity, such as action potential propagation in cells, requires the sensitive detection of the weak electrical signal with high spatial and temporal resolution. None of the existing tools can fulfill this need. Recentl...

Non-Invasive Detection of Early-Stage Fatty Liver Disease via an On-Skin Impedance Sensor and Attention-Based Deep Learning.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Early-stage nonalcoholic fatty liver disease (NAFLD) is a silent condition, with most cases going undiagnosed, potentially progressing to liver cirrhosis and cancer. A non-invasive and cost-effective detection method for early-stage NAFLD detection i...