In the process of long-term monitoring of the coal seam floor of a coal mining face using electrical resistivity tomography (ERT), the data loss caused by electrode disconnection adversely affects early warning of water inrush and prevents the identi...
BACKGROUND: We aimed to determine whether unsupervised machine learning was able to discover latent and possibly clinically-relevant clusters, hidden in dynamic electrical impedance tomography (EIT) images within a population of mechanically ventilat...
This paper presents the development of a novel miniature electrical impedance tomography (EIT) system made out of glass, along with the training, validation, and testing of an accompanying open-source machine learning image reconstruction model. Our ...
Accurately estimating energy requirements is critical for individuals to maintain a healthy life. Traditional methods may be time-consuming, complex, low in accuracy, and costly, thus creating a need for new approaches. This study explores the applic...
Frequency-dependent impedance spectroscopy in combination with machine learning offers a powerful strategy for discriminating among gas species using mutually interacting semiconductor metal oxide (SMO) gas sensors. In this study, 0.3 at% platinum-lo...
This study aimed to apply a neural network to raw bioelectrical impedance analysis data and to test whether sarcopenia could be predicted with high accuracy. The study population comprised 727 community-dwelling older adults aged 65-85 years who part...
U-Net has gained traction in biomedical signal processing, particularly for segmenting 1D waveforms. Building on this success, we propose a U-Net-inspired architecture that integrates both 2D and 1D CNNs to effectively learn and segment gastroesophag...
Soft strain sensors are crucial for enabling humanoid robots to perform industrial, medical, and other human-related tasks. However, the limited internal space of humanoid robots exposes soft strain sensors to interference from line resistance, conta...
The accurate classification of obesity is essential for public health and clinical decision-making. Traditional anthropometric measures such as body mass index (BMI) have limitations in differentiating between fat and lean mass. This study aimed to e...
The demand for advanced human-machine interfaces (HMIs) highlights the need for accurate measurement of muscle contraction states. Traditional methods, such as electromyography, cannot measure passive muscle contraction states, while optical and ultr...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.