Wearable and Flexible Sensor Devices: Recent Advances in Designs, Fabrication Methods, and Applications

Sensors, Journal Year: 2025, Volume and Issue: 25(5), P. 1377 - 1377

Published: Feb. 24, 2025

The development of wearable sensor devices brings significant benefits to patients by offering real-time healthcare via wireless body area networks (WBANs). These have gained traction due advantageous features, including their lightweight nature, comfortable feel, stretchability, flexibility, low power consumption, and cost-effectiveness. Wearable play a pivotal role in healthcare, defence, sports, health monitoring, disease detection, subject tracking. However, the irregular nature human poses challenge design such systems. This manuscript provides comprehensive review recent advancements flexible smart that can support next generation devices. Further, direct ink writing (DIW) (DW) methods has revolutionised new high-resolution integrated structures, enabling next-generation soft, flexible, stretchable Recognising importance keeping academia industry informed about cutting-edge technology time-efficient fabrication tools, this also thorough overview latest progress various for utilised WBAN evaluation using phantoms. An emerging challenges future research directions is discussed conclusion.

Language: Английский

Machine Learning Model Development for Malignant Prostate Lesion Prediction Using Texture Analysis Features from Ultrasound Shear-Wave Elastography

Cancers, Journal Year: 2025, Volume and Issue: 17(8), P. 1358 - 1358

Published: April 18, 2025

Introduction: Artificial intelligence (AI) is increasingly utilized for texture analysis and the development of machine learning (ML) techniques to enhance diagnostic accuracy. ML algorithms are trained differentiate between normal malignant conditions based on provided data. Texture feature analysis, including first-order second-order features, a critical step in development. This study aimed evaluate quantitative features prostate cancer tissues identified through ultrasound B-mode shear-wave elastography (SWE) imaging develop assess models predicting classifying versus tissues. Methodology: First-order were extracted from SWE imaging, four reconstructed regions interest (ROIs) images A total 94 derived, intensity, Gray-Level Co-Occurrence Matrix (GLCM), Dependence Length (GLDLM), Run (GLRLM), Size Zone (GLSZM). Five developed evaluated using 5-fold cross-validation predict Results: Data 62 patients analyzed. All ROIs, except those derived exhibited statistically significant differences Among models, Support Vector Machines (SVM), Random Forest (RF), Naive Bayes (NB) demonstrated highest performance across all ROIs. These consistently achieved strong predictive accuracy Gray Pure Reconstructed Provided sensitivity specificity PCa prediction by 82%, 90%, 98%, 96%, respectively. Conclusions: with SWE-US effectively differentiates benign lesions, like contrast, entropy, correlation playing key role. Forest, SVM, Naïve showed classification performance, while grayscale reconstructions (GPSWE GRRI) enhanced detection

Language: Английский

Implementation of a Breast Phantom with Acoustic Properties for Ultrasonic Thermometry

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(10), P. 5275 - 5275

Published: May 9, 2025

Breast cancer remains one of the leading causes death among women globally. Early detection is critical for improving patient outcomes, making development accurate and efficient methods essential facilitating timely treatment enhancing patients’ quality life. Lesion sites are often associated with localized temperature increases, which can be identified by characterizing thermal gradients using thermometry tools. Ultrasound-based techniques preferred obtaining patterns due to their noninvasive, non-ionizing nature cost-effectiveness compared like magnetic resonance imaging. This study focuses on developing breast tissue models varying acoustic properties, specifically speed sound across temperatures ranging from 32 °C 36 in increments 0.5 ultrasonic inspection diagnostic applications. These simulate healthy tumorous tissue, including fat, gland, tumor layers. Signal variations were analyzed cross-correlation assess changes as a function temperature. The proposed methodology offers cost-effective, rapid, precise approach phantom production, intervals through analysis acquired signals.

Language: Английский