AIMC Topic: Smartphone
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Ultrafast Ratiometric Fluorescent Probe and Deep Learning-Assisted On-Site Detection Platform for BAs and Meat Freshness Based on Molecular Engineering.
ACS sensors
May 23, 2025
As metabolic byproducts and representative indicators of food spoilage, the monitoring and detection for biogenic amines (BAs) are crucial but challenging for food quality assessment. Here, a strategy is proposed by combining fluorescent probe molecu...
Personalized prediction of negative affect in individuals with serious mental illness followed using long-term multimodal mobile phenotyping.
Translational psychiatry
May 19, 2025
Heightened negative affect is a core feature of serious mental illness. Over 90% of American adults own a smartphone, equipped with an array of sensors which can continuously and unobtrusively measure behaviors (e.g., activity levels, location, and p...
A stretchable, adhesive, and wearable hydrogel-based patches based on a bilayer PVA composite for online monitoring of sweat by artificial intelligence-assisted smartphones.
Talanta
May 15, 2025
Real-time monitoring of sweat using wearable devices faces challenges such as limited adhesion, mechanical flexibility, and accurate detection. In this work, we present a stretchable, adhesive, bilayer hydrogel-based patch designed for continuous mon...
A machine-learning-integrated portable electrochemiluminescence sensing platform for the visualization and high-throughput immunoassays.
Talanta
May 15, 2025
Electrochemiluminescence (ECL)-based point-of-care testing (POCT) has the potential to facilitate the rapid identification of diseases, offering advantages such as high sensitivity, strong selectivity, and minimal background interference. However, as...
Advanced internet of things enhanced activity recognition for disability people using deep learning model with nature-inspired optimization algorithms.
Scientific reports
May 14, 2025
Human activity recognition has complex applications because of its worldly use of acquisition devices, namely video cameras and smartphones, and its capability to take human activity data. Human activity recognition became a hot scientific subject in...
A Software-Defined Sensor System Using Semantic Segmentation for Monitoring Remaining Intravenous Fluids.
Sensors (Basel, Switzerland)
May 13, 2025
Accurate intravenous (IV) fluid monitoring is critical in healthcare to prevent infusion errors and ensure patient safety. Traditional monitoring methods often depend on dedicated hardware, such as weight sensors or optical systems, which can be cost...
Machine learning-based prediction of restless legs syndrome using digital phenotypes from wearables and smartphone data.
Scientific reports
May 10, 2025
Restless legs syndrome (RLS) is a relatively common neurosensory disorder that causes an irresistible urge for leg movement. RLS causes sleep disturbances and reduced quality of life, but accurate diagnosis remains challenging owing to the reliance o...
Machine learning of blood haemoglobin and haematocrit levels via smartphone conjunctiva photography in Kenyan pregnant women: a clinical study protocol.
BMJ open
May 8, 2025
INTRODUCTION: Anaemia during pregnancy is a widespread health burden globally, especially in low- and middle-income countries, posing a serious risk to both maternal and neonatal health. The primary challenge is that anaemia is frequently undetected ...
Incorporating computer vision on smart phone photographs into screening for inflammatory arthritis: results from an Indian patient cohort.
Rheumatology (Oxford, England)
May 1, 2025
OBJECTIVES: Convolutional neural networks (CNNs) are increasingly used to classify medical images, but few studies utilize smartphone photographs. The objective of this study was to assess CNNs for differentiating patients from controls and detecting...
A Neural Network for Atrial Fibrillation Detection via PPG.
Studies in health technology and informatics
Apr 24, 2025
Atrial fibrillation (AF) is a prevalent cardiac arrhythmia associated with severe complications such as ischemic stroke and heart failure. Early detection is essential for timely intervention; however, traditional diagnostic methods often lack scalab...
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