AIMC Topic: Smartphone

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Smartphone-based fluorescence Eu/Ce-MOFs hydrogel sensor for sensitive and visual detection of tetracyclines with machine learning-assistance.

Food chemistry
The excessive use of tetracyclines (TCs) poses a significant threat to human health, necessitating the development of convenient, rapid, and intelligent detection methods for monitoring TCs residues in food products. In this work, we present a hetero...

Application of image guided analyses to monitor fecal microbial composition and diversity in a human cohort.

Scientific reports
The critical role of gut microbiota in human health and disease has been increasingly illustrated over the past decades, with a significant amount of research demonstrating an unmet need for self-monitor of the fecal microbial composition in an easil...

Video-based pupillometry using Fourier Mellin image correlation.

Scientific reports
We introduce a novel method for evaluating the pupil light reflex (PLR) response using digital video recordings. Expensive, specialized devices are replacing traditional penlight tests in emergency and neurotrauma departments, but they are not widely...

Finger drawing on smartphone screens enables early Parkinson's disease detection through hybrid 1D-CNN and BiGRU deep learning architecture.

PloS one
BACKGROUND: Parkinson's disease (PD), a progressive neurodegenerative disorder prevalent in aging populations, manifests clinically through characteristic motor impairments including bradykinesia, rigidity, and resting tremor. Early detection and tim...

PREACT-digital: study protocol for a longitudinal, observational multicentre study on digital phenotypes of non-response to cognitive behavioural therapy for internalising disorders.

BMJ open
INTRODUCTION: Cognitive behavioural therapy (CBT) serves as a first-line treatment for internalising disorders (ID), encompassing depressive, anxiety or obsessive-compulsive disorders. Nonetheless, a substantial proportion of patients do not experien...

Assessing chronic obstructive pulmonary disease risk based on exhalation and cough sounds.

Biomedical engineering online
BACKGROUND AND OBJECTIVE: Chronic obstructive pulmonary disease (COPD), a progressively worsening respiratory condition, severely impacts patient quality of life. Early risk assessment can improve treatment outcomes and lessen healthcare burdens. How...

A human activity recognition model based on deep neural network integrating attention mechanism.

Scientific reports
Human Activity Recognition (HAR) is crucial in multiple fields. Existing HAR techniques include manual feature extraction, codebook-based methods, and deep learning, each with limitations. This paper presents DCAM-Net (DeepConvAttentionMLPNet), a nov...

Facial Emotion Recognition of 16 Distinct Emotions From Smartphone Videos: Comparative Study of Machine Learning and Human Performance.

Journal of medical Internet research
BACKGROUND: The development of automatic emotion recognition models from smartphone videos is a crucial step toward the dissemination of psychotherapeutic app interventions that encourage emotional expressions. Existing models focus mainly on the 6 b...

A novel mobiles android application for facilitating wheelchair users access to public buildings in urban environments.

Scientific reports
In recent years, societies and governments worldwide have increasingly focused on addressing the rights and needs of individuals with various disabilities. Concurrently, smartphone applications (apps) have gained widespread popularity across diverse ...

Deep learning for smartphone-aided detection system of Helicobacter Pylori in gastric biopsy.

Scientific reports
Helicobacter pylori (HP) have chronically infected more than half of the world's population and is a cause of chronic gastritis, peptic ulcers and gastric carcinoma. The manual detection of HP in a glass slide with a microscope is extremely time-cons...