Detection of biomarkers in urine sample is often conducted by use of dipsticks, which provides a qualitative result. Urinalysis involving image recognition and data processing has becoming one of the powerful tools in clinical diagnosis. This paper presents colorimetric recognition of urinalysis dipsticks based on quadratic discriminant analysis (QDA) in order to overcome the drawbacks, such as, limited detection area, seriously affected by the external light conditions etc. It can decrease the error of color space conversion by directly processing the data from the captured image using QDA. The correlation of the sRGB color space and the difference of covariance matrix of the acquired data were took into account in this discriminant analysis. The results of validation experiments by Matlab simulation show that it can effectively identify the similarity between the test and reference color on the dipsticks with the color recognition accuracy at 97.33%.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1109/EMBC.2017.8037709 | DOI Listing |
PLoS One
March 2025
Yunnan Province Engineering Research Center for Functional Flower Resources and Industrialization, Southwest Forestry University, Kunming, Yunnan, China.
Rhus chinensis, a native plant species of China, possesses significant economic value in the ornamental sector. This study investigates the floral fragrance components and release patterns of R. chinensis, thus providing a theoretical foundation for the utilization of its floral fragrance.
View Article and Find Full Text PDFBiom J
April 2025
Department of Statistical Sciences, Università Cattolica del Sacro Cuore, Milan, Italy.
Supervised learning in presence of multiple sets of noisy labels is a challenging task that is receiving increasing interest in the ever-evolving landscape of healthcare analytics. Such an issue arises when multiple annotators are tasked to manually label the same training samples, potentially giving rise to discrepancies in class assignments among the supplied labels with respect to the ground truth. Commonly, the labeling process is entrusted to a small group of domain experts, and different level of experience and subjectivity may result in noisy training labels.
View Article and Find Full Text PDFThis study presents a novel deep learning approach for surface electromyography (sEMG) gesture recognition using stacked autoencoder neural network (SAE)s. The method leverages hierarchical representation learning to extract meaningful features from raw sEMG signals, enhancing the precision and robustness of gesture classification.•Feature Extraction and Classification MODWT Decomposition: The sEMG signals were decomposed using the MODWT DECOMPOSITION(Maximal Overlap Discrete Wavelet Transform) to capture various frequency components.
View Article and Find Full Text PDFFront Public Health
March 2025
Independent Researcher, Windermere, FL, United States.
Purpose: Adolescents are experiencing rising rates of obesity, insufficient exercise, and sleep disorders. To provide a scientific basis for policymakers to develop targeted and evidence-based health behavior education and policies, this study employed structural equation modeling to design the Adolescent Health Behavior Checklist (AHBC).
Methods: We designed a draft 6-dimensional AHBC, which includes the dimensions of exercise, diet, personal responsibility, sleep, interpersonal relationships, and stress management.
Sci Rep
March 2025
Medical School, Kunming University of Science and Technology, Kunming, China.
Acute myocardial infarction (AMI) is a major contributor to cardiovascular-related mortality, and early diagnosis is crucial for effective treatment and better outcomes. While several biomarkers have been explored for AMI, there remains a need for reliable, non-invasive biomarkers that can accurately differentiate AMI patients from healthy individuals. This study aims to identify potential mRNA biomarkers in peripheral blood that could aid in the diagnosis and monitoring of AMI.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!