ArticleBiosensors & bioelectronics2025
An integrated wearable fluorescence sensor for E. coli detection in catheter bags.
Article in Biosensors & bioelectronics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
2 citing papers in PubMed.
- Sensing in Urinary Catheter Systems: From Measurands and Signal Fidelity to Supportable Clinical Claims.Sensors (Basel, Switzerland) · 2026Review
- OpenLM: an open-source pixel super-resolution platform for lens-free microscopy with applications in bacterial growth monitoring and deep learning-based bacterial detection.Lab on a chip · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Urinary tract infections (UTIs), including catheter-associated UTIs (CAUTIs), affect millions worldwide. Traditional diagnostic methods, like urinalysis and urine culture, have limitations-urinalysis is fast but lacks sensitivity, while urine culture is accurate but takes up to two days. Here, we present an integrated wearable fluorescence sensor to detect UTI-related bacterial infections early at the point of care by on-body monitoring. The sensor features a hardware platform with a flexible PCB that attaches to a urine catheter bag, emitting excitation light and detecting emission light of E. coli-specific enzymatic reaction for continuous monitoring. Our custom-developed smartphone application allows remote control and data transfer via Bluetooth and performs in situ data analysis without cloud computing. The performance of the device was demonstrated by detecting E. coli at concentrations of 10
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.