We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
INTEGRA BIOSCIENCES AG

Download Mobile App




Potential Uses for Smartphone-Based Diagnostic Tool Described

By LabMedica International staff writers
Posted on 30 Oct 2017
Print article
Image: The system uses a commercial smartphone to acquire and interpret real-time images of an enzymatic amplification reaction that takes place in a silicon microfluidic chip that generates green fluorescence and displays a visual read-out of the test. The system is composed of an unmodified smartphone and a portable 3-dimensional-printed cradle that supports the optical and electrical components, and interfaces with the rear-facing camera of the smartphone (Photo courtesy of the Micro & Nanotechnology Laboratory, University of Illinois at Urbana-Champaign).
Image: The system uses a commercial smartphone to acquire and interpret real-time images of an enzymatic amplification reaction that takes place in a silicon microfluidic chip that generates green fluorescence and displays a visual read-out of the test. The system is composed of an unmodified smartphone and a portable 3-dimensional-printed cradle that supports the optical and electrical components, and interfaces with the rear-facing camera of the smartphone (Photo courtesy of the Micro & Nanotechnology Laboratory, University of Illinois at Urbana-Champaign).
Two recent papers described potential applications for a smartphone-based instrument that can evaluate biological samples with the accuracy of clinical laboratory analyzers but at a fraction of the cost.

Investigators at the University of Illinois College of Engineering (Urbana-Champaign, USA) utilized a smartphone's internal rear-facing camera as a high-resolution spectrometer for measuring the colorimetric absorption spectrum, fluorescence emission spectrum, and resonant reflection spectrum from a microfluidic cartridge inserted into the measurement light path. Under user selection, the instrument gathered light from either the white “flash” LED of the smartphone or an integrated green laser diode to direct illumination into a liquid test sample or onto a photonic crystal biosensor.

Light emerging from each type of assay was gathered via optical fiber and passed through a diffraction grating placed directly over the smartphone camera to generate spectra from the assay when an image was collected. Each sensing modality was associated with a unique configuration of a microfluidic “stick” containing a linear array of liquid chambers that were swiped through the instrument while the smartphone captured video, and the software automatically selected spectra representative of each compartment.

Potential uses for the smartphone analyzer were described in a paper in the August 18, 2017, online edition of the journal Analytical Chemistry, where the investigators used the device to detect four horse respiratory diseases, and in a second paper in the August 22, 2017, online edition of the journal Biomedical Microdevices, where the device was used in a point-of-care setting to detect and quantify the presence of Zika, Dengue, and Chikungunya virus in a droplet of whole blood.

Contributing author Fu Sun, a research assistant at the University of Illinois College of Engineering, said, "I entered graduate school with the hope to make a better world by developing biomedical devices that can facilitate effective disease prevention, diagnosis, or treatment. This project is in line with my goal since it provides a point-of-care solution for the fast diagnosis of infectious diseases. Connected to a cloud database through a smartphone, it helps healthcare providers in the field embrace the era of big data and the Internet of Things."

Related Links:
University of Illinois College of Engineering

Gold Member
Chagas Disease Test
CHAGAS Cassette
Verification Panels for Assay Development & QC
Seroconversion Panels
New
Silver Member
H-FABP Assay
Heart-Type Fatty Acid-Binding Protein Assay
New
Malondialdehyde HPLC Test
Malondialdehyde in Serum/Plasma – HPLC

Print article

Channels

Clinical Chemistry

view channel
Image: The GlycoLocate platform uses multi-omics and advanced computational biology algorithms to diagnose early-stage cancers (Photo courtesy of AOA Dx)

AI-Powered Blood Test Accurately Detects Ovarian Cancer

Ovarian cancer ranks as the fifth leading cause of cancer-related deaths in women, largely due to late-stage diagnoses. Although over 90% of women exhibit symptoms in Stage I, only 20% are diagnosed in... Read more

Immunology

view channel
Image: The cancer stem cell test can accurately choose more effective treatments (Photo courtesy of University of Cincinnati)

Stem Cell Test Predicts Treatment Outcome for Patients with Platinum-Resistant Ovarian Cancer

Epithelial ovarian cancer frequently responds to chemotherapy initially, but eventually, the tumor develops resistance to the therapy, leading to regrowth. This resistance is partially due to the activation... Read more

Technology

view channel
Image: The new algorithms can help predict which patients have undiagnosed cancer (Photo courtesy of Adobe Stock)

Advanced Predictive Algorithms Identify Patients Having Undiagnosed Cancer

Two newly developed advanced predictive algorithms leverage a person’s health conditions and basic blood test results to accurately predict the likelihood of having an undiagnosed cancer, including ch... Read more
Copyright © 2000-2025 Globetech Media. All rights reserved.