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
ARAB HEALTH - INFORMA

Download Mobile App




Events

27 Jan 2025 - 30 Jan 2025
15 Feb 2025 - 17 Feb 2025

mHealth Spectroscopy Measures Hemoglobin Optically

By HospiMedica International staff writers
Posted on 08 Jun 2020
Print article
Image: Professor Kim using the Hemoglobin smartphone app (Photo courtesy of Vincent Walter/ Purdue University)
Image: Professor Kim using the Hemoglobin smartphone app (Photo courtesy of Vincent Walter/ Purdue University)
A novel smartphone-based technique helps assess blood hemoglobin (Hgb) and blood disorders without drawing blood, claims a new study.

Developed at Purdue University (Lafayette, IN, USA), Vanderbilt University (Nashville, TN, USA), and Moi University (Nairobi, Kenya), the smartphone app is based on spectral super-resolution (SSR) spectroscopy, which transforms the built-in camera of a smartphone into a hyperspectral imager, without the need for hardware modifications or accessories. The Hgb measurements are based on statistical learning of SSR of the eyelids, and reconstruction of the detailed spectra from the camera’s three color RGB data. To perform an Hgb measurement, the patient pulls down the inner eyelid to expose the small blood vessels underneath.

A healthcare professional then uses the smartphone app to take pictures of the inner eyelids. The SSR then extracts the detailed spectral information from the camera's images and a computational algorithm quantifies Hgb content from the data. The mobile app also includes features designed to stabilize image quality and synchronize the smartphone flashlight so as to obtain consistent images. The inner eyelid was selected as the sensing site because microvasculature is easily visible there, and it is not affected by skin color, which eliminates the need for any personal calibrations.

With the aid of a randomly selected group of 138 patients who had conventional blood tests at the Moi University Teaching and Referral Hospital, the researchers first trained the algorithm, and then tested the mobile health app with the remaining 15 volunteers. The results showed that the prediction errors for the smartphone technique were within 5-10% of those measured with clinical laboratory blood tests. They now plan to use the mobile health tool to assess nutritional status, anemia, and sickle cell disease. The study was published in the June 2020 issue of Optica.

“This new technology could be very useful for detecting anemia, which is characterized by low levels of blood hemoglobin. This is a major public health problem in developing countries, but can also be caused by cancer and cancer treatments,” said senior author Professor Young Kim, PhD, of Purdue University. "The COVID-19 pandemic has greatly increased awareness of the need for expanded mobile health and telemedicine services.”

Related Links:
Purdue University
Vanderbilt University
Moi University


Gold Member
STI Test
Vivalytic Sexually Transmitted Infection (STI) Array
New
Gold Member
X-Ray QA Meter
T3 AD Pro
New
Mobile Power Procedure Chair
LeMans P360
New
Standing Sling
Sara Flex

Print article

Channels

Surgical Techniques

view channel
Image: The surgical team and the Edge Multi-Port Endoscopic Surgical Robot MP1000 surgical system (Photo courtesy of Wei Zhang)

Endoscopic Surgical System Enables Remote Robot-Assisted Laparoscopic Hysterectomy

Telemedicine enables patients in remote areas to access consultations and treatments, overcoming challenges related to the uneven distribution and availability of medical resources. However, the execution... Read more

Health IT

view channel
Image: First ever institution-specific model provides significant performance advantage over current population-derived models (Photo courtesy of Mount Sinai)

Machine Learning Model Improves Mortality Risk Prediction for Cardiac Surgery Patients

Machine learning algorithms have been deployed to create predictive models in various medical fields, with some demonstrating improved outcomes compared to their standard-of-care counterparts.... Read more

Point of Care

view channel
Image: The acoustic pipette uses sound waves to test for biomarkers in blood (Photo courtesy of Patrick Campbell/CU Boulder)

Handheld, Sound-Based Diagnostic System Delivers Bedside Blood Test Results in An Hour

Patients who go to a doctor for a blood test often have to contend with a needle and syringe, followed by a long wait—sometimes hours or even days—for lab results. Scientists have been working hard to... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.