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





AI-Powered Coronavirus-Screening App Uses Wearable Biosensors to Detect COVID-19 within Two Minutes

By HospiMedica International staff writers
Posted on 21 Jan 2021
Print article
Image: AI-Powered Coronavirus-Screening App (Photo courtesy of NeuTigers)
Image: AI-Powered Coronavirus-Screening App (Photo courtesy of NeuTigers)
A new AI-powered solution can triage those needing further testing for SARS-CoV-2/COVID-19 using physiological sensors data derived from wearable devices.

NeuTigers (Brooklyn, NY, USA), a spinout of Princeton University, in partnership with Rajant Corporation (Malvern, PA, USA), has launched the CovidDeep app which has an accuracy of more than 90% in predicting whether a person is virus-free or virus-positive, and is twice as effective as current triage tools, such as temperature checks and questionnaires.

COVID-19 affects people’s biometrics and physiological markers in both obvious and nearly imperceptible ways. CovidDeep is powered by cutting-edge AI deep neural networks that mimic how the human brain perceives, learns, and interprets the world. Scientists at NeuTigers used proprietary deep neural networks to learn from hundreds-of-thousands of digital health data points and a specific questionnaire in SARS-CoV-2-positive and healthy participants. They identified patterns in the sensor physiological readings such as Galvanic Skin Response (GSR), Skin temperature, Heart Inter-beat Interval (IBI), Blood pressure, and Blood oxygen saturation levels (SpO2) that are consistent with how COVID-19 impacts the body.

Users simply answer a questionnaire regarding symptoms and health history (based on CDC guidelines) and input their health sensor’s data. Data is entered by connecting CovidDeep to an Empatica E4 Wristband as well as inputting blood pressure and blood oxygen readings using any off-the-shelf device. CovidDeep then analyzes the data and provides a prediction as to whether someone is likely to be negative or positive for SARS CoV-2/COVID-19. Using advanced machine learning algorithms, CovidDeep detects changes in physiological patterns even before they are felt by the patient and all with real-time analysis. CovidDeep recognizes the ‘digital signature’ of SARS-CoV-2/COVID-19 and quickly identifies if a person is COVID-positive, even if they do not have symptoms (asymptomatic). The process takes around two minutes, allowing one Empatica device, blood pressure monitor and pulse oximeter to screen unlimited numbers of people after being sanitized between usages.

In a controlled clinical study, CovidDeep was shown to predict SARS-CoV-2/COVID-19 with upwards of 90% accuracy, almost twice as effective as temperature checks and visual symptoms checks, while NeuTiger’s own study and others have shown that it can predict COVID-19 with around 50% accuracy. CovidDeep has already been deployed in B2B settings, including multiple nursing homes and assisted living facilities in the US and Europe, and is expected to become a powerful tool for businesses and healthcare facilities who regularly screen for COVID-19.

“Advances in machine learning and the proliferation of medical-grade sensors in everyday consumer wearables has led to a new era in which we can predict and identify the onset of a myriad of diseases,” said Adel Laoui, CEO and founder of NeuTigers. “Initially meeting the urgent need for mass screening in the business environment, CovidDeep is set to expand to a wider consumer offering in early 2021,” added Laoui.

Related Links:
NeuTigers
Rajant Corporation


New
Gold Member
X-Ray QA Meter
T3 AD Pro
Gold Member
Real-Time Diagnostics Onscreen Viewer
GEMweb Live
New
Standing Sling
Sara Flex
New
Cannulating Sphincterotome
TRUEtome

Print article

Channels

Surgical Techniques

view channel
Image: Schematic diagram of intra-articular pressure detection using a sensory system in a sheep model (Photo courtesy of Science China Press)

Novel Sensory System Enables Real-Time Intra-Articular Pressure Monitoring

Knee replacement surgery is a widely performed procedure to relieve knee pain and restore joint function, with over one million surgeries conducted annually. However, 10%-20% of patients remain dissatisfied... Read more

Patient Care

view channel
Image: The portable biosensor platform uses printed electrochemical sensors for the rapid, selective detection of Staphylococcus aureus (Photo courtesy of AIMPLAS)

Portable Biosensor Platform to Reduce Hospital-Acquired Infections

Approximately 4 million patients in the European Union acquire healthcare-associated infections (HAIs) or nosocomial infections each year, with around 37,000 deaths directly resulting from these infections,... 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.