NeuTigers, an Artificial Intelligence company spun out of Princeton University, launched CovidDeep, a clinically validated solution that can triage those needing further testing for SARS-CoV-2/COVID-19 using physiological sensors data derived from wearable devices. The CovidDeep app is 90%+ accurate 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.
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Early in the pandemic, NeuTigers realized its StarDeep™ Smart Healthcare Platform, which delivers AI[1]powered solutions to augment healthcare professionals’ productivity, could be used in the fight against COVID-19. CovidDeep was developed through rigorous clinical research and validation trials beginning at San Matteo Hospital in Pavia, Italy, during the acute phase of the COVID-19 pandemic in April 2020, with further expanded prospective field studies in hospitals in France and the United States to explore its robustness.
A powerful tool for businesses and healthcare facilities who regularly screen for COVID-19, CovidDeep is already deployed in B2B settings including multiple nursing homes and assisted living facilities in America and Europe. Designed to help keep work and medical facilities safe, CovidDeep is effective in multiple industries and use cases, and today is being made widely available.
CovidDeep works by collecting physiological sensor data from the Empatica E4 wristband, blood pressure and blood oxygen levels from any off-the-shelf, standalone monitors as well as personal health symptoms from a brief questionnaire. As a potential game-changer in the rapid and cost-effective screening of SARS-CoV-2/COVID-19, it is already being adapted to work with connected health products from Fitbit, Withings, Apple, Samsung, and other devices. The CovidDeep consumer app is expected in early 2021.
Deep Neural Networks
COVID-19 affects people’s biometrics and physiological markers in both obvious and nearly imperceptible ways. Using advanced algorithms of machine learning, CovidDeep is so sensitive it can detect changes in these physiological patterns even before they are felt by the patient and all with real[1]time analysis.
CovidDeep is powered by cutting-edge AI deep neural networks that mimic how the human brain perceives, learns, and interprets the world. NeuTigers’ research co-founders at the Department of Electrical Engineering at Princeton University 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. CovidDeep can recognize the ‘digital signature’ of SARS-CoV-2/COVID-19 and quickly identify if a person is COVID[1]positive, even if they do not have symptoms (asymptomatic).
CovidDeep is shown from the controlled clinical study at San Matteo hospital to predict SARS-CoV[1]2/COVID-19 with upwards of 90% accuracy, almost twice as effective as temperature checks and visual symptoms checks, which NeuTiger’s study and others have shown predict COVID-19 with around 50% accuracy.
“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. “Before the pandemic, our teams were using predictive models in our StarDeep health platform to monitor and screen for diabetes and mental health conditions.”
“Realizing our AI technology could be valuable in the fight against COVID-19, we quickly pivoted and developed a new solution after rigorous clinical research trials. 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,” he continued.
CovidDeep – How it Works
CovidDeep brings forth groundbreaking science as an app that can predict SARS CoV-2/COVID-19 accurately, safely, quickly, and importantly by preserving people’s privacy. 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. All data remains local to the device, is never shared, and stays securely and privately under the user’s control.
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. The process takes around 2 minutes, allowing one Empatica device, blood pressure monitor, and pulse oximeter to screen unlimited numbers of people after being sanitized between usages.
Available globally from January 12, 2021, on Android with iOS availability coming soon, users can try CovidDeep for free with unlimited screening results for seven days.
Combatting COVID – Today and Tomorrow
CovidDeep represents a critical tool in combating SARS-CoV-2/COVID-19 both today and in the future. Public health professionals and policymakers agree that rapid and mass testing is the key to controlling the spread of the virus and reopening society and the economy. CovidDeep is a powerful bridge to affordable mass testing and a highly scalable solution to efficiently triage scarce medical resources worldwide.
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“Whether helping frontline healthcare workers, employers keeping the workplace safe, assisting airlines in reestablishing consumer confidence in travel, helping students to stay in schools, or providing fast access to sporting and entertainment venues, the applications of CovidDeep are endless,” added Laoui. NeuTigers is continuing extended clinical field testing worldwide to further hone the app’s accuracy to ensure that no geographic, demographic, or ethnic biases occur. In addition to completed trials in Italy, validation field-testing studies are currently ongoing in the United States, France and planned in North Africa, Switzerland, Japan, and India.
