black smartwatch on human hand
Early detection of viral infections may be as easy as wearing a smartwatch.
Source: Purdue University photo/John Underwood

A smartwatch-based algorithm to detect viral infections

Purdue University engineers and physIQ have developed a viral detection algorithm for smartwatches. The embedded app collects physiological data as patients are monitored remotely.

This innovation will be the result of a collaboration between physIQ and university engineers. The algorithm will be commercialized by physIQ, which develops solutions designed to improve health care outcomes by applying artificial intelligence to real-time physiological data from wearable sensors.

The research was led by Craig Goergen, Purdue's Leslie A. Geddes Associate Professor of Biomedical Engineering. "Smartwatches are well-suited for the detection of early viral infection, including COVID-19," Goergen said. “Infections can happen at any time, making the continuously tracked data available through an individual's smartwatches uniquely suited to identify the earliest signs of illness. In particular, knowledge of a person's usual heart rate and respiratory during sleep and activity over long periods of time is especially valuable for detecting subtle changes from normal.”

App compared with ‘gold standard’ biosensor data

The research involved a study of 100 participants, including Purdue students, staff and faculty, to determine whether wearing a smartwatch to collect data was practical, unobtrusive and user-friendly. Each participant received a Samsung Galaxy smartwatch with a pre-loaded physIQ app to collect data. Along with the smartwatch, they also wore FDA-cleared adhesive chest-based biosensors to capture a single-lead electrocardiogram signal and multiple other parameters for five days of continuous monitoring. Goergen's lab analyzed data from the app remotely using physIQ's cloud-based accelerateIQ™ platform.

Data from the chest patches were processed by physIQ's U.S. Food and Drug Administration-cleared AI-based algorithms in deriving heart rate, respiration rate and heart rate variability. These data served as "gold standard" references to compare with data from the smartwatches.

"The algorithms for enabling early detection are built off physiological features derived from the biosensor data collected by the smartwatches," said Stephan Wegerich, physIQ's chief science officer. "Generating accurate and robust physiological features forms the input to subsequent viral detection algorithms. This requires the development of sophisticated signal processing and machine learning algorithms. Combined, these make the most out of smartwatch biosensor data, which is a big part of our collaboration with Purdue."

The viral infection detection algorithm complements physIQ's other health care applications. The goal across all of physIQ's applications is the ability to characterize dynamic human physiology over time, whether it is for assessing the efficacy of a new therapy, safety monitoring during treatment or general wellness.

"The collaborative nature of our relationship and work with Purdue University has the potential to greatly expand physIQ's physiological monitoring applications that can be targeted to a wide range of clinical needs using the pinpointIQ and accelerateIQ platforms," said Dr. Steve Steinhubl, physIQ's chief medical officer and Purdue alumnus.

Subscribe to our newsletter

Related articles

Decentralized patient monitoring: Sensors quickly detect changes in vital signs

Decentralized patient monitoring: Sensors quickly detect changes in vital signs

The Fraunhofer Institutes project M³Infekt aims to develop a multi-modal, modular and mobile system of sensors for monitoring infectious diseases.

Patches detect when a viral disease is getting worse

Patches detect when a viral disease is getting worse

Xsensio has been awarded CHF 1.8 million in EU funding to adapt its Lab-on-Skin sensing patches so that they can detect when a viral illness like the flu or COVID-19 is about to get worse.

Smart ring detects COVID-19 early

Smart ring detects COVID-19 early

According to new research, the Oura smart ring is indeed suitable for detecting COVID-19 infection up to three days before symptoms appear.

AI, App provide at-home assessment of coronavirus risk

AI, App provide at-home assessment of coronavirus risk

A coronavirus app coupled with machine intelligence will soon enable an individual to get an at-home risk assessment based on how they feel and where they've been in about a minute.

Electronic skin – the next generation of wearables

Electronic skin – the next generation of wearables

Electronic skins will play a significant role in monitoring, personalized medicine, prosthetics, and robotics.

Wash-and-wear biosensors

Wash-and-wear biosensors

A process turns clothing fabric into biosensors which measure a muscle’s electrical activity as it is worn.

Wearables must demonstrate efficacy in respiratory care

Wearables must demonstrate efficacy in respiratory care

Wearables are becoming a trend in respiratory care and many products are being developed to monitor patients remotely. But how much can these tools really help clinicians?

Smart bandage shows promise for wound management

Smart bandage shows promise for wound management

Wearable sensor detects multiple chronic wound biomarkers to facilitate timely and personalised wound care.

No needles required for glucose levels monitoring

No needles required for glucose levels monitoring

Researchers have developed a first-of-its-kind wearable, noninvasive glucose monitoring device prototype.

Popular articles

Subscribe to Newsletter