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Combining WiFi Sensing and Artificial Intelligence to Monitor Patient Health and Well-Being

An aging population is one of many reasons health care is among the biggest social and economic issues of our time. The need to assist people with disabilities, dementia, and mental health challenges has increased pressure on our limited resources for around-the-clock monitoring of activity, especially within residential care.


Widely adopted and established activity monitoring techniques include wearable devices, camera-based vision systems, and ambient sensors. However, these options come with major drawbacks including physical discomfort, privacy concerns, and limited detection accuracy.


The solution? Passive WiFi sensing technology.


The concept of passive WiFi sensing, specifically for residential healthcare, is a natural extension of the research conducted at University College London, which proved the concept of passive WiFi radar. Originally, researchers developed this system to enable undetectable, through-wall surveillance for hostage and counterterrorism scenarios. But the addition of artificial intelligence empowered the researchers to scale the system to meet the needs of modern health care.

 Passive WiFi Sensing for In-Home Activity SensingPassive WiFi Sensing for In-Home Activity Sensing

In this context, the term passive means that users do not need to actively transmit a wireless signal to receive the radar echo. Instead, the passive WiFi prototype leverages the wireless signals that already inundate our urban airways.


Using WiFi Radar to Passively See Through Walls


Passive WiFi sensing has obvious advantages compared to more established monitoring techniques. Passive WiFi radar is “receive only,” which makes it convenient, low power, and unobtrusive. Health care professionals can take advantage of these features to easily monitor vital signs, life-threatening events, and the daily activity of their patients.


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The Developers


Dr. Bo Tan, Coventry University 
Qingchao Chen, University College London 
Dr. Kevin Chetty, University College London 
Professor Karl Woodbridge, University College London


Learn more about this innovative research from the developers themselves >>


Explore NI software defined radio products >>