Shazam for lungs: can your phone hear your lung condition?

Apps can tell us the name of that song that’s just on the tip of your tongue, how many calories you’re burning or how much sleep we’re getting. But can our mobile phones tell us about our lung health?

Right now, lung health diagnosis can be slow, sometimes taking years for people to get the right diagnosis and the right treatment. It often also requires specialist equipment, such as spirometry tests, which are hard to access and can be hard to complete. This can mean that people end up being diagnosed at the point of emergency care in A&E, which puts pressure on an already overstretched service. Sometimes, people’s lungs are irreversibly damaged by that point.

So, we challenged engineers, AI specialists, and lung health researchers to push the diagnosis of lung conditions into the 21st century. They’ve developed four projects using everyday technology that will make diagnosis and monitoring of lung conditions simple, quick and accessible.

Can your phone hear inside your lungs?

Project name: AirTime: AI-enabled mobile first screening for early respiratory disease detection. 

This project, led by Professor Liangxiu Han, Manchester Metropolitan University, uses AI technology to measure both your chest motion and your breathing sounds to understand your breathing pattern. 

Your breathing sounds will be captured through your phone’s microphone – things like how many breaths you’re taking per minute, how fast your ribcage moves when you breathe in or out and whether you’re making audible wheezing sounds. Your chest movements can be tracked using your phone’s motion sensors. All you need to do is lie down and place your phone on your chest. 

The app then combines both of these things and lets you know what’s happening in your lungs. If any abnormalities are detected, it recommends you contact your doctor. It also stores data about your breathing over time, meaning you can share these patterns with other healthcare professionals involved in your care.

This app could help people feel more confident in how they’re breathing, empower them to monitor their lung health at home and know when to go and see their GP. This could help ease the pressure on the NHS by reducing the number of people who need to go to hospital for breathing tests or in emergencies. 

What can your facial expressions tell us about your lungs?

Project Name: LungSight: visual and acoustic screening for early detection of lung conditions

The impact of struggling to breathe can often be seen in our facial expressions, even to the naked eye. Tiny muscles in our faces, and the way they move, can tell us a lot about how our lungs are performing. This project led by Moi Hoon Yap, Manchester Metropolitan University, wants to use visual data captured by phone cameras, plus audio data through the microphone, to understand more about how people are breathing.

The app will allow your phone camera to track micromovements in your facial expressions. It will also record chest motion, voice patterns, wheeze, and stridor, which is a high-pitched wheezy sound when breathing. By combining these two sets of data – audio and visual – this app will be able to give a measure of how well people are breathing. 

Hey Siri, do I have a lung condition?

Project name: Audio clinical history: diagnosis through speech patterns 
 
This project, led by Himanshu Kaul, looks at what speech patterns can tell us about your lung capabilities. 

The way we speak will change depending on how well we breathe. People who are struggling for breath will naturally have different speech patterns to people who aren’t - something as simple as being out of breath from running for the bus can really change the way we talk.  

For people with lung conditions, variation in speech patterns can tell us something about risk to their lung health, such as an upcoming asthma attack for example. This app wants to make use of virtual agents, similar to Siri and Alexa, to monitor and track breathing patterns to help determine lung capacity. This in turn will help people understand their lung health risks and even inform diagnosis. This app is accessible, easy to engage with, and provides a measure of lung health from one of the biggest negative impacts struggling to breath can have on a person's everyday life – altered speech. 

Hold the line: adapting landlines with AI 

Project name: Sound check: early detection of lung disease

This project, also led by Dr Himanshu Kaul at the University of Leicester, uses AI to analyse your voice and breathing sounds from everyday phone conversations to assess how your lungs are functioning. It’s similar to the project above but also includes adaptions for landlines so that people without smartphones can access it.  

This AI model creates a personal sound profile and will provide real-time analysis of how well you’re breathing. It also has a built-in virtual referee – a mechanism that can recommend referral to a healthcare professional for further assessment if your voice and breathing pattern doesn’t match your usual profile. For those with a camera on their phone, lip and facial movements can be tracked and profiled too. 

This is a simple, easy-to-use method that can support early detection of lung disease by identifying lung irregularities and support people’s care by referring people to a healthcare professional.

Transforming everyday tech into powerful health tools 

These projects show how the technology we use every day could transform the way we understand and care for our lungs. By turning smartphones, microphones and cameras into powerful health tools, researchers are exploring new ways to spot the early signs of lung disease, track changes over time, and help people get the right support sooner. That means fewer missed diagnoses, less pressure on hospitals, and more people able to understand their own lung health from home.

These projects support the ambitions of the Lung Research Grand Challenges led by Asthma + Lung UK. The Grand Challenges call for bold, cross-disciplinary ideas that can transform prevention, diagnosis and treatment for the millions of people affected by lung conditions. By bringing together engineers, AI experts and lung health researchers, these projects show exactly what that kind of collaboration can achieve.