The world is currently facing a mental health crisis post pandemic.

The World Health Organisation estimates that nearly a billion people worldwide are living with a mental disorder. In Europe around half of young people in the EU and a quarter of adults have unmet mental health needs whilst in the UK 8 million people in England with mental health problems cannot get specialist help because they are not considered sick enough to qualify. 

These are sobering and miserable statistics. That is why in 2019 I and some of my colleagues at the University of Nottingham set up Blueskeye AI. 

Building on 18 years of academic research in the field of affective computing and social systems processing we set out to create the most-used technology for ethical machine understanding of face and voice behaviour trusted  to measure the mind through the use of ubiquitously available, affordable technology.

Our B-Healthy software allows our customers to build companion apps that use machine learning to objectively and automatically analyse face and voice data (the only company in the field using both), to interpret medically relevant expressed behaviour and help clinicians, patients and their friends and families assess, treat  and monitor health, mood and mental state.

Our technology is clinical grade. It has been and continues to be tested in extensive clinical trials and investigations to prove both its efficacy and safety. 

But how to make our technology available to people, swiftly and easily the world over? 

With over an estimated  6 billion smartphones worldwide it was obvious to us that mobile technology was a key tool in the fight to address the growing mental health crisis. 

That is why we put smart, mobile phone technology at the heart of our design, and created a software development kit that will allow anyone to create their own apps that make use of our ground-breaking technology. The integral microphone and video make smartphones ideally suited to the capture of face and voice data. Data that can be gathered whilst users interact with their phones, undertaking specific, carefully designed tasks such as reading stories, playing games or journaling.

A machine learning algorithm analyses the face and voice of the user during these tasks, producing first an intermediate output of objective and human-interpretable characteristics of face and voice behaviour over time, which is then in turn used as the input to another machine learning algorithm which uses well established mental health rating scales to assess mood and mental state. 

Whilst we continue to test and validate our technology in clinical settings with specific therapeutic contexts the technology should be used by people running clinical trials, or be integrated into non-clinical health and wellbeing apps allowing users to monitor mood and signpost them to sources of help and support.  

Once validated the software can be used as a diagnostic aid to clinicians for a range of mental health conditions. 

Designing for mobile phone application has meant that our algorithms must be small and fast enough to run on people’s phones without draining their batteries. We do this using proprietary inventions that make our algorithms super small and fast.

Using mobile phones also enhances privacy giving people total control over their own data. By processing your face and voice data directly on your phone and not in the cloud, you can rest assured that that data never leaves your phone. Users can use familiar security measures to protect their data with the phones operating systems’ security measures (FaceID, finger print, PIN) to prevent any unauthorised access. Users can choose who they share their data with, and when they do it is always over end-to-end encrypted channels.

The combination of affective computing and mobile technology presents one of the best chances of meeting the growing unmet need for support with anxiety and depression that is growing across the world. It can never replace the role of trained professionals but whilst there remain too few to meet growing demand it can offer some help.

We are now keen to take this further and want to work with Clinical Research Organisations or Pharmaceutical Companies who would like to learn more about B-Healthy and put our technology to the test

Get in touch at

Our Founding CEO, Michel Valstar, adds a little more


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