Developing mathematical methods to infer mental health states from wearable technology

Principal investigator(s)Co-InvestigatorPhD student or Research Fellow(s)Project title

Dr Matteo Cella (KCL) and Dr Daniel Stahl (KCL)

Dr Jamie Walker (UoE) Dr Eder Zavala (UoE)

Developing mathematical methods to infer mental health states from wearable technology

 

Lay summary:

Many mental health conditions are enduring and likely to affect people for prolonged time periods. Service users, carers and the healthcare system often have to deal with crisis and relapse episodes associated with symptoms worsening. There is increasing recognition in the field that regular monitoring may be particularly important to achieve early detection of emerging problems and prevention of relapse. However, mental healthcare services currently face several challenges, including the limited availability of tools for preventing hospitalisation and the regular monitoring of patients. There is hope that mobile technology could help assess health states regularly, in real-time, remotely, and cost-effectively. However, the information that wearable devices currently provide is complex and does not correspond directly to specific indicators of mental health.

This seed corn project brings together psychologist Dr Matteo Cella and biostatistician Dr Daniel Stahl from King’s College London and mathematicians Dr Jamie Walker and Dr Eder Zavala from the University of Exeter. The team aims to develop a tool that reliably predicts emotional states associated with mental health conditions such as anxiety, low mood, and stress by analysing data collected by wearable devices. This has the potential to contribute to fulfilling a long-sought goal of empowering patients to monitor their own health conditions, improving mental health outcomes that reduce the societal costs associated with mental illness (e.g. loss of employment, welfare costs), and optimising the use of healthcare resources by preventing symptoms from becoming severe.

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