OTTER-A uses wearable and other monitoring to collect continuous health data after an asthma attack, aiming to identify patterns that show recovery or early deterioration. Project Summary Failing to detect and respond to deteriorating asthma costs lives. Each year, patients experience avoidable attacks and unnecessary admissions because warning signs are missed. The days after hospital discharge are especially high-risk. Current monitoring of asthma is inadequate, relying heavily on self-report and lacking objective, timely signals. Wearable sensors allow continuous capture of physiology in real-world settings. Beyond single measures such as heart rate, respiratory rate and cough frequency, wearables can reveal complex physiological patterns, known as digital signatures. Continuous multimodal physiology from wearables has not yet been applied in adult asthma care, leaving a critical gap. This programme of work will define digital signatures of asthma through multimodal wearable data integrated with clinical outcomes. We will generate a unique dataset linking high-dimensional physiology with clinical trajectories, enabling discovery through machine learning across rest, activity and sleep transitions, and providing mechanistic insight into altered physiological coordination. We will examine how digital signatures vary across asthma phenotypes and recovery trajectories and evaluate their potential to serve as continuous markers of lung physiology, supporting personalised monitoring. The discoveries made during this research will lay the foundations to minimise the high-risk period following discharge, reduce readmissions, and pave the way for proactive monitoring. Primary Contact Principal Investigator | Dr Luke Daines – General Practitioner and data scientistLuke.Daines@ed.ac.uk Key People NameRoleLuke DainesPrincipal InvestigatorVern PereraClinical Lecturer in General Practice & Primary CareTony FalodunMedical Student Key Publications Luke Daines | University of Edinburgh Research Explorer Key Collaborations Sibel Health, USA Lothar Medical, Germany Professor Chris Brightling, University of Leicester, UK Professor Will Dixon, University of Manchester, UK Dr Amy Chan, University of Auckland, New Zealand Dr Annemarie Docherty, University of Edinburgh, UK Professor Ioannis Vogiatzis, Northumbria University, UK Professor Jean Bousquet, University Hospital Montpellier, France Professor Jenni Quint, Imperial College London, UK Professor DK Arvind, University of Edinburgh, UK Funders This work was supported by the Wellcome Trust [333409/Z/25/Z] Project timeline 01/10/2026 to 30/09/2031 Scientific themes Asthma; Wearable Monitoring; Digital Signatures; Hospital to Community Methodology keywords Health Data Science; Multimodal data; Digital Biomarkers; Signal Processing Related Links Primary Care Data Discovery Research Group This article was published on Friday 2 October 2026
