Syed Ahmar Shah

Syed Ahmar Shah moved from the MRC Brain Network Dynamics Unit at the University of Oxford to take up a Chancellor’s Fellowship here in the Usher Institute and Informatics at the University’s Medical School, bringing with him a strong background in biomedical engineering and an impressive track-record in inter-disciplinary projects involving health care professionals, statisticians and fellow engineers. “I have rich experience of collaborating with health care professionals, allowing me to develop unique perspectives in applying engineering techniques to solve problems in healthcare,” says Dr Shah. He has also co-authored over 25 peer-reviewed publications, and holds two patent file applications. His expertise ranges from signal processing and machine learning applied in healthcare to wearables and digital health system design. In addition, Dr Shah offers training workshops on Data Science application to staff in all kinds of organisations. “My personal research experience has mostly been in healthcare,” he adds, although he has undertaken projects in other areas as well.

The demand for Dr Shah’s expertise in biomedical and clinical settings is entirely understandable in the context of the number and severity of long-term health conditions that people have to manage. For example, asthma affects five million people in the UK alone, including more than one million children, and globally the number of sufferers exceeds 330 million. There is no cure for asthma, and because there is no single, definitive cause there is a risk of it not being recognised and treated appropriately. And even when diagnosed, there remains an issue of adherence to treatment, which can be linked to a lack of patient-centred thinking in the design and delivery of those treatments.

Dr Shah is currently co-supervisor, along with Usher Institute colleague Professor Hilary Pinnock, of a project on the application of data-driven technologies for asthma self-management, under the auspices of the Asthma UK Centre for Applied Research. The project aims to “identify objective measures that can unobtrusively be captured with smartphones and wearable devices.” Given the near-ubiquity of smartphones and the proximity they enjoy in our day-to-day lives, using them to encourage positive behavioural interventions in long-term health conditions is one of the most attractive aspects of their use. Moreover, in line with Asthma UK’s commitment to involving patients in the development and application of new methods to manage their condition, the project features patient-centred design workshops and focus groups. The project is also looking at developing signal processing algorithms so that useful information from the personal digital devices can be accessed, and will create predictive modelling techniques using machine learning to convert the metrics into effective early warning system for patients.