BA (Hons), MSc, DPhil
Senior Research Fellow
Digital Phenotyping & Brain Health
Chris Hinds’ research explores the use of digital phenotyping methods to understand health and disease. This may involve using devices to measure physical movement, or software to assess our digital activity, or games that probe our cognition. His interest spans the development lifecycle, from the methodologies used to design new technology, the studies needed to validate them, and the informatics required to underpin their use at scale in clinical or epidemiological settings.
Brain health is a particular area of interest. Recent projects have involved working with mood, sleep and cognition. Most recently Chris has been looking at how digital methods can be used to measure the very earliest signs of pre-clinical dementia. He leads a project funded by a consortium of industry partners to design, develop, validate and then make freely available, open source, digital biomarkers for dementia, with a particular focus on smartphone and wearable devices. This work aims to set new standards and form a critical building block for the trial-ready cohorts, citizen science projects, and public health initiatives of the future.
In 2017 Chris took up the Robertson Foundation Fellowship in Digital Phenotyping at the Oxford University Big Data Institute. Before this he worked on the design and development of digital health technologies at the Oxford University Department of Psychiatry, was Head of Applications Development for Oxford Health NHS FT, played a significant role at several health-tech startups, and lectured extensively for the Oxford University Software Engineering Programme. His DPhil, undertaken at the Oxford University Computing Laboratory, considered methodologies for the design of digital health technologies, especially those using ethnographic methods; his undergraduate degree is in Computation, also from the Oxford University Computing Laboratory.
McKnight RF. et al, (2017), J Affect Disord, 223, 139 - 145
Freeman D. et al, (2017), Lancet Psychiatry
Psychoeducation and online mood tracking for patients with bipolar disorder: A randomised controlled trial.
Bilderbeck AC. et al, (2016), Journal of Affective Disorders, 205, 245 - 251
Large-scale roll out of online prospective measurement of mood symptoms in affective disorders
Knott S. et al, (2016), BIPOLAR DISORDERS, 18, 185 - 186
Gulati G. et al, (2016), J Forensic Psychol Pract, 16, 49 - 59
Geddes JR. et al, (2016), Lancet Psychiatry, 3, 31 - 39
Cognitive assessments using mobile technologies: moving beyond the inflection point
Ash J. et al, (2015)
Comparative evaluation of quetiapine plus lamotrigine versus quetiapine monotherapy in people with bipolar depression: a randomized trial (CEQUEL)
Geddes JR. et al, (2015), BIPOLAR DISORDERS, 17, 50 - 51