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Details of Grant 

EPSRC Reference: EP/H017178/1
Title: Pain rehabilitation: E/Motion-based automated coaching
Principal Investigator: Berthouze, Professor NL
Other Investigators:
Williams, Professor A
Researcher Co-Investigators:
Project Partners:
Department: UCL Interaction Centre
Organisation: UCL
Scheme: Standard Research
Starts: 04 May 2010 Ends: 31 January 2015 Value (£): 1,154,532
EPSRC Research Topic Classifications:
Biomechanics & Rehabilitation Computer Graphics & Visual.
Image & Vision Computing
EPSRC Industrial Sector Classifications:
Healthcare
Related Grants:
EP/H016988/1 EP/H017194/1
Panel History:
Panel DatePanel NameOutcome
20 Nov 2009 ICT Prioritisation Panel (Nov 09) Announced
Summary on Grant Application Form
Almost 1 in 7 UK citizens suffer from chronic pain, much of which is mechanical lower back pain with no treatable pathology. Pain management rehabilitative programs suffer from two shortcomings: (a) there are too few resources in the health care system to treat all patients face-to-face; (b) current approaches fail to integrate treatment of interrelated physiological and psychological factors. Combining expertise from engineering, clinical health sciences, and industry through a multidisciplinary team of investigators and advisors, this proposal seeks to address both shortcomings by (a) developing a set of methods for automatically recognising audiovisual cues associated with pain, behavioural patterns typical of pain, and affective states influencing pain and activity, and (b) integrating these methods into an interactive computer system that will provide appropriate feedback and prompts to the patient based on his/her behaviour measured during self-directed exercise and fitness-building sessions. This intelligent system will enable and motivate patients to continue their progress in extending activity inside (and in the longer term, outside) the clinical environment and thus will facilitate their reintegration into social and working life.In doing so, the project aims to make major contributions in a number of research areas. First, the project will significantly expand the state of the art in the field of emotion recognition by extending current methods in affective body gesture recognition, facial expression recognition and affective vocalisation recognition to deal with naturalistic rather than acted emotional expressions. This entails theoretical and practical contributions to important challenges such as detection and tracking of human behavioural cues in real world unconstrained environments, spatiotemporal analysis of complex dynamic stimuli such as non-linguistic vocalisations, facial expressions, and body movements, and spatiotemporal fusion of multimodal data streams in which constraints of synchronisation are relaxed. Second, the project will advance our understanding of how affect and pain-related moods such as fear, depression, and frustration in particular, interact with motor behaviour to not only modify pain expressions, but also to produce guarded movements that can exacerbate pain or worsen disability. This, in turn, will contribute to the body of work on cognitive behavioural models of pain to improve the diagnosis and management of pain behaviours. Finally, the project will contribute a novel user-centred approach to developing patients' understanding of their body movement during self-directed therapy; it will also identify what type of feedback best promotes engagement and encourages persistence, and offsets the negative effects of pain-related anxiety, frustration, and low-mood. Patients, clinicians and members of the advisory team will be periodically involved in the design of the interface and the testing of the system through design workshops. The system will eventually be made available for long term testing to the Pain Management Centre of the National Hospital of Neurology and Neurosurgery, London.
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