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iFidget: a biofeedback device and algorithms for real-time stress intervention

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  • Full or part time
    Dr E Kanjo
    Prof D Brown
    Prof TM McGinnity
  • Application Deadline
    No more applications being accepted
  • Competition Funded PhD Project (Students Worldwide)
    Competition Funded PhD Project (Students Worldwide)

Project Description

Mood disorders conditions rank among the top health problems worldwide, with an estimated cost to the UK of ~£16 billion a year1. Despite the magnitude of this problem, there are currently no objective measures or real-time self-management interventions based on physiology or behaviour to detect and tackle episodes of mental health decline. Studies2 have shown that both the sympathetic and parasympathetic responses involved with emotional behaviour differ in individuals diagnosed with mood disorder, suggesting that it may be possible to identify stress signature of sympathetic and parasympathetic tone that can be measured through various behavioural and physiological cues.
Limited attention has been given to the design of technological management and interventions for individuals who might benefit from self-support tools. Existing technologies commonly range from online therapy programs3 and self-help systems, to designs that supplement psychotherapy by providing additional content to the therapy5. These systems are relying on users to act, to be able to recognise and/or self-report accurately to information in relation to their mental health. Users often do not know how to respond, therefore providing specific direct physical feedback (e.g. tactile or vibration) may ameliorate this effect. Also, the difficulty in accessing possible vulnerable and underserved groups may have made it challenging to design more effective technological interventions that can be tailored to their needs, where technology can have a life-changing impact.
The aim of this project is to design and develop novel technologies supporting emotional regulation in depression and anxiety through biofeedback. The developed prototypes will integrate wearable biosensors and electronic hardware for capturing emotional response such as heart rate variability and respiration, and for mapping them for real time visual, audio, or haptic feedback.

This project will design and develop novel technological tools that can sense and model behaviour and deliver feedback to regulate emotions (including vibrations and light, and sound, etc).

To be eligible to apply, you must hold (or expect to obtain by 1st October 2018) a 1st Class/2.1 UK honours degree (or equivalent as verified by UK Naric and the NTU International development Office) in Computer. For applicants holding a 2.2 UK honours degree this must be supported by a Masters at “Merit” level (or equivalent as verified by UK Naric and the NTU International development Office) as an additional qualification.

For informal enquiries, please contact Dr Kanjo – [Email Address Removed] or 0115 848 4820

Funding Notes

This studentship competition is open to applicants who wish to study for a PhD on a full-time basis only. The studentship will pay UK/EU fees (currently set at £4,195 for 2017/18 and are revised annually) and provide a maintenance stipend linked to the RCUK rate (this is revised annually and is currently £14,553 for academic year 2017/18) for up to three years*. The studentships will be expected to commence in 2018.

How good is research at Nottingham Trent University in Computer Science and Informatics?

FTE Category A staff submitted: 14.25

Research output data provided by the Research Excellence Framework (REF)

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