Developing data assimilation and machine learning approaches to analysing complex multimodal biometric data towards a more personalised and adaptive mental health care
The PhD research will be to design and implement personalised adaptive computer-based interventions to support mental health issues, for example, in people experiencing anxiety disorders. These interventions may be software-based apps to support mindfulness practices, gamebased systems or virtual / augmented reality experiences. However, to create the adaptive component of these systems, the team will look at the types of emotion, as measured by multimodal biometric and physiological responses, which are typically being experienced by the volunteers. Once profiled, computerised-based interventions will be developed, which will adaptively respond and encourage a shift from negative emotions to positive ones as a result of the implementation of personalised biofeedback loops.
More information on the project, from potential impact to references, can be found on the accompanying PDF.
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