Looking to list your PhD opportunities? Log in here.
This project is no longer listed on FindAPhD.com and may not be available.
Click here to search FindAPhD.com for PhD studentship opportunitiesAbout the Project
Reference Number
Please refer to SCEBE-20-026-YZSF
Project Details
Resilience is our ability to recover after exposure to significant adversity, e.g., the covid-19 pandemic. There are many factors that can influence our resilience including our life experiences and support networks. Resilience can be improved using resources such as self-care techniques, mindfulness. Resilience had been shown to have a significant negative correlation with both anxiety and depression. Promoting resilience can directly impact on productivity, performance, and can improve quality of life. Measurements of resilience can be psychologist-led or self-assessment using questionnaires, although with questionnaires there can be a significant bias.
Recently, voice screening and monitoring for stress and depression have been reported. Machine-learning technology has been utilised to analyse speech samples obtained in the clinic or remotely (e.g., using a mobile App) for automated assessment of psychiatric. The technology of emotion recognition has been used to evaluate a stress resilience program in combination such as breathing and yoga. Online quantitative eye tracking using webcam has been used in emotion recognition. Also, in the field of Human Computer Interaction (HCI), a new area called affective computing has emerged with the goal of developing techniques for modelling emotions.
This project aims to study the unique role of multi-modality based smart system in managing resilience and mental wellbeing. It’ll scope and define the problem through a Multi-Disciplinary Team, including psychologists and health specialists. To enable reliable and real-time management of resilience and mental wellbeing, this project will make use of data collected and extracted from multi-modalities, such as facial expression detection, speech recognition, body movement, gesture and eye tracking. Deep learning will be applied for resilience management. Furthermore, evaluation will be conducted based on feedbacks from the Multi-Disciplinary Team, as well as end users. The smart system will be deployed as a mobile app or a plugin for online platform to provide real-time resilience assessment and support for individual to manage their resilience and mental wellbeing.
Funding Notes
See more on fees and funding. https://www.gcu.ac.uk/research/postgraduateresearchstudy/feesandfunding/
References
Director of Studies
Name: Dr Yan Zhang
Email: yan.zhang@gcu.ac.uk
GCU Research Online URL: (essential) https://researchonline.gcu.ac.uk/en/persons/yan-zhang
2nd Supervisor Name: Dr Nicola Roberts
Email: Nicola.Roberts@gcu.ac.uk
GCU Research Online URL: (essential) https://researchonline.gcu.ac.uk/en/persons/nicola-roberts
3rd Supervisor Name: Prof Huaglory Tianfield
Email: H.Tianfield@gcu.ac.uk
GCU Research Online URL: (essential) https://researchonline.gcu.ac.uk/en/persons/huaglory-tianfield

Search suggestions
Based on your current searches we recommend the following search filters.
Check out our other PhDs in Glasgow, United Kingdom
Check out our other PhDs in United Kingdom
Start a New search with our database of over 4,000 PhDs

PhD suggestions
Based on your current search criteria we thought you might be interested in these.
Deep learning-based data imputation and missing modality prediction for single-cell multi-omics data
Children’s Medical Research Institute
Flexible textile-based self-powered energy harvesting and storage system for smart wearable electronics
Cardiff University
Making a Computer-Based Tutorial Environment for Mathematics “Intelligent” : The Design, Implementation and Evaluation of a Tutorial System that Learns
Kingston University