Predicting diagnosis and symptom severity in ADHD with deep learning and network analysis using EEG

Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder characterized by symptoms of inattention, hyperactivity and or impulsivity. The diagnosis and monitoring of the symptom severity are mostly based on subjective reports, while neuropsychological testing and direct classroom observations are more objective diagnosis methods, but they are time-consuming and expensive. A new cost-effective and accurate diagnosis and symptom monitoring technique is urgently needed.

This project aims to explore whether EEG can provide a quantitative and effective approach for the diagnosis and severity monitoring of ADHD. Additionally, we would like to evaluate whether an integration of advanced signal processing, network analysis and deep learning techniques would improve the diagnosis performance compared with traditional EEG analysis methods.

The successful applicant will be awarded a scholarship from Coventry University with the supervision team being drawn from Coventry University and Deakin University, Australia. The PhD Student will graduate with two testamurs, one from Coventry University and one from Deakin University, each of which recognizing that the program was carried out as part of a jointly supervised doctoral program. The program is for a duration of 3.5 years (funding only for 3.5 years, maximum allowed time 4 years) and scheduled to commence in September 2024. The PhD Student is anticipated to spend up to 12 months of the total period of the program at Deakin University, with the remainder of the program based at Coventry University.

Training and Development 

The successful candidate will receive comprehensive research training including technical, personal and professional skills. 

All researchers at Coventry University (from PhD to Professor) are part of the Doctoral College and Centre for Research Capability and Development, which provides support with high-quality training and career development activities.  

Candidate specification

Applicants must meet the admission and scholarship criteria for both Coventry University and Deakin University for entry to the cotutelle programme.

• Applicants should have graduated within the top 15% of their undergraduate cohort. This might include a high 2:1 in a relevant discipline/subject area with a minimum 70% mark (80% for Australian graduates) in the project element or equivalent with a minimum 70% overall module average (80% for Australian graduates).
•  A Bachelor’s degree in a relevant field requiring at least four years of full-time study, and which normally includes a research component which is equivalent to at least 25% of a year’s full-time study in the fourth year, with achievement of a grade for the project equivalent to a H1 standard or 80%

 OR

•  A Masters degree, with a significant research component, in a relevant subject area, with overall mark at minimum Distinction.
• • In addition, the mark for the Masters thesis (or equivalent) must be a minimum of 80%.
• Please note that where a candidate has 70-79% and can provide evidence of research experience to meet equivalency to the minimum first-class honours equivalent (80%+) additional evidence can be submitted and may include independently peer-reviewed publications, research-related awards or prizes and/or professional reports.
• Language proficiency (IELTS overall minimum score of 7.0 with a minimum of 6.5 in each component).

The potential to engage in innovative research and to complete the PhD within a prescribed period of study

Additional Requirements

The applicant is required to submit a supporting statement as part of their application. Within the supporting statement, candidates should articulate why they believe they are suited for this position. Specifically, we anticipate that the applicant will demonstrate some experience/and or knowledge pertinent to machine learning and will have good programming skills.

For further details please visit: https://www.coventry.ac.uk/research/research-opportunities/research-students/making-an-application/research-entry-criteria/

https://www.coventry.ac.uk/research/research-opportunities/research-students/making-an-application/

To find out more about the project please contact Dr Fei He:  [email protected]

All applications require a covering letter and a 2000-word supporting statement is required showing how the applicant’s expertise and interests are relevant to the project.