Project Title: Affective Computing for Real-time Assessment of Pain
Assessing pain in children and in adults unable to self report information about their pain is difficult. Therefore, clinical pain assessments are typically derived, aided by nurses or family members. However, several previous studies have shown nursing staff may have difficulty accurately estimating pain and often underestimating pain, particularly among paediatric patients and adults with confusional states. Family members and carers are generally more in tune with their relatives pain levels, but may not always be available. Therefore, accurate pain assessment is important as it informs pain control strategies for the patients comfort, but also for recovery.
The PhD researcher will investigate how: 1) to distinguish between patterns of facial expressions at different pain levels in participants that have been given stimuli below and above pain threshold and 2) to design a cost-effective solution that addresses the challenge towards big data of facial expressions recorded over a period of time for detecting and assessing pain. More specifically, the PhD researcher will explore the following questions:
- Given a sequence of faces from video input at what frame level do we decompose a face into separate non-rigid components in order to automatically label the dataset and achieve learning of pain on an automatic classifier?
- Is there an inherent feature that can discriminate between detection of “genuine” versus “faked” pain?
We will determine whether such an automated pain assessment tool can be easily integrated into the clinical workup and contribute to current clinical pain assessment methods and treatment paradigms. Such technology could potentially advocate for children and adults with communication deficits who are in pain when their family members are unavailable to notify medical staff regarding their relatives pain level. For this project we seek a PhD candidate with a background in machine learning or related fields and excellent technical skills in C++ and Matlab.
This project will enable the student to develop skills in Computational Intelligence with direct impact on Digital Economy and Healthcare. The student will be encouraged to attend relevant conferences, participate in the University’s Doctoral Researcher Development Programme (DRDP) and have the opportunity to obtain a Postgraduate Certificate in teaching and learning.
This PhD project is offered on a self-funding basis. It is open to applicants with funding or those applying to funding sources. Details of tuition fees can be found at https://www.westminster.ac.uk/courses/research-degrees/fees-and-funding
Informal project enquiries and Director of Studies: Dr Anastassia Angelopoulou (email@example.com)
Supervisory team: Prof. Tony Towell (A.Towell@westminster.ac.uk)