Andrew Neary , MSc in BME
Scott Hyland, MSc in BME
Georgy Namm, BEng in Mathematics & Physic
The project aims to assess the feasibility to develop a pupilometer via the mobile app. Setup for the acquisition of eye images included a mobile phone on a tripod, another mobile phone used as a flash generator and a few filters to obtain different intensities of light. Videos of the eye were acquired in a normal lighting condition, followed by flashes of light at different intensities with some resting time in between. Afterwards, some parameters (e.g. pupil size changes) were calculated out of the processed frames. These parameters showed how the pupil reacted to light and could be used to assess non-physiological behaviours. Finally, these results proved that pupil reaction to light can be evaluated even with low budget instruments. Future developments may include a Pupillometer application that automatically assesses patients’ conditions.
Ms Natasha Vakharia, MEng Student
The project entails usage of previous anonymised ECG data where 42 healthy subjects were subjected to the Stroop Test and their HRV was measured for 7 minutes before that period and 7 minutes after. The Stroop test induces acute stress therefore I will analyse the difference between the acute stress periods and base periods in an ultra-short time period. After the analysis is done, I will choose an analysis to focus on whether it be in the non-linear domain or time-frequency domain.
Mr Gordon Charlie-BEng Student
Mr Gordon Charlieis a BEng Student working on HTA analysis. The aim of this project is to identify the differences between the electrical environment of surgical theatres in low/medium income countries (LMIC), in particular Benin, and ones in the UK. Then using this information suggest how medical devices and their designs can be adapted to create a safer for environment for patients and medical staff in LMIC surgical theatres.
- Mr Claudio Guerra, Visiting Research Assistant, The University of Parma
- Miss Yiyu Li, MSc Student in Communications and Information Engineering
- Mr Sacha Gozlan,MSc Student in Electronic Engineering
Miss Sajeevie Pinnaduwe Hewa-BEng Student
Miss Sajeevie Pinnaduwe Hewa was a BEng Student in Engineering Business Management. She worked on Analytic Hierarchy process (AHP) to decide whether to adopt laparoscopy or open surgery in terms of prioritizing the different factors affecting the decision. AHP was used to solve this problem by constructing a consistent framework for step-by-step decision-making.
Mr Karan Hunjan-MEng Student
Mr Karan Hunjan was a MEng student in Electronic Engineering. He worked on early detection of disease worsening. In particular, he investigated the impact of mental stress on Heart Rate Variability, using machine learning predictive modelling. The study investigated the use of ultra-short (2 minute) HRV measurements by comparing their analysis with the more standard short (5 minute) measurements. It aimed to test whether or not a 2 minute recording, once processed, is significant in showing indication of significant physiological change such that a diagnosis could be completed or actions could be taken to address negative changes.
Miss Ruby Davies-BEng Student
Miss Ruby Davies was a BEng student in Engineering Business Management. She worked on Analytic Hierarchy process (AHP) applied to cardiology. She created a survey to discuss and analyse whether AHP is a realistic tool in cardiology to help healthcare professionals make decisions about the care of their patients finding a solution to a problem based on several different opinions within the same ward. Therefore, the aim of my project was to determine whether AHP is a useful tool when bringing different opinions together to decide on the best outcome, or whether AHP is not possible when there are many different opinions.
Mr Xu Haotian- MSc Student
Mr Xu Haotian was a MSc student in Communications and Information Engineering. He worked on mental stress detecion via ultra-short Heart Rate Variability analysis using wearable sensors. The study aimed to find out about the limit of existing methods to detect stress using wearable devices, as well as exploring new and alternative solutions. By analysing 5-minute, 3-minute, 2-minute, 1-minute, and 30-second segments of ECG data from 42 students under rest and stress conditions.
Miss Erin Charest-MSc Student
Miss Erin Chest was MSc student in Biomedical Engineering. She worked on actigraphy signals, investigating the difference between accelerometers signals acquired on the chest and wrist to assess sleep qiality. She used advanced signal processing to monitor sleep patterns.