SleepCogni: Joe Hawkins
BEng Systems and Control Engineering
I have recently graduated from the Department of Automatic Control and Systems Engineering (ACSE) with a 2:1 in Systems and Control Engineering.
My third year dissertation was awarded the prestigious Euler Award for my collaboration with local Sheffield company, SleepCogni, where I explored the possibilities of using machine learning to predict the onset of sleep. Using the coding and data analysis skills I attained during my degree, I approached the challenge by employing fuzzy logic to analyse synthetic data I created as well as factual data supplied by SleepCogni. From this I was able to identify and accurately map the physiological markers that consistently identified the stages of sleep for each of the data subjects. This work has allowed SleepCogni to continue developing their ground-breaking exploration in this extremely important area of medical research.
My course in the department of ACSE provided me with a breadth of knowledge on the topics of systems modelling, simulation and control, which I could then apply to my work with industry.
SleepCogni are at the forefront of developing a product that delivers a unique wind down process to promote sleep. The system can deliver multiple interventions that support cognitive behavioural therapy. Their patented active biofeedback intervention works through visual, auditory and tactile cues, to help users relearn sleep. The personalised biofeedback is based on the measurement of a range of physiological and behavioural measures related to sleep, to swiftly and effectively guide you towards sleep initiation. The system is made up of a handheld trigger and a bedside base-station. SleepCogni contacted ACSE’s Dr George Panoutsos to help bridge the gap between their sophisticated hardware capabilities and their challenges of capturing the analytical medical relevant data.
In your final year, each student is required to undertake an individual project. We were given over a hundred titles to choose from and the project with SleepCogni interested me the most. I have an interest in wearable devices and algorithms and this project allowed me to further my knowledge in this area.
My course in the department of Automatic Control and Systems Engineering provided me with a breadth of knowledge on the topics of systems modelling, simulation and control, which I could then apply to my work with industry. As well as the course content I received a large amount of support from my supervisor, Dr George Panoutsos throughout my project which allowed me to achieve my full potential. By working on the project I have learnt how to work with start-up businesses and SME’s, witnessing first-hand the challenges they face. This will help prepare me for my work with industry in the future.
Currently I am working as a Data Engineering and Analytics Manager for SleepCogni. Due to SleepCogni being a start-up business it means I am working in a number of areas which is providing me with invaluable experience. However, my main focus is similar to the role I had when carrying out my dissertation. Where I analysed data from the SleepCogni system with the aim of creating an algorithm which is at the heart of the diagnostics and intervention of the SleepCogni system.