Predicting good sleep using computer science: Can we use machine learning to find out 'what's the best bed?'

Overview

In the Westernised world a person typically spends one third of their life in bed, with more time spent sleeping in a bed than in any other single activity. Sleep amount and quality of sleep have a direct impact on mood, behaviour, motor skills and overall quality of life. Yet, despite how important restful sleep is for the body to maintain good health, there is a comparatively small amount of studies evaluating key multi-factorial determinants of restful sleep in non-pathological, healthy adults.

We are seeking one applicant to begin 1 July 2023 to explore this. Domestic applicants are encouraged to apply.

Each student will receive an annual, tax-free PhD stipend of $32,500, along with eligibility for a fee-waiver scholarship from QUT for their degree.

Research activities

The Biomechanics and Spine Research Group (BSRG), in partnership with Sealy of Australia, has created an extensive dataset describing key sleep biomarkers – this includes biomechanical, anatomical and sleep physiology measurements for 130 adult participants. Using this dataset and proprietary data describing mattress performance, this project will use data science approaches to tease out the underlying relationships which link the physical (posture & biomechanics), psychological (comfort perception), and physiological (sleep quality) aspects of sleep. In doing this, the student will discover new understanding of how to create a well-adapted ‘sleep system’ for healthy adults.

This project will use engineering principles, data science, and advanced simulation to gain new understanding of sleep biometrics. With this new knowledge, a contemporary understanding of optimised sleep surface choices for individual people can be developed, and an evidence base for future mattress design established.

The student’s project will be based at Queensland University of Technology Gardens Point campus, in the Brisbane CBD. The project will be in the School of Mechanical, Medical and Process Engineering, within the Faculty of Engineering.

In addition to this, they will have real world research experience, with co-location at Sealy of Australia’s Research and Development headquarters, in Wacol, Brisbane.

As part of their candidature, the student will be supported to enhance their applied research experience through a 60 day industry internship, which they will complete part-time during the first or second year of the PhD candidature.

Outcomes

The project outcomes will:

• develop strategies to organise, identify, analyse and ultimately interpret multi-factorial data describing how healthy adults sleep
• develop analytical methods (eg. statistical, mathematical, programming, machine learning) to describe the complex relationship between sleep biometrics collected from human participants and lying surface mechanics
• create an analytical (machine learning) tool to predict an ideal lying surface for an individual person, such that the human-surface interaction is enhanced and/or optimised
• test  this algorithm with support from your supervisors to carry out a community based sleep study.

Skills and experience

We are seeking a motivated and highly skilled applicant to undertake a PhD research project with industry partner Sealy of Australia. This student will be a member of the newly established QUT-Sealy Centre for Biomechanics and Sleep Research.

The ideal candidate will be either:

• IT/Software Engineer (Honours)
• Data/Computer Scientist (Honours)
• hold an Honours degree in human movement or biomechanics with strong computer science/programming and machine learning experience.

Scholarships

You may be eligible to apply for a research scholarship.

Explore our research scholarships

Keywords

• biomechanics
• computer science
• engineering
• data science
• sleep

Contact

Contact the supervisor Associate Professor Paige Little via j2.little@qut.edu.au for more information, mentioning that you have seen this PhD project advertised on the QUT website.