Building a Better Home Sleep Tracking System

Research areas


Sleep is regarded as one of our most important physiological functions, and maintenance of appropriate sleeping habits is considered vital to human health and wellbeing.  Sleep loss can result in potentially expensive and fatal consequences. Recently, there has been increasing interest in tracking and quantifying not just hours of sleep but sleep quality at a consumer level, using relatively inexpensive devices such as fitness trackers. Most of these, however, involve only one or two modes of measurement (e.g. accelerometer data, heart rate), and offer very little user control over the data acquired. By contrast, accessing high quality multi-modal sleep clinic data collection can be difficult and expensive, and can usually only be done over one or two nights for each patient/participant. 


A middle way between the two above approaches could be to combine data from consumer-level fitness tracking devices with data from electrodes measuring both EEG and respiration, sychronising these via a smartphone app which the group would develop. Challenges would include creating a system that does not, in itself, interfere with sleep, and that is comfortable to wear and resistant to movement. 

Research questions could include comparing the data acquired in this manner with both less and more sophisticated methods, for instance looking at test-retest reliability, data dropout, and concordance with psychometric measures such as participants' own ratings of their sleep, as well as tests of vigilance and attention. 
This project would be suitable for a TechLauncher group, and would also be suitable for collaborations with Psychology students. 


Students will need to have strong programming skills, an interest in (and preferably some experience with) physiological data and sleep/fitness applications, and a strong ability to work in teams, including good communication skills. A track record of app development and/or technical skills in working with integrated devices would be an advantage. 

Background Literature

Casson, A., Yates, D., Smith, S., Duncan, J., & Rodriguez-Villegas, E. (2010). Wearable Electroencephalography. IEEE Engineering in Medicine and Biology Magazine, 29(3), 44–56. 

Pantelopoulos, A., & Bourbakis, N. G. (2010). A Survey on Wearable Sensor-Based Systems for Health Monitoring and Prognosis. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 40(1), 1–12.


The student will develop an understanding of the use of integrated consumer-level devices to collect and analyse human physiological and health data, which is a rapidly growing field with many opportunities for new developments and discoveries. There is the potential for commercial applications arising from this project, so IP agreements will be essential. Depending on the student contribution, co-authorship in scientific papers or conference travel to present them may be granted.

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