The aim of this project is to develop the analysis of complex, high-dimensional, functional data collected from research into sleep, glucose and cardiometabolism. The identification of zeitgebers in sleep/activity, light and temperature, and their prediction of patterns in glucose and melatonin, will be explored. Ambulatory blood pressure is measured using personally-worn devices.

The outcome is blood pressure measured over time and the exposures of interest are age and sex, with adjustment for the usual confounders.

These types of data are becoming more widespread as the technology develops for personal measures of real-time events. The overarching characteristic is that they produce patterns over time. A recent review (Ullah & Finch, 2013) concluded that there is a lack of appreciation of the value of FDA for biomedical problems.

The aim of the proposed project is to develop clinically relevant statistical techniques for analysing real time complex data made available through recent advances in ambulatory physiological monitoring systems, and thereby establish:

1. the strengths and weaknesses of each statistical and methodological technique for generating comprehensive and holistic analyses of real time complex data series;

2. the extent to which these statistical techniques might offer more sophisticated interpretations of real time physiological data recorded from free-living patients, and thereby improve the clinical acuity of aetiological, diagnostic and prognostic investigations; and

3. the most appropriate format(s) in which such techniques might be made available for non-specialist biomedical technicians and clinicians to optimise the impact of these techniques on aetiological, diagnostic, prognostic and therapeutic decision-making.

A dedicated Work Package for each of these three objectives will involve an assessment of empirical evidence drawn from:

Work Package 1. continuously recorded measurements of interstitial glucose concentration, activity, ambient temperature and light from free living pregnant women with gestational diabetes in order to identify any occult glycaemic abnormalities capable of predicting macrosomia and/or abnormal neonatal glycaemic control - data that will support a robust comparison of the different analytical techniques examined;

Work Package 2. clinically relevant real time physiological data series provided by project partners from the commercial (industrial) and public (healthcare) sectors using recent advances in ambulatory monitoring systems for: body temperature; ECG, EMG and EEG; respiration; blood pressure; heart rate; and blood oxygenation - data that will allow the team to assess the generalisable utility of the analytical techniques developed in WorkPackage 1; and developmental workshops with commercial and public sector partners where mechanisms and associated tools for supporting the uptake, application and integration of the analytical techniques developed and tested in Work Packages 1 and 2 will be designed and implemented - data that will ensure that any advanced statistical techniques become available in a format that is accessible and useful to non-specialist biomedical technicians and clinicians.