Melina Nohemi Del Angel Martinez

I am a statistician with interest in medical and biological sciences. I enjoy working in cross-disciplinary enviroments, and contribute to expand the knowdlege in scientific disciplines through development of novel statistical methodolgies. 

My PhD project

Physical activity is important for the treatment and management of multiple health conditions. Understanding its relationship with certain diseases is key for health professionals to make tailored advice to patients, targeting improvements in specific health dimensions. Recently, wearable monitors have been introduced as a new technology for monitoring physical activity in a more objective and reliable way than the usual self-reported methods. These devices can track individuals’ physical activity for long periods of time at very high resolution (minute-by-minute). However, analysing wearable data represents a new challenge because of its large volume, non-stationarity, and highly noisy observations.

In the current literature, most of the methods used draw conclusions from means-based analysis, aggregating data into daily or weekly resolutions. They usually ignore the time-dependent structure of the data and overlook important information regarding individuals’ behaviour. One promising but unexplored approach for analysing wearable data is time series analysis. In my PhD, I propose to use non-stationary time series analysis along with functional data analysis tools to assess physical activity performance over the course of a 12-week intervention programme. These models provide more robust methods to understand the underlying components of the physical activity data, and provide health professionals with additional tools to analyze longitudinal medical data, complementing and enhancing conclusions drawn with conventional methods.