DOI
https://doi.org/10.1109/JPROC.2015.2491979

Summary
The multiscale analysis of intensive longitudinal biomedical signals (heart rate variability (HRV) and spontaneous physical activity (SPA) is described in this paper. The recently developed technologies of wearable and biomedical sensing enable to collect large amount of time series data, analyze it, and use in medicine and healthcare, for example, to early diagnose various diseases, including psychiatric disorders. The article consists of review on the previous research and identified problems of interest, provides the characterizations of intensive longitudinal data (ILD) that demonstrate intermittent and non-Gaussian behavior, and illustrative examples of practical applications of the multiscale analysis. The authors state that the described approach can be a useful tool to extract information from the time series of biological data continuously collected throughout the daily life events.

Relevance for Complex Systems Knowledge
The presented scheme for multiscale analysis of time series of biological signals requires knowledge and skills in the fields of medicine, mathematics, statistics, engineering, informatics. From the biological point of view, biological signals are hard to control over a long period of time as they are generated unconsciously. Moreover, they show the resulting interaction between human biological systems. That is why the measured signals should be considered as parameters which define the state of a complex system. The suggested approach may be applied in personalized medicine, disease prevention, early disease prediction, diagnosis and risk assessment, disease management.

Point of Strength
The strength of the article is a presented complex approach to analyze time series of biological signals.