In larger terms, Professor McGregor's research interests span a very broad range of topics including some of the most applied aspects of exercise physiology (e.g. interval training and athletic performance (6, 9, 12, 14)) and, at the same time, some of the most esoteric (e.g. entropy of physiological signals (1, 4, 7, 11)). There are two primary foci of research that continue to be pursued at Eastern Michigan University over the past nine years. The first relates to the use of wireless high resolution accelerometers (HRA) networks and tools from "traditional" exercise physiology to quantify movement and, in particular, investigate what underlies inter-individual differences in running ability. This work is exciting as it is practically relevant and accessible for students, but also provides increased understanding of fundamental elements of physiology.
The second area of research we have been focusing on relates to the non-linear analysis of physiological signals obtained from various types of sensors and measuring devices (1, 2, 4, 7, 8, 11). The Applied Physiology-Dynamical Systems (AP-DS) Group is a collaborative effort between the School of Health Promotion and Human Performance at Eastern Michigan University (EMU) and Department of Mathematics and Computer Science at Clarkson University (CU). The EMU group has had extensive experience working with a range of human subjects, from untrained to elite athletes, in order to develop tools that objectively quantify workload and physiological responses during exercise, particularly in the field. The CU group is well accomplished in the field of non-linear dynamical systems and has developed approaches that have been specifically applied to the physiological signals and/or workload measures developed by the EMU group. Most notably of these non-linear tools is Control Entropy (CE), which can be used as a systems health monitoring tool under conditions that do not satisfy the criteria of stationarity (1).