Correlating Multimodal Physical Sensor Information with Biological Analysis in Ultra Endurance Cycling

The sporting domain has traditionally been used as a testing ground for new technologies which subsequently make their way into the public domain. This includes sensors. In this article a range of physical and biological sensors deployed in a 64 hour ultra-endurance non-stop cycling race are described. A novel algorithm to estimate the energy expenditure while cycling and resting during the event are outlined. Initial analysis in this noisy domain of “sensors in the field” are very encouraging and represent a first with respect to cycling

Physical activity measurement using novel sensor technologies in unique environments

This thesis presents methods of estimating the physical activity, and energy expenditure during various activities in three unique environments using a low cost sensor platform, the GT3X ActiGraph accelerometer. The environments in this study included; simulated and real world horse riding, search and rescue operations, and ultra-endurance cycle racing. GT3X ActiGraphs were deployed in each environment to measure the associated energy expenditure of specific activities. Where possible other validated energy expenditure estimation sensors were deployed in parallel with the GT3X ActiGraphs. However, due to the nature and duration of deployment in the environments, this was not always possible. In these cases assumptions were made based on the activity, the subject anthropometrics and the intensity of the motions observed in order to better estimate the energy expended. Specific events were defined for each environment and the energy demands of these events were further investigated with the GT3X ActiGraphs. These included; the differences between simulated and outdoor horse riding at similar energy expenditure rates; the differences between sleeping environments on physical activity and sleep indices in search and rescue operators; and an analysis of the energy expended during cycling and rest periods during an ultra-endurance cycling race using proprietary and researcher developed algorithms. However, the data presented from the propitiatory software may not be capable of estimating the physical activity expended during various activities certain environments as external factors may first need to be filtered out. This calls for a combined physiological and computer science approach to be taken in further research with these sensors