Identification of rheological properties of human body surface tissue.

According to World Health Organization obesity is one of the greatest public health challenges of the 21st century. It has tripled since the 1980s and the numbers of those affected continue to rise at an alarming rate, especially among children. There are number of devices that act as a prevention measure to boost person's motivation for physical activity and its levels. The placement of these devices is not restricted thus the measurement errors that appear because of the body rheology, clothes, etc. cannot be eliminated. The main objective of this work is to introduce a tool that can be applied directly to process measured accelerations so human body surface tissue induced errors can be reduced. Both the modeling and experimental techniques are proposed to identify body tissue rheological properties and prelate them to body mass index. Multi-level computational model composed from measurement device model and human body surface tissue rheological model is developed. Human body surface tissue induced inaccuracies can increase the magnitude of measured accelerations up to 34% when accelerations of the magnitude of up to 27 m/s(2) are measured. Although the timeframe of those disruptions are short - up to 0.2 s - they still result in increased overall measurement error.
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