Fitness development and performance assessment of elite athletes requires an understanding of many physiological factors, many of these are direct and indirect measures of athlete energy expenditure. Many methods are physiological factor assessments and require the athlete to be constrained by laboratory equipment or periodic interruption of activity to take measurements such as blood samples are required to be taken. This paper presents a method that is entirely ambulatory and noninvasive, using microelectromechanical systems (MEMS) accelerometers. The commonly used output of commercial accelerometer-based devices (known as "counts") cannot discriminate activity intensity for the activities of interest. This, in conjunction with variability in output from different systems and lack of commonality across manufacturers, limits the usefulness of commercial devices. This paper identifies anthropometric and kinematic sources of inter-athlete variability in accelerometer output, leading to an alternate energy expenditure estimator based mainly on step frequency modified by anthropometric measures. This energy expenditure estimator is more robust and not influenced by many sources of variability that affect the currently used estimator. In this system, low-power signal processing was implemented to extract both the energy estimator and other information of physiological and statistical interest
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