Good science stems from both valid measurement of relevant data, and its processing, analysis, and interpretation in an appropriate way. Bad data will always lead to bad science irrespective of how well the data were analyzed and/or interpreted. Therefore, it is of paramount importance that the measurements are as accurate and reliable as possible, and the derived metrics are argu able, understandable, commensurable, comparable, unambiguous, and contextually meaningful. Only then is reasonable interpretation of measured data possible, and far-reaching and solid conclusions drawn. Accelerometry is the most widely used method for objective measurement of physical activity (PA) and sedentary behavior (SB) in clinical and research settings.1 Its primary purpose is to translate the measured acceleration data into relevant information that describes adequately the individual behavior in terms of physical activity and sedentariness. This information can be specific both for the monitoring period of interest and for some feature(s) of the monitored individual: for example, his/her daily/weekly PA and SB profile, daily energy expenditure, met PA recommendations, or risk of diseases.
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