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This paper presents an approach to designing a method for the estimation of human energy expenditure (EE). The approach first evaluates different sensors and their combinations. After that, multiple regression models are trained utilizing data from different sensors. The EE estimation method designed in this way was evaluated on a dataset containing a wide range of activities. It was compared against three competing state-of-the-art approaches, including the BodyMedia Fit armband, the leading consumer EE estimation device. The results show that the proposed method outperforms the competition by up to 10.2 percentage points.

We investigated the iron-related haematological parameters in both male and female athletes participating in different sporting disciplines necessitating different metabolic energy demands. A total of 873 athletes (514 males, mean age: 22.08 ± 4.95 years and 359 females, mean age: 21.38 ± 3.88 years) were divided according to gender and to the predominant energy system required for participation in sport (aerobic, anaerobic or mixed) and haematological and iron-related parameters were measured. For both male and female athletes, significant differences related to the predominant energy system were found at a general level: male (Wilks' λ = 0.798, F = 3.047, p < 0.001) and female (Wilks' λ = 0.762, F = 2.591, p < 0.001). According to the ferritin cutoff value of 35 μg/L, whole body iron and sTfR significantly differed in all three groups of male and female athletes (p < 0.001). The percentage of hypochromic erythrocytes in male athletes was significantly higher only in those who required an anaerobic energy source (p < 0.001), whilst in the females hypochromic erythrocytes (p < 0.001) and haemoglobin (anaerobic, p = 0.042; mixed, p = 0.006) were significantly different only in anaerobic and mixed energy source athletes. According to the ferritin cutoff value of 22 μg/L, in females, whole body iron, sTfR and hypochromic erythrocytes were significantly higher in all three groups of athletes than those below the aforementioned cutoff value (p < 0.001). We conclude that the predominant energy system required for participation in sport affects haematological parameters. sTfR and body iron proved to be reliable parameters for monitoring the dynamics of iron metabolism and could contribute to successful iron-deficiency prevention.

The study confirms that in a large and representative group of elite swimmers, creatinine concentration is strictly correlated to BMI. The use of creatinine-based eGFR formulas should be used with caution in athletes.

The paper addresses relations between the characteristics of body composition in international sprint swimmers and sprint performance. The research included 82 swimmers of international level (N = 46 male and N = 36 female athletes) from 8 countries. We measured body composition using multifrequency bioelectrical impedance methods with “InBody 720” device. In the case of male swimmers, it was established that the most important statistically significant correlation with sprint performance is seen in variables, which define the quantitative relationship between their fat and muscle with the contractile potential of the body (Protein-Fat Index, r = 0.392, p = 0.007; Index of Body Composition, r = 0.392, p = 0.007; Percent of Skeletal Muscle Mass, r = 0.392, p = 0.016). In the case of female athletes, statistically significant relations with sprint performance were established for variables that define the absolute and relative amount of a contractile component in the body, but also with the variables that define the structure of body fat characteristics (Percent of Skeletal Muscle Mass, r = 0.732, p = 0.000; Free Fat Mass, r = 0.702, p = 0.000; Fat Mass Index, r = −0.642, p = 0.000; Percent of Body Fat, r = −0.621, p = 0.000). Using Multiple Regression Analysis, we managed to predict swimming performance of sprint swimmers with the help of body composition variables, where the models defined explained 35.1 and 75.1% of the mutual variability of performance, for male and female swimmers, respectively. This data clearly demonstrate the importance of body composition control in sprint swimmers as a valuable method for monitoring the efficiency of body adaptation to training process in order to optimize competitive performance.