BackgroundThe measurement of activity energy expenditure (AEE) via accelerometry is the most commonly used objective method for assessing human daily physical activity and has gained increasing importance in the medical, sports and psychological science research in recent years.ObjectiveThe purpose of this study was to determine which of the following procedures is more accurate to determine the energy cost during the most common everyday life activities; a single regression or an activity based approach. For this we used a device that utilizes single regression models (GT3X, ActiGraph Manufacturing Technology Inc., FL., USA) and a device using activity-dependent calculation models (move II, movisens GmbH, Karlsruhe, Germany).Material and MethodsNineteen adults (11 male, 8 female; 30.4±9.0 years) wore the activity monitors attached to the waist and a portable indirect calorimeter (IC) as reference measure for AEE while performing several typical daily activities. The accuracy of the two devices for estimating AEE was assessed as the mean differences between their output and the reference and evaluated using Bland-Altman analysis.ResultsThe GT3X overestimated the AEE of walking (GT3X minus reference, 1.26 kcal/min), walking fast (1.72 kcal/min), walking up−/downhill (1.45 kcal/min) and walking upstairs (1.92 kcal/min) and underestimated the AEE of jogging (−1.30 kcal/min) and walking upstairs (−2.46 kcal/min). The errors for move II were smaller than those for GT3X for all activities. The move II overestimated AEE of walking (move II minus reference, 0.21 kcal/min), walking up−/downhill (0.06 kcal/min) and stair walking (upstairs: 0.13 kcal/min; downstairs: 0.29 kcal/min) and underestimated AEE of walking fast (−0.11 kcal/min) and jogging (−0.93 kcal/min).ConclusionsOur data suggest that the activity monitor using activity-dependent calculation models is more appropriate for predicting AEE in daily life than the activity monitor using a single regression model.

Acute and regular exercise as well as physical activity (PA) is related to well-being and positive affect. Recent studies have shown that even daily, unstructured physical activities increase positive affect. However, the attempt to achieve adherence to PA or exercise in inactive people through public health interventions has often been unsuccessful. Most studies analyzing the activity-affect association in daily life, did not report participants’ habitual activity behavior. Thus, samples included active and inactive people, but they did not necessarily exhibit the same affective reactions to PA in daily life. Therefore the present study investigated whether the association between PA and subsequent affective state in daily life can also be observed in inactive individuals. We conducted a pilot study with 29 inactive university students (mean age 21.3 ± 1.7 years) using the method of ambulatory assessment. Affect was assessed via electronic diary and PA was measured with accelerometers. Participants had to rate affect every 2 h on a six item bipolar scale reflecting the three basic mood dimensions energetic arousal, valence, and calmness. We calculated activity intensity level [mean Metabolic Equivalent (MET) value] and the amount of time spent in light activity over the last 15 min before every diary prompt and conducted within-subject correlations. We did not find significant associations between activity intensity and the three mood dimensions. Due to the high variability in within-subject correlations we conclude that not all inactive people show the same affective reactions to PA in daily life. Analyzing the PA-affect association of inactive people was difficult due to little variance and distribution of the assessed variables. Interactive assessment and randomized controlled trials might help solving these problems. Future studies should examine characteristics of affective responses of inactive people to PA in daily life. General assumptions considering the relation between affect and PA might not be suitable for this target group.

Regular exercise and physical activity are among the most important factors influencing the quality of life and make a significant contribution to the maintenance of health and well-being. The assessment of physical activity via accelerometry has become a promising technique often used as means to objectively measure physical activity. This work proposes a simple and reliable method to assess human physical activity and calculate the energy expenditure (EE) by using an acceleration and an air pressure sensor. Our proposed algorithm differentiates between 7 activities with an average accuracy of 98.2% and estimates the second by second EE with an average percent error of 1.59 ± 8.20% using a single measurement unit attached to the subject's hip.

Zusammenfassung In den vergangenen Jahren ist die Notwendigkeit, k?rperliche Aktivit?t objektiv zu erfassen, deutlich geworden, da diese bei einer Reihe der bedeutendsten Volkskrankheiten eine entscheidende Rolle f?r die Entstehung sowie bei der Therapie spielt. Aktivit?tsmonitore, die auf Beschleunigungssensoren basieren und verschiedene Parameter erfassen k?nnen, haben sich in den letzten Jahren zum Standardinstrument bei der objektiven Messung der k?rperlichen Aktivit?t entwickelt. Der grundlegende Parameter zur Beurteilung der k?rperlichen Aktivit?t ist dabei der Energieumsatz. Die derzeit gebr?uchlichen Methoden weisen aber eine Reihe von Begrenzungen auf, die zu erheblichen Fehlern f?hren k?nnen. Eine Verbesserung kann erreicht werden, wenn die aktuelle Bewegungsart erkannt und ein spezifisches Modell f?r die Berechnung des Energieverbrauchs verwendet wird. Zudem k?nnen weitere Informationen anderer ?Sensoren die Genauigkeit weiter erh?hen. Dieser Artikel fasst die aktuelle Forschung auf dem Gebiet der Akzelerometrie zusammen und schl?gt zuk?nftige Forschungs?arbeiten und Entwicklungen vor.

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