Estimation of energy expenditure using accelerometers and activity-based energy models—validation of a new device

Over the last few years, the estimation of energy expenditure with accelerometers has become more and more accurate due to
improvements in sensor technology. Significant enhancement could be reached by model-based estimation regarding different
activity types. The kmsMove-sensor (movisens GmbH, Karlsruhe, Germany) is a device that is used to compute human energy expenditure
using motion-dependent calculation models. It is outfitted with an accelerometer to measure body acceleration during certain
movements and activities. To validate its accuracy, the sensor was compared to indirect calorimetry as criterion measure.
For this experiment, nine subjects (all males, age 46.4 ± 10.9 years, 28–64 years) were equipped with the kmsMove-sensor as
well as a portable indirect calorimeter and their energy consumption was measured over a time period of 100 min. Additionally,
the energy consumption of seven out of the above-mentioned nine subjects was measured over an average of 7 h. The measurements
took place in a rehabilitation clinic, where the subjects completed their regular daily rehabilitation activities. An analysis
of the data revealed ICCs between the kmsMove-sensor and indirect calorimetry for the time period of 100 min of 0.82 (0.38–0.96;
p = 0.003) and for an averaged measuring time of 7 h of 0.81 (0.22–0.97; p = 0.01). Furthermore, a Bland–Altman analysis for the time period of 100 min led to a difference of the means of 4.3 kcal
(limits of agreement: −94.3 and 102.9 kcal) and for the time period of an average of 7 h to −14.0 kcal (limits of agreement:
−320.0 and 292.0 kcal). These findings indicate that the kmsMove-sensor is an appropriate measuring device with relatively
good accuracy to assess human energy expenditure in rehabilitation patients. However, this study has some limiting aspects
(small sample size, artificial setting) which could influence validity.