Abstract
The aim of this study was to compare the seven following commercially available activity monitors in terms of step count detection accuracy: Movemonitor (Mc Roberts), Up (Jawbone), One (Fitbit), ActivPAL (PAL Technologies Ltd.), Nike+ Fuelband (Nike Inc.), Tractivity (Kineteks Corp.) and Sensewear Armband Mini (Bodymedia). Sixteen healthy adults consented to take part in the study. The experimental protocol included walking along an indoor straight walkway, descending and ascending 24 steps, free outdoor walking and free indoor walking. These tasks were repeated at three self-selected walking speeds. Angular velocity signals collected at both shanks using two wireless inertial measurement units (OPAL, ADPM Inc) were used as a reference for the step count, computed using previously validated algorithms. Step detection accuracy was assessed using the mean absolute percentage error computed for each sensor. The Movemonitor and the ActivPAL were also tested within a nine-minute activity recognition protocol, during which the participants performed a set of complex tasks. Posture classifications were obtained from the two monitors and expressed as a percentage of the total task duration.The Movemonitor, One, ActivPAL, Nike+ Fuelband and Sensewear Armband Mini underestimated the number of steps in all the observed walking speeds, whereas the Tractivity significantly overestimated step count. The Movemonitor was the best performing sensor, with an error lower than 2% at all speeds and the smallest error obtained in the outdoor walking. The activity recognition protocol showed that the Movemonitor performed best in the walking recognition, but had difficulty in discriminating between standing and sitting. Results of this study can be used to inform choice of a monitor for specific applications.
Highlights
An objective and reliable method for the classification and quantification of free-living motor activity is a prerequisite for the understanding of the complex relationship between health and physical activity
The devices investigated in this study showed an absolute error for energy expenditure estimation during a 69minute protocol ranging between 9.3% and 23.5% [12]
The aim of this study is to compare the step count detection accuracy of seven different physical activity monitors (PAMs) in healthy adults, covering a range of technologies and prices, during different walking protocols, including indoor and outdoor walking at different speeds
Summary
An objective and reliable method for the classification and quantification of free-living motor activity is a prerequisite for the understanding of the complex relationship between health and physical activity. The development of micro-engineered piezoresistive and capacitive accelerometers, often referred to as microelectromechanical systems (MEMS), allows the recognition of both dynamic and static activities [2] These devices have been combined with physiological sensors such as heart rate, temperature, heat flux and galvanic skin response with the aim of increasing their accuracy of predicting energy expenditure and discriminating activity types [3,4,5]. The integration of these technologies in a sensor fusion approach has been investigated in the last decades [6]
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