Step detection and activity recognition accuracy of seven physical activity monitors

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.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1. Sensor placement.

The figure shows the location of the sensors on a subject’s body: Movemonitor (1), Up (2), One (3), ActivPAL (4) Tractivity (5), Nike+ Fuelband (6), Sensewear Armband Mini (7), OPAL (8).

Fig 2. Typical angular velocity signal of the shank in the sagittal plane during consecutive steps.

The figure shows the angular velocity signal as measured by one of the shank sensors in the sagittal plane during a portion of a randomly selected indoor walking trial. The shown portion of the signal includes walking, stopping and turning. The maxima detected by the algorithm used to detect single steps are also highlighted (dotted vertical lines).

Fig 3. Summary of MPE for the 7 PAMs included in the study.

The figure shows the mean percentage error (MPE) during slow, self-selected and fast walking speed trials for all the sensors included in the study. Error bars are mean ± SD.

Fig 4. Bland-Altman plots for step count for (a) the Movemonitor, ActivPAL and One, and (b) for the Up, Tractivity, Nike+ Fuelband and Sensewear Armband Mini.

The solid lines indicate the mean step count difference between the OPAL sensor and each monitor. The dashed lines indicate mean ± Limits of Agreement (1.96*SD). Regression lines, relevant equations and Pearson’s correlation coefficients (r) are shown for the Nike+ Fuelband and the Sensewear Armband Mini.