Wrist-Worn Activity Trackers in Laboratory and Free-Living Settings for Patients With Chronic Pain: Criterion Validity Study

Abstract

Background: Physical activity is evidently a crucial part of the rehabilitation process for patients with chronic pain. Modern wrist-worn activity tracking devices seemingly have a great potential to provide objective feedback and assist in the adoption of healthy physical activity behavior by supplying data of energy expenditure expressed as metabolic equivalent of task units (MET). However, no studies of any wrist-worn activity tracking devices' have examined criterion validity in estimating energy expenditure, heart rate, or step count in patients with chronic pain.

Objective: The aim was to determine the criterion validity of wrist-worn activity tracking devices for estimations of energy expenditure, heart rate, and step count in a controlled laboratory setting and free-living settings for patients with chronic pain.

Methods: In this combined laboratory and field validation study, energy expenditure, heart rate, and step count were simultaneously estimated by a wrist-worn activity tracker (Fitbit Versa), indirect calorimetry (Jaeger Oxycon Pro), and a research-grade hip-worn accelerometer (ActiGraph GT3X) during treadmill walking at 3 speeds (3.0 km/h, 4.5 km/h, and 6.0 km/h) in the laboratory setting. Energy expenditure and step count were also estimated by the wrist-worn activity tracker in free-living settings for 72 hours. The criterion validity of each measure was determined using intraclass and Spearman correlation, Bland-Altman plots, and mean absolute percentage error. An analysis of variance was used to determine whether there were any significant systematic differences between estimations.

Results: A total of 42 patients (age: 25-66 years; male: 10/42, 24%; female: 32/42, 76%), living with chronic pain (duration, in years: mean 9, SD 6.72) were included. At baseline, their mean pain intensity was 3.5 (SD 1.1) out of 6 (Multidimensional Pain Inventory, Swedish version). Results showed that the wrist-worn activity tracking device (Fitbit Versa) systematically overestimated energy expenditure when compared to the criterion standard (Jaeger Oxycon Pro) and the relative criterion standard (ActiGraph GT3X). Poor agreement and poor correlation were shown between Fitbit Versa and both Jaeger Oxycon Pro and ActiGraph GT3X for estimated energy expenditure at all treadmill speeds. Estimations of heart rate demonstrated poor to fair agreement during laboratory-based treadmill walks. For step count, the wrist-worn devices showed fair agreement and fair correlation at most treadmill speeds. In free-living settings; however, the agreement for step count between the wrist-worn device and waist-worn accelerometer was good, and the correlation was excellent.

Conclusions: The wrist-worn device systematically overestimated energy expenditure and showed poor agreement and correlation compared to the criterion standard (Jaeger Oxycon Pro) and the relative criterion standard (ActiGraph GT3X), which needs to be considered when used clinically. Step count measured with a wrist-worn device, however, seemed to be a valid estimation, suggesting that future guidelines could include such variables in this group with chronic pain.

Keywords: chronic pain; energy expenditure; heart rate; pain; physical activity; rehabilitation; step count; validity; wearable; wearable devices.

Figure 1

Bland-Altman plot visualizing agreement of energy expenditure (MET) estimated by Fitbit Versa and criterion measurement Jaeger Oxycon Pro during overall treadmill walk. The middle green line shows the mean difference (bias) between devices. The dashed lines indicate upper (+1.96 SD) and lower (–1.96 SD) limits of agreement and the black line represents the regression line illustrating association between estimations.

Figure 2

Bland-Altman plot visualizing agreement of heartrate estimated by Fitbit Versa and criterion measurement Jaeger Oxycon Pro during overall treadmill walk. The middle green line shows the mean difference (bias) between devices. The dashed lines indicate upper (+1.96 SD) and lower (–1.96 SD) limits of agreement and the black line represents the regression line illustrating association between estimations.

Figure 3

Bland-Altman plot visualizing agreement of energy expenditure (MET) estimated by Fitbit Versa and relative criterion measurement ActiGraph GT3X during overall treadmill walk. The middle green line shows the mean difference (bias) between devices. The dashed lines indicate upper (+1.96 SD) and lower (–1.96 SD) limits of agreement and the black line represents the regression line illustrating association between estimations.

Figure 4

Bland-Altman plot visualizing agreement of step count estimated by Fitbit Versa and relative criterion measurement ActiGraph GT3X during overall treadmill walk. The middle green line shows the mean difference (bias) between devices. The dashed lines indicate upper (+1.96 SD) and lower (–1.96 SD) limits of agreement and the black line represents the regression line illustrating association between estimations.

Figure 5

Bland-Altman plot visualizing agreement of step count estimated by Fitbit Versa and relative criterion measurement ActiGraph GT3X during free-living. The middle green line shows the mean difference (bias) between devices. The dashed lines indicate upper (+1.96 SD) and lower (–1.96 SD) limits of agreement and the black line represents the regression line illustrating association between estimations.