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Introduction
Consumer wearable technology has recently become an integral part of behavioral research. In addition to common motion sensors, such as accelerometers and gyroscopes, used to compute steps and activity intensity values, newer devices have also begun to include heart rate sensors. These typically take the form of optical sensors for photoplethysmogram (PPG) measures that compute heart rate. While many wearable devices are wrist-based sensors, there are a growing number of companies that are integrating multiple sensor suites into smart garments.

This study, conducted as part of a larger ongoing study aiming to understand predictors of productivity in a high-stress work environment,. The Fitbit Charge 2 is a wrist-worn device that incorporates PPG sensing for 24/7 measurement of heart rate. The OMsignal smart garment (bra or compression shirt) includes a variety of sensors, including printed electrodes for ECG measurement.

Methods
A total of 192 adult participants (71.9% female) wore the Fitbit Charge 2 and an OMsignal garment during working hours over a 10-week period in early 2018. Fitbit heart rate data was captured at one minute epochs (mean heart rate over one minute) and OMsignal data was captured at five minute epochs (mean heart rate over five minutes). Fitbit data was resampled to reflect the available five minute epochs from OMsignal. Additionally, OMsignal values associated with poor RR coverage were removed, per manufacturer analysis guidelines. Comparison between the two devices was measured by mean bias, mean absolute percent error (MAPE), concordance correlation coefficients (CCC), and Bland-Altman plots with 95% limits of agreements (LOA). The OMsignal was treated as the reference device in this analysis due to its use of ECG measurement.

Results
Across all participants, 3,738 days of observation were included in this analysis. The mean number of paired Fitbit-OMsignal epochs per participant was 1,277.96 (SD = 964.21). The mean bias was 1.69bpm, and MAPE was 4.98%. The overall CCC was 0.892 (95% CI = 0.891 – 0.893). Bland-Altman analysis indicated 95% of values fall between -10.06bpm and 13.43bpm.

Conclusion
We found that in a long-term free-living study the Fitbit Charge 2 performed similarly to the OMsignal garment for measuring heart rate. When compared to prior validation studies comparing Fitbit heart rate to gold standards in free-living and laboratory settings, these results indicate slightly higher correlation, a narrower LOA, and smaller mean bias. This study is unique due to the large amount of free-living data spanning real-world activities of daily living and the inclusion of a new device, the OMsignal smart garment. Further research should explore additional features extracted from ECG data beyond heart rate and how they compare against laboratory studies.

 

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