Comparing a Fitbit Wearable to an Electrocardiogram Gold Standard as a Measure of Heart Rate Under Psychological Stress: A Validation Study

Abstract

Background Wearable devices collect physiological and behavioral data that have the potential to identify individuals at risk of declining mental health and well-being. Past research has mainly focused on assessing the accuracy and the agreement of heart rate (HR) measurement of wearables under different physical exercise conditions. However, the capacity of wearables to sense physiological changes, assessed by increasing HR, caused by a stressful event has not been thoroughly studied. Objective This study followed 3 objectives: (1) to test the ability of a wearable device (Fitbit Versa 2) to sense an increase in HR upon induction of psychological stress in the laboratory; (2) to assess the accuracy of the wearable device to capture short-term HR variations caused by psychological stress compared to a gold-standard electrocardiogram (ECG) measure (Biopac); and (3) to quantify the degree of agreement between the wearable device and the gold-standard ECG measure across different experimental conditions. Methods Participants underwent the Trier Social Stress Test protocol, which consists of an oral phase, an arithmetic stress phase, an anticipation phase, and 2 relaxation phases (at the beginning and the end). During the stress protocol, the participants wore a Fitbit Versa 2 and were also connected to a Biopac. A mixed-effect modeling approach was used (1) to assess the effect of experimental conditions on HR, (2) to estimate several metrics of accuracy, and (3) to assess the agreement: the Bland-Altman limits of agreement (LoA), the concordance correlation coefficient, the coverage probability, the total deviation index, and the coefficient of an individual agreement. Mean absolute error and mean absolute percent error were calculated as accuracy indices. Results A total of 34 university students were recruited for this study (64% of participants were female with a mean age of 26.8 years, SD 8.3). Overall, the results showed significant HR variations across experimental phases. Post hoc tests revealed significant pairwise differences for all phases. Accuracy analyses revealed acceptable accuracy according to the analyzed metrics of accuracy for the Fitbit Versa 2 to capture the short-term variations in psychological stress levels. However, poor indices of agreement between the Fitbit Versa 2 and the Biopac were found. Conclusions Overall, the results support the use of the Fitbit Versa 2 to capture short-term stress variations. The Fitbit device showed acceptable levels of accuracy but poor agreement with an ECG gold standard. Greater inaccuracy and smaller agreement were found for stressful experimental conditions that induced a higher HR. Fitbit devices can be used in research to measure HR variations caused by stress, although they cannot replace an ECG instrument when precision is of utmost importance.

Aquatic Cognitive–Motor Exercise for Cognition, Balance, and Functional Mobility in Older Adults

“…Program intensity was monitored every 5-10 min using the Borg Category-Ratio Scale (28), with participants rating their rate of perceived exertion (RPE) from a scale of 1 to 10. Heart rate was recorded using a Fitbit Versa 2 smartwatch (San Francisco, CA), which has been validated for heart rate monitoring (29,30). A summary of the aquatic exercise intervention protocol can be found in Fig.…”

The use of commercial wrist-worn technology to track physiological outcomes in behavioral interventions

“…Devices from popular brands, including Apple (Apple Inc, Cupertino, California, USA), Fitbit (Fitbit Inc, San Francisco, California, USA), Samsung (Samsung Electronics Co., Ltd., Suwon, South Korea), Garmin (Garmin Ltd, Olathe, Kansas, USA), and Polar (Polar Electro, Inc., Kempele, Finland) demonstrate high agreement for HR measurements during sleep and/or rest when compared with criterion measures (i.e. ECG or chest HR monitor) [29–35]; however, as exercise intensity increases, measurement error is more likely to occur [29–32,36,37 ▪ ,39]. The extent of this relationship can be influenced by activity type, arm movement, and device [32,40].…”