Abstract

As wearable technologies are being increasingly used for clinical research and healthcare, it is critical to understand their accuracy and determine how measurement errors may affect research conclusions and impact healthcare decision-making. Accuracy of wearable technologies has been a hotly debated topic in both the research and popular science literature. Currently, wearable technology companies are responsible for assessing and reporting the accuracy of their products, but little information about the evaluation method is made publicly available. Heart rate measurements from wearables are derived from photoplethysmography (PPG), an optical method for measuring changes in blood volume under the skin. Potential inaccuracies in PPG stem from three major areas, includes (1) diverse skin types, (2) motion artifacts, and (3) signal crossover. To date, no study has systematically explored the accuracy of wearables across the full range of skin tones. Here, we explored heart rate and PPG data from consumer- and research-grade wearables under multiple circumstances to test whether and to what extent these inaccuracies exist. We saw no statistically significant difference in accuracy across skin tones, but we saw significant differences between devices, and between activity types, notably, that absolute error during activity was, on average, 30% higher than during rest. Our conclusions indicate that different wearables are all reasonably accurate at resting and prolonged elevated heart rate, but that differences exist between devices in responding to changes in activity. This has implications for researchers, clinicians, and consumers in drawing study conclusions, combining study results, and making health-related decisions using these devices.

Highlights

  • Wearable technology has the potential to transform healthcare and healthcare research by enabling accessible, continuous, and longitudinal health monitoring

  • We found that wearable device, wearable device category, and activity condition all significantly correlated with heart rate (HR) measurement error, but changes in skin tone did not impact measurement error or wearable device accuracy

  • In addition to HR, we examined HR variability (HRV), a clinically relevant diagnostic metric that can be derived from PPG signals and is a widely used metric of autonomic nervous system function

Read more

Summary

Introduction

Wearable technology has the potential to transform healthcare and healthcare research by enabling accessible, continuous, and longitudinal health monitoring. While research- and consumer-grade wearables often contain the same sensors and are quite similar functionally, their markets and use cases are different, which may influence accuracy (Supplementary Table 1). Digital biomarkers are expected to enable actionable health insights in real time and outside of the clinic. Both consumer- and research-grade wearables are frequently being used in research, with the most common brands being Fitbit (PubMed: 476 studies, ClinicalTrials.gov: 449 studies) for consumer-grade wearables and Empatica (PubMed: 22 studies, ClinicalTrials.gov: 22 studies) for research-grade wearables (Supplementary Table 2)

Objectives
Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call