Comparing and Normalizing the Measurement of Step Counts and Heart Rates of Selected Wristbands and Smartwatches
Conference proceedings article
Authors/Editors
Strategic Research Themes
Publication Details
Author list: Siam Yamsaengsung, Thanapong Khajontantichaikun, Bunthit Watanapa, Saichon Jaiyen, Vajirasak Vanijja, Pornchai Mongkolnam, Chujit Treerattanaphan, Pairoj Likitthanasate
Publication year: 2023
Start page: 371
End page: 376
Number of pages: 6
URL: https://ieeexplore.ieee.org/document/10329731
Languages: English-United States (EN-US)
Abstract
The usefulness and popularity of smartwatches in the marketplace has led to a large variety of brands and models, each utilizing different technologies and processing methods to detect physical activities and measure vital metrics. Consequently, the reported values of widely available metrics of heart rate and step count can exhibit significant variations across these devices compared to standard medical equipment. This research proposes a model to standardize these values using a medical-grade device as a reference for heart rate and a manual clicker for step count. Descriptive statistics reveal that while the detected median values of step count align closely with actual steps, there is a notable oscillation in the overall data distribution. Fitbit devices consistently report lower step counts with high variability, while Garmin devices demonstrate more accurate step counts. Fitbit devices provide more precise heart rate measurements, while Huawei's measurements are less so. A linear regression model is used to effectively refine smartwatch measurements across multiple models, achieving a high level of accuracy as compared to a medical-grade sensor. Gender does not significantly impact the modeling adjustments.
Keywords
Data Mining, Digital Health, Heart rate (HR), Smartwatch, Step Counts