Related Experiment Video
Updated: Aug 6, 2026

Assessing the Accuracy of Fitness Smartwatch Data for Cardiovascular and Physical Activity Monitoring: A Validation Study in Digital Health
Published on: February 21, 2025
Accelerometry and heart rate as a measure of physical fitness: cross-validation
Guy Plasqui1, Klaas R Westerterp
1Department of Human Biology, Maastricht University, The Netherlands. g.plasqui@hb.unimaas.nl
Purpose:
We recently reported on a new method to assess physical fitness, based on the combined use of accelerometry and heart rate (HR) registration. This study tested the validity of the prediction formula in a group of healthy young adults.
Methods:
Twenty-six healthy subjects performed a maximal incremental test on a bicycle ergometer to determine VO2max. A triaxial accelerometer and a HR monitor were worn for 7 d under free-living conditions. The prediction formula developed in a previous experimental group (EXP) was applied on the cross-validation group (CV).
Results:
No difference was found in subjects' characteristics between the EXP and CV groups except for accelerometer output (activity counts). Although measured VO2max could be predicted for 80% (P < 0.0001), a paired t-test showed a significant difference between measured and predicted VO2max (178 mL.min(-1); P = 0.015). Because of the difference in activity between the EXP and the CV groups, all data were combined and sorted according to activity counts, then two new groups were formed. As a result, EXP and CV groups were created that did not significantly differ in activity or any other parameters. The formula developed in the new experimental group (R2 = 0.74; P < 0.0001) explained 72% (P < 0.0001) of the variation in VO2max in the cross-validation group, a paired t-test showed no difference between measured and predicted VO2max, and Bland-Altman plotting showed no systematic bias.
Conclusion:
Although a good correlation was seen between measured and predicted VO2max in the cross-validation group, care should be taken in applying the prediction formula on groups that differ in physical activity from the current study population.
Related Concept Videos
Factors Influencing Heart Rate
Let us explore the significant factors affecting heart rate, including age, body temperature, posture, acute pain, chemical influences,...
Measuring Acceleration Due to Gravity
A simple pendulum can be described as a point mass and a string. Meanwhile, a physical pendulum is any object whose oscillations are similar to a simple pendulum, but cannot be modeled as a point mass on a string because its mass is distributed over a larger area. The behavior of a physical pendulum can be modeled using the principles of...
Correlation between ECG and Cardiac Cycle
A cardiac action potential originates in the SA node and spreads throughout the atria and the AV node in approximately 0.03 seconds. This results in the P wave in an ECG and triggers atrial contraction. The action potential is then briefly slowed at the AV node, allowing the atria to contract and fill the ventricles with blood before...
Exercise and Cardiovascular Response
Light to moderate physical activity initiates a series of interconnected responses in the body. The heart rate modestly increases in anticipation of the workout, followed by widespread vasodilation as oxygen consumption by skeletal muscles increases. This results in decreased peripheral resistance, increased capillary blood flow, and accelerated...
Special considerations while measuring pulse
Equipments Used To Measure Blood Pressure
This invasive approach involves cannulating a peripheral artery. During each cardiac contraction, pressure generates mechanical motion within the catheter, transmitted through rigid, fluid-filled tubing to a transducer. This transducer converts mechanical motion into electrical signals displayed as waveforms on a monitor. An automatic flushing system prevents blood backflow. Due to the potential risk of unexpected arterial blood loss, this method is primarily used in intensive...

