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The Relationship between Accelerometry, Global Navigation Satellite System, and Known Distance: A Correlational
Abdulmalek K Bursais1,2, Caleb D Bazyler2, Andrew R Dotterweich2
1Department of Physical Education, College of Education, King Faisal University, Al-Ahsa 31982, Saudi Arabia.
Sensors (Basel, Switzerland)
|May 20, 2022
Summary
This study shows that both Global Navigation Satellite System (GNSS) and accelerometry can accurately predict walking distance. These wearable technologies offer reliable methods for measuring distance covered during physical activity.
Area of Science:
- Biomechanics
- Sports Science
- Wearable Technology
Background:
- Previous studies explored accelerometry and GNSS for load measurement.
- No prior research linked these measures to known distances.
- This study bridges that gap by examining distance prediction.
Purpose of the Study:
- To assess accelerometry-based metrics and GNSS for predicting known walking distances.
- To compare the predictive accuracy of different measurement tools.
- To evaluate performance under varying movement constraints (circle diameter).
Main Methods:
- Correlational design with 30 physically active college students.
- Participants walked known distances on small (2m) and large (8m) diameter circles.
- Data collected using tri-axial accelerometers and triple GNSS units.
Main Results:
- All regression models showed high performance (R² = 0.922–0.999).
- GNSS (GNSSD) and accelerometry's MAG metric demonstrated the highest accuracy in predicting distance.
- Both technologies proved effective across different circle sizes.
Conclusions:
- Both GNSS and accelerometry are viable tools for indicating total walking distance.
- These findings support the use of wearable technology for objective distance measurement.
- Further research can refine these applications in diverse physical activities.
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