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Predicting Tissue Loads in Running from Inertial Measurement Units
John Rasmussen1, Sebastian Skejø2,3, Rasmus Plenge Waagepetersen4
1Department of Materials and Production, Aalborg University, Fibigerstraede 16, 9220 Aalborg East, Denmark.
Sensors (Basel, Switzerland)
|December 23, 2023
Summary
Smartwatch sensors show promise in predicting running-related tissue loads, potentially preventing injuries. Further research is needed to refine these biomechanical predictions for widespread use.
Area of Science:
- Biomechanics
- Sports Medicine
- Wearable Technology
Background:
- Repetitive load injuries are common in runners.
- Smartwatches with Inertial Measurement Unit (IMU) sensors are frequently used by runners.
- IMU data may offer insights into tissue loading to prevent injuries.
Purpose of the Study:
- To investigate the potential of using IMU data to predict tissue loads in runners.
- To assess the feasibility of employing physics-based and data-based models for this prediction.
Main Methods:
- A combined physics-based simulation and data-based approach was used.
- Data from 285 running trials of 76 runners were analyzed.
- Elastic net and gradient boosting models were trained and tested to predict Achilles tendon and patella ligament forces.
Main Results:
- High correlations were found between predicted and simulated forces for the patella ligament (up to 0.95) and Achilles tendon (0.71).
- No single predictive algorithm consistently outperformed others.
- The study highlights the potential but also the variability in predictive accuracy.
Conclusions:
- Predicting tissue loads using body-mounted IMUs is a promising avenue for injury prevention in runners.
- Further investigation is required before this technology can be widely implemented in running watches.
- Refining algorithms and validating models are crucial next steps.
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