Related Experiment Video
Updated: May 11, 2026
10:07
Measurement of Dynamic Scapular Kinematics Using an Acromion Marker Cluster to Minimize Skin Movement Artifact
Published on: February 10, 2015
19.2K
Machine learning insights into scapular stabilization for alleviating shoulder pain in college students
Omar M Mabrouk1, Doaa A Abdel Hady2, Tarek Abd El-Hafeez3,4
1Basic Science for Physical Therapy, Deraya University, EL-Minia, Egypt.
Scientific Reports
|November 18, 2024
Summary
Scapular stabilization exercises effectively reduce non-specific shoulder pain in college students. Machine learning, particularly scikit-optimize, optimizes these exercises for better outcomes in musculoskeletal health management.
Area of Science:
- Orthopedics
- Rehabilitation Medicine
- Computational Science
Background:
- Non-specific shoulder pain is prevalent among college students, impacting their quality of life.
- Scapular stabilization exercises (SSE) are utilized to improve scapular control and mobility.
- Predictive modeling can enhance the efficacy of SSE for shoulder pain management.
Purpose of the Study:
- To investigate the predictive impact of scapular stabilization exercises on non-specific shoulder pain.
- To leverage machine learning for optimizing SSE protocols.
- To evaluate the effectiveness of various regression and optimization techniques.
Main Methods:
- Employed diverse regression models (Gamma, Tweedie, Poisson) to analyze exercise effectiveness.
- Utilized optimization techniques (Hyperopt, scikit-optimize, Optuna) for protocol fine-tuning.
- Assessed prediction accuracy using Mean Squared Error, Mean Absolute Error, and R2 score.
Main Results:
- Optimized SSE using machine learning significantly reduced shoulder pain in college students.
- Scikit-optimize achieved the best performance with an R2 score of 0.8501.
- Accurate predictions were made regarding the relationship between exercises and pain reduction.
Conclusions:
- Scapular stabilization exercises are critical for alleviating non-specific shoulder pain.
- Machine learning techniques, especially scikit-optimize, can optimize therapeutic strategies.
- Findings support personalized rehabilitation programs for musculoskeletal disorders using AI.
