Anthropometry and diagnostic aware deep learning for exercise assessment

Key Points

• Improved movement quality classification supports personalized feedback methods for training and rehabilitation.
• Key evidence indicates that subject-specific features significantly enhance classification accuracy in exercise assessments.
• Assessment using deep learning methods reveals a direct link between static features and risk stratification levels.
• This highlights the potential for wearable devices to personalize feedback, while further validation in diverse populations is needed.