The evaluation of movement quality in physiotherapy and sports training has found a promising tool in inertial sensors (IMU), but training artificial intelligence models to interpret these signals faces obstacles such as scarcity of labeled data, class imbalance, and label ambiguity. An innovative alternative involves generating synthetic data through musculoskeletal simulations that modify movement trajectories while respecting anatomical constraints, and which are automatically labeled by combining inverse kinematic parameters with evaluation rules based on expert knowledge. This approach allows augmenting real datasets, improving classification accuracy, generalization to new subjects, and the ability to fine-tune with few examples from a specific patient.
From a business perspective, implementing such solutions requires a team that masters both custom software development and artificial intelligence applied to complex data. At Q2BSTUDIO we offer AI for businesses ranging from creating deep learning models to integrating synthetic data generation pipelines. Additionally, these systems can be deployed scalably and securely using AWS and Azure cloud services, and complemented with cybersecurity modules to protect sensitive data. Result visualization and progress tracking are enhanced with business intelligence tools such as Power BI, while process automation benefits from incorporating AI agents that act on workflows.
Ultimately, the combination of biomechanical simulations with data augmentation techniques opens the door to objective and automated exercise evaluation, overcoming traditional limitations. Organizations seeking to adopt these capabilities can rely on custom applications that integrate all these components. At Q2BSTUDIO we transform advanced concepts into tangible solutions, helping clinics, sports centers, and companies leverage artificial intelligence and the cloud to improve health and performance.
