Innovative workflow for clinical gait analysis for children with cerebral palsy

Clinical gait analysis is essential for functional diagnostics, evaluation and related treatment decisions for patients with cerebral palsy (CP). Its clinical use for large patient groups is, however, limited due to the high costs, long processing time (8 hours/patient), need for advanced equipment and specialized personnel. Moreover, manual actions are required in processing data. This project aims to improve the current workflow for clinical gait analysis in children with CP by developing and validating a proof-of-concept Machine-learning  Assisted Movement Analysis (MAMA) system for automatic gait features annotation and identification of gait kinematic abnormalities to support clinical decision-making. MAMA will be implemented  in a cloud-based infrastructure (‘Moveshelf’) which is accessible at any location and can be connected to electronic health record systems. This makes gait results visible for more care providers allowing better coordination within the chain.

The new workflow will reduce the processing time by 30% and lower operational costs making clinical gait analysis more scalable and cost effective, allowing more patients to benefit from advanced clinical gait analysis. The automatic detection reduces operator errors and allows more data to be involved, improving the reliability of gait reports. Altogether, this will contribute to better clinical decision-making and treatment advice and thus, finally to optimised and personalised patient care, i.e.  healthier walking behaviour which positively influences the  patients’ participation in society, well-being, quality of life and general health, and in turn reduce health-related costs.

First the requirements for the MAMA system will be established, and a large gait database comprising retrospective data of healthy children, adults and children with CP is created. Based on this, a MAMA algorithm is developed and validated. Next, MAMA is implemented in Moveshelf and the new workflow is evaluated in clinical practice. Finally an operational proof-of-concept workflow, including MAMA implemented in Moveshelf, is delivered.