Instrumental gait analysis is widely used to provide a quantitative description of gait impairments among people with neurological conditions, such as stroke and cerebral palsy. Common applications of gait analysis in clinical settings encompass functional diagnosis, disease progression monitoring, treatment planning, and pre- and post-operative assessments.
A large amount of data can be derived from gait analysis, including kinematics, spatio-temporal parameters, dynamics, muscular patterns. This presents significant challenges to clinicians in terms of time and consensus-building for clinical decision-making.
Machine learning for gait analysis
To address these challenges, several data analysis techniques have emerged, including machine learning. Machine learning techniques can employ both supervised or unsupervised methods and are able to uncover hidden patterns within the data.
PhD program on machine learning
Sol et Salus Hospital, Rimini, Italy, funded a PhD program on IA techniques in clinical gait analysis. In 2023, Sol et Salus Hospital in Rimini welcomed an esteemed colleague from Iran, Engineer Farshad Samadi Kohnehshahri. Eng. Samadi was selected to pursue this PhD in bioengineering at the University of Bologna and the Gait&Motion Analysis Laboratory of the Sol et Salus Hospital.
During the first year of his PhD, he conducted an ambitious systematic review on the application of machine learning to gait analysis data in cerebral palsy and stroke. Eng. Samadi did this work with the supervision of Professor Rita Stagni from the University of Bologna, Department of Electrical Energy and Information Engineering “Guglielmo Marconi”, and Andrea Merlo, scientific head of Sol et Salus and founder of MerloBioEngineering.
The following link will allow you to access the systematic review on the clinical use of machine learning in gait analysis.
We developed a useful and innovative form for critically appraising the 63 included studies, aiming to observe the performance of the existing machine learning literature in the domains of suitability, feasibility, and reliability.
This achievement marks the first result of a year-long collaboration with Eng. Samadi. We are confident that numerous other successes will be forthcoming in the coming months.
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