The opportunity of using this technological solution in daily life can have an enormous impact on many aspects of neuromuscular diseases, from the early diagnosis to the evaluation of intervention outcome, up to the monitoring of rehabilitation treatments. However, the use of these sensors requires basic knowledge on multi-body dynamics, human biomechanical models, and sensor-to-segment calibration.
In the first part of this tutorial, an in-depth analysis of the altered kinematic patterns of some neuro-muscular pathologies is presented. An experimental-based computational model of the motor control function of the brain is explained. Finally, some real examples of kinematic analysis conducted on pathological populations, such as Parkinson’s, Multiple Sclerosis, Cerebral Palsy, or Stroke, are presented.
In the second part, attendees will be guided through the creation of a biomechanical model in MATLAB, fed with anonymized IMU data of patients with neuromuscular disease, up to the extraction of the kinematic quantities of interest for the analysis of intervention outcome.
