Using Gait ML for disease indentification
Human gait is a unique signature that provides deep insights into the neurological aspects of the person. Gait analysis can provide us a with options for early detection of various neurological conditions.
The session talks about using Machine Learning frameworks with Random Forest (RF) and Support Vector Machine (SVM) classifiers to train a model for early detection of neurological and neuromuscular diseases using the gait analysis from a robotic gait assistance device.
Outline/Structure of the Talk
Attendees will learn how the different classification models are used for disease detection using gait analysis techniques. They will also learn the challenges in building deploying these training models in the real world.
Data Scientists, ML Engineers, Medical ML enthsiasts
Prerequisites for Attendees
It would be good for attendees to have a basic understanding of human gait analysis techniques in order to appreciate the complexities involved in using it for disease detection.