The Embodied Machine Learning node

The node for Embodied Machine Learning investigates how machine learning can support the personalisation of embodied services and technologies.

An example of the approach is a current research project combining research into open-ended tools for instructed physical training, with approaches to interactive machine learning to support personalised physiotherapeutically training. The goal is to empower both physiotherapists and patients to take control over their tools, and adapt them to suit their specific needs and the practices at hand. Of central concern is to present devices that allow for fluent adaptation and human control of the personalisation process, maintaining the fluent concept of what is considered a ‘correct’ exercise execution in physiotherapy.

The node for Embodied Machine Learning – more information about studies conducted within the node at the Interactive Machine Learning for Personalised Physical Training project page.

Funding provided by The Swedish Research Council.