CPR Tutor (2020)

The CPR tutor is a tool that helps users learn and practice CPR skills using real-time feedback and multimodal data. It uses sensors to measure the kinematic and electromyographic data of the user while performing CPR on a manikin. The system uses recurrent neural networks to detect and classify chest compressions according to five performance indicators: compression rate, compression depth, compression release, hand position, and arm posture. The system then provides audio feedback to correct the most critical mistakes and improve CPR performance. The CPR tutor aims to enhance the learning experience and outcomes of CPR training by providing personalised and adaptive feedback based on multimodal data.

Published by Daniele Di Mitri

Daniele Di Mitri is a research group leader at the DIPF - Leibniz Institute for Research and Information in Education and a lecturer at the Goethe University of Frankfurt, Germany. Daniele received his PhD entitled "The Multimodal Tutor" at the Open University of The Netherlands (2020) in Learning Analytics and wearable sensor support. His research focuses on collecting and analysing multimodal data during physical interactions for automatic feedback and human behaviour analysis. Daniele's current research focuses on designing responsible Artificial Intelligence applications for education and human support. He is a "Johanna Quandt Young Academy" fellow and was elected "AI Newcomer 2021" at the KI Camp by the German Informatics Society. He is a member of the editorial board of Frontiers in Artificial Intelligence journal, a member of the CrossMMLA, a special interest group of the Society of Learning Analytics Research, and chair of the Learning Analytics Hackathon (LAKathon) series.