In this paper, we investigate and present the possible benefits of combining a very powerful Augmented Reality (AR) Headset (Microsoft Hololens) with the Machine Learning (ML) powered tooltracking system. The ongoing automation of modern production processes requires novel human-computer interaction... Continue

In this paper we motivate, describe and evaluate the Machine Learning enabled tool tracking system, that is jointly developed with Fraunhofer IIS. Despite the ongoing automation of modern production processes, manual labor continues to be necessary due to its flexibility and ease of deployment. A... Continue

We are proud to announce that our MedTech E-Lab team PalliCare (https://www.mad.tf.fau.de/teaching/innolab/pallicare/) published the work on their prototype at the annual conference of the German Association for Palliative Medicine - “13. DGP Kongress”. The developed system enables home-monitoring o... Continue

This paper presents a handwriting recognition (HWR) system that deals with online character recognition in real-time. Our sensor-enhanced ballpoint pen delivers sensor data streams from triaxial acceleration, gyroscope, magnetometer, and force signals at 100𝐻𝑧. As most existing datasets do not meet ... Continue

Katharina joined the MAD Team in September 2020. She studied Medical Engineering at FAU with focus on pattern recognition and machine learning. For her master's thesis, she spent 6 months in Belgium collaborating with the maternal and fetal health company Bloomlife. Her main interest was to analyze ... Continue