Inhalt des Dokuments
Dr.-Ing. Jan-Niklas Voigt-Antons
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Jan-Niklas Voigt-Antons joined the Telekom Innovation Laboratories as a research scientist in January 2009 and is working there since 2014 as a senior research scientist. He received his diploma in psychology in 2008 from the Technische Universität Darmstadt, Germany, a Doctor-of-Engineering degree in 2014 from the Technische Universität Berlin, Germany and has been doing research at the Quality and Usability Lab at the Technische Universität (TU) Berlin, since. His research interests are in Quality-of-Experience evaluation and its physiological correlates with an emphasis on media transmissions and human-machine-interaction, including neural processing of multimodal interaction. During summer 2012 he was visiting researcher at MuSAE Lab (INRS-EMT), Canada where he examined neural correlates of quality perception for complex speech signals. In spring 2014 he was visiting researcher at the department of psychology of NTNU, Norway where he examined neural correlates of audiovisual asynchrony.
QULab research group: Quality , User Experience, Augmented
and Virtual Reality
• Multimedia Experience (Usability evaluation methods, Quality-of-Experience evaluation physiological measures)
• Interaction Design (Adaptive software, data mining, sensor and behavioural data)
Measuring of immersive media experience
Exergaming in virtual reality 
DemTab - Tabletgestützte ambulante Versorgung von Menschen mit Demenz 
VoiceAdapt - Adaptives Sprachtraining für ältere Menschen mit Aphasie 
OurPuppet - Pflegeunterstützung mit einer interaktiven Puppe für informell Pflegende 
PflegeTab - Technik für mehr Lebensqualität trotz Pflegebedürftigkeit bei Demenz (GKV) 
Quality of Mobile Gaming 
Bernstein Focus Neurotechnology - Berlin (BFNT - B) 
|Project||Study Project Quality
& Usability (6/9 CP)
Current thesis offers of our lab can be found here . Please contact me via email if you are interested in doing a thesis supervised by me.
Current job offers of our lab can be found here .
+49 30 8353 58 377
AddressTechnische Univertistät Berlin
Quality and Usability Lab
Telekom Innovation Laboratories
10587 Berlin, Germany
|Autor||Trahms, Carola and Möller, Sebastian and Voigt-Antons, Jan-Niklas|
|Buchtitel||2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX)|
|Adresse||Piscataway, NJ, USA|
|Zusammenfassung||Obtaining reliable quality ratings for applications is a time-consuming and expensive process. Touch interaction data, however, can be recorded without additional effort when using mobile applications. It could be used to assess usability without having to conduct dedicated tests. This work investigates the possibility to estimate quality ratings for two mobile games solely from touch interactions without relying on performance or game logic measures. To capture pragmatic as well as hedonic quality aspects of usability as ground truth, the AttrakDiff Mini questionnaire was chosen. Two different simple mobile games were used to capture a variety of touch interactions (taps and swipes). To influence the user ratings, three versions of the games were presented: one in original quality, the two others with manipulated interaction quality. Touch interaction features were extracted from the recorded interaction data and used for training models using linear regression and multivariate adaptive regression splines (MARS). The models were built with three times 10-fold cross-validation on each game data set separately. The results indicate that the ratings for pragmatic quality are estimated significantly better than for hedonic quality and attractiveness. Furthermore, the transferability of the models from one game to the other was examined and the touch features that were most important for estimating quality ratings in this study were identified. Touch interactions seem to carry some information on usability, especially pragmatic quality, and it seems to be possible to estimate a broad direction of the user's usability perception. Just a few touch features carry the most information and can be used for simple but fast and powerful models. This could be applied as an automatic analytic tool for mobile applications as well as in adaptive applications that optimize themselves in terms of usability perceived by individual users.|