Cognition-aware systems

Computing systems that sense, model, and adapt to their users’ cognitive states.

Project overview

In today’s information society, knowledge is created at an ever-increasing pace. As a result, most of us face constant pressure to consume information and acquire new knowledge. But information gain and learning require time and mental resources. While the proliferation of ubiquitous computing devices, such as smartphones, enables us to consume information anytime and anywhere, technologies are often disruptive rather than sensitive to the current user context.

For example, mobile applications trigger a plethora of notifications throughout the day, which often causes interruptions and breaks users’ concentration. In addition, people exhibit different levels of concentration and cognitive capacity over the course of the day. During phases of low performance, the ability to concentrate is very limited, which negatively affects the effectiveness  of information intake. Mobile applications do not take these variations in performance into account and often overburden the user with information or cause boredom due to a lack of stimulation.

Cognition-aware systems sense, model, and adapt to users’ current cognitive states and systematic fluctuations, including varying states of alertness, fatigue, and general receptivity. In our research, we create tools and applications that use mobile and stationary sensors to monitor attention and reconstruct circadian rhythms of alertness and homeostasis. Technologies aware of our fluctuating cognitive capacities enable the development of interfaces that consider our attentional limitations and boost our focus and productivity.


We are actively collaborating with researchers from Osaka Prefecture University in Japan and the German Research Center for Artificial Intelligence in Kaiserslautern, Germany.

Project team

Contact details


Dingler, Tilman, Ken Singer, Niels Henze, and Tonja Machulla. "Extracting Daytime-Dependent Alertness Patterns from Mobile Game Data." In Proceedings of the 22nd international conference on human-computer interaction with mobile devices and services, 2020.

Tag, Benjamin, Tilman Dingler, Andrew W. Vargo, and Vassilis Kostakos. "Inferring Circadian Rhythms of Cognitive Performance in Everyday Life." IEEE Pervasive Computing, 19, no. 3 (2020): 14–23.

Dingler, Tilman, Benjamin Tag, Evangelos Karapanos, Koichi Kise, and Andreas Dengel. "Workshop on Detection and Design for Cognitive Biases in People and Computing Systems." In Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, pp. 1–6. 2020.

Babaei, Ebrahim, Namrata Srivastava, Joshua Newn, Qiushi Zhou, Tilman Dingler, and Eduardo Velloso. "Faces of Focus: A Study on the Facial Cues of Attentional States." In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, pp. 1–13. 2020. https://

Brishtel, Iuliia, Anam Ahmad Khan, Thomas Schmidt, Tilman Dingler, Shoya Ishimaru, and Andreas Dengel. "Mind Wandering in a Multimodal Reading Setting: Behavior Analysis & Automatic Detection Using Eye-Tracking and an EDA Sensor." Sensors, 20, no. 9 (2020): 2546.

Zhou, Qiushi, Joshua Newn, Namrata Srivastava, Tilman Dingler, Jorge Goncalves, and Eduardo Velloso. "Cognitive Aid: Task Assistance Based On Mental Workload Estimation." In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems, pp. 1–6. 2019.

Tag, Benjamin, Andrew W. Vargo, Aman Gupta, George Chernyshov, Kai Kunze, and Tilman Dingler. "Continuous alertness assessments: Using EOG glasses to unobtrusively monitor fatigue levels In-The-Wild." In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, pp. 1–12. 2019.

Sarsenbayeva, Zhanna, Niels van Berkel, Danula Hettiachchi, Weiwei Jiang, Tilman Dingler, Eduardo Velloso, Vassilis Kostakos, and Jorge Goncalves. "Measuring the effects of stress on mobile interaction." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 3, no. 1 (2019): 1–18.