CPHS.group

Cyber Physical & Human Systems group

Cyber-Physical & Human Systems (CPHS) consist of cyber-physical computer systems and humans. Cyber-Physical Systems (CPS) arise from the networking of embedded systems through wired or wireless communication networks. The multidisciplinary research of CPS sees the following fields of application: medical systems, assistance systems, control-, automation-, and logistics-systems, security systems, systems for influencing and monitoring the environment, communication, and culture, e.g. in the context of a digital twin. Cyber-Physical & Human Systems (CPHS) additionally focus on the interactions between CPS and humans. The interactions between technology and humans take place on different levels, physically and digitally in cyberspace and represent the basis of "hybrid intelligence" in which humans use the capabilities of technology and vice versa, such as in modern assistance systems.

How can new technologies be used sensibly to further improve CPHS?

How can systems and people grow together in a human-machine symbiosis in a meaningful way?

What new opportunities do CPHS open up in the fields of industry and health?

What role does artificial intelligence play in a CPHS and how can it be used beneficially?

Focus

The Cyber-Physical & Human Systems group combines two focal points: 1. the cyber-physical system and 2. the human system, which are not just connected in space and time, but also increasingly on a cyber-digital level as a digital twin. The cyber-digital level also includes the use of artificial intelligence (AI), which e.g. enables smart assistance for the user in the real world, such as augmented reality. The AI is a link between the cyber-physical and human system, which is being researched by this specialist group on the basis of different applications.

Cyber-Physical System

Focus 1: Cyber-Physical System

The first professional focus is on the technical capabilities of the systems. The increasing performance of embedded systems and the advancing miniaturization of hardware including sensors enable new types of systems in prototype and product development. Especially in the field of mobile systems, wireless transmission technologies facilitate convenient use and the necessary user acceptance.

We develop solutions for:

  • Networking of systems, in particular using wireless technologies
  • Autonomous and embedded systems with hardware and software components
  • Digital twin of physical entities
  • Modeling, design and implementation of distributed AI systems in computer networks and innovative end devices such as wearables
Human System

Focus 2: Human System

The second specialist focus is on the augmentation of humans in order to expand their capacities in cyber-physical space. In particular, this will enable assistive augmentation in the future with mobile systems, which on the one hand requires a seamless integration of technological systems with our body and on the other hand the expansion of our cognitive, perceptual and motor skills, as well as the ability of a system to implicitly relate to the human context understand, enables. This performance is only made possible by the supply of artificial intelligence, which links the digital twins.

We develop solutions for:

  • Prevention - to identify diseases early and avoid them
  • Substitution - to technologically replace impaired functions, such as a disability
  • Extension - to expand the ability to interact with our environment

People

The CPHS.group is jointly headed by the Professors Horst Hellbrück and Denys Matthies.

Horst Hellbrück

Horst Hellbrück

Professor

Denys J.C. Matthies

Denys J.C. Matthies

Professor

Ruben Schlonsak

Ruben Schlonsak

Research Associate

Sebastian Hauschild

Sebastian Hauschild

Research Associate

Marco Gabrecht

Marco Gabrecht

Research Associate

Arina Borzistaia

Arina Borzistaia

Research Associate

Franziska Seidensticker

Franziska Seidensticker

Research Associate

Publications

2025

Yu, Z., Schlonsak, R. and Matthies, DJ.C.. (2025). Hacking Rokoko Smart Gloves for Tool Detection using Recurrent Neural Networks. In Proceedings of the 10th international Workshop on Sensor-Based Activity Recognition and Artificial Intelligence. Springer.

2024

Gabrecht, M.H. and Matthies, DJ.C.. (2024). RecogNNetion: Evaluating the Suitability of Automotive Radar for Human Gesture Recognition. In Proceedings of the 9th international Workshop on Sensor-Based Activity Recognition and Artificial Intelligence. ACM. https://doi.org/10.1145/3692066.3692074

Gabrecht, M.H., Harder, T. and Matthies, DJ.C.. (2024). Radar-based Gesture Recognition for Automotive Applications using a Lightweight Spatiotemporal CNN. In Proceedings of the 2024 International Conference on Advanced Visual Interfaces. ACM. https://doi.org/10.1145/3656650.3656699

Borzistaia, A. and Matthies, DJ.C.. (2024). Investigating the Role of Earable Wearables in Tongue Gesture Detection Using Inertial Sensors. In Proceedings of the 9th international Workshop on Sensor-Based Activity Recognition and Artificial Intelligence. ACM. https://doi.org/10.1145/3692066.3692073

Harder, T., Gabrecht, M.H. and Matthies, DJ.C.. (2024). Evaluating mmWave Radar for In-Car Gesture Recognition: Influence of Mounting Position, Antenna Configuration, and Range on Gesture Classification. In Proceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications. ACM. pp. 325-336. https://doi.org/10.1145/3640792.3675725

Schlonsak, R., Ginter, V. and Matthies, DJ.C.. (2024). Foot Gesture Recognition using Commercial Smart Insoles and a Recurrent Neural Network. In Proceedings of the 2024 International Conference on Advanced Visual Interfaces. ACM. https://doi.org/10.1145/3656650.3656700

Schlonsak, R. and Matthies, DJ.C.. (2024). A Multi-Sensor Smart Insole Setup for Unsupervised Data Collection in the Wild. In Proceedings of the Augmented Humans International Conference (AHs 2024). ACM. https://doi.org/10.1145/3652920.3652929

Matthies, DJ.C.., Borzistaia, A. and Hellbrück, H. (2024). Head Gesture Recognition using Gyroscopic Sensors integrated in Earbuds. In Proceedings of the Augmented Humans International Conference (AHs 2024). ACM. https://doi.org/10.1145/3652920.3652933

Hauschild, S., Wewetzer, L., Kusche, R., Steinhäuser, J. and Hellbrück, H. (2024). eMedic - An AI-based Mobile Decision Support System for Primary Care. In 58. DEGAM-Jahrestagung.

Seidensticker, F., Hauschild, S. and Hellbrück, H. (2024). Exploring Facial Feature Tracking in the Wild Using Apple's iPhone TrueDepth Sensor. In Proceedings of the 9th international Workshop on Sensor-Based Activity Recognition and Artificial Intelligence. ACM. https://doi.org/10.1145/3692066.3692076

Hauschild, S. and Hellbrück, H. (2024). Comparative Accuracy of Mobile Smart Devices and Clinical Blood Pressure Monitors for Pulse Transit Time and Blood Pressure Measurement. In BMC Primary Care. vol. 25. no. 1. https://doi.org/10.1186/s12875-024-02647-1

2023

Matthies, DJ.C.., Bretterbauer, F., Ginter, V. and Hellbrück, H. (2023). FitFone++: Tracking Exercise Repetitions of Home Workouts using a Smartphone. In Proceedings of the 16th International Conference on PErvasive Technologies Related to Assistive Environments. ACM. pp. 250-259. https://doi.org/10.1145/3594806.3594810

Matthies, DJ.C.., Bretterbauer, F. and Hellbrück, H. (2023). EarGestures: Hands-Free Micro-Gestures Detection using Earbuds to Support Mobile and Smart IoT Applications. In Proceedings of the 16th International Conference on PErvasive Technologies Related to Assistive Environments. ACM. pp. 296-303. https://doi.org/10.1145/3594806.3596520

Schmidt, SO. and Hellbrück, H. (2023). Position Estimation from UWB CIR using Autocorrelation and Deep Learning. In 2023 International Conference on Indoor Positioning and Indoor Navigation (IPIN). pp. 1-7. https://doi.org/10.1109/IPIN57070.2023.10332516

Schmidt, SO. and Hellbrück, H. (2023). UWB CIR-based 1D Localization from Single Anchor using Autocorrelation and Regression Models. In 2023 International Conference on Localization and GNSS (ICL-GNSS). pp. 1-6. https://doi.org/10.1109/ICL-GNSS57829.2023.10148061

Hauschild, S. and Hellbrück, H. (2023). Comparison of Inference Latency and Accuracy of Compact Image Classification Models on Heterogeneous IoT Platforms. Chapter in Wireless Sensor Networks. Springer Nature Switzerland. pp. 153-172. https://doi.org/10.1007/978-3-031-48831-3_11

2022

Matthies, DJ.C.., Haescher, M., Alm, R., Seidensticker, F. and Urban, B. (2022). CapGlasses 2: An Open Capacitive Sensing Toolkit for Creative Prototyping with Glasses. In Proceedings of the Augmented Humans International Conference 2022. ACM. https://doi.org/10.1145/3519391.3519395

Matthies, DJ.C.., Makino, Y. and Shinoda, H. (2022). SqueezAR: Exploring Squeeze Gesture Recognition for Augmented Reality. In 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW). IEEE. pp. 812-813. https://doi.org/10.1109/VRW55335.2022.00265

Cimdins, M., Schmidt, SO., Bartmann, P. and Hellbrück, H. (2022). Exploiting Ultra-Wideband Channel Impulse Responses for Device-Free Localization. In Sensors. vol. 22. https://doi.org/10.3390/s22166255

Soukieh, A., Yaqot, A. and Hellbrueck, H. (2022). HLS: Hierarchical Lossless Segmentation - A New Approach for Bilevel Image Compression. In 2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME). pp. 1-6. https://doi.org/10.1109/ICECCME55909.2022.9988021

Schmidt, SO., Cimdins, M. and Hellbrueck, H. (2022). SALOS - a UWB Single Anchor Localization System based on CIR-vectors - Design and Evaluation. In International Conference for Indoor Positioning and Navigation (IPIN) 2022. pp. 1-16. [pdf]

Hauschild, S. and Hellbrück, H. (2022). Latency and Energy Consumption of Convolutional Neural Network Models from IoT Edge Perspective. Chapter in Internet of Things. Springer International Publishing. pp. 385-396. https://doi.org/10.1007/978-3-031-20936-9_31

2021

Muthukumarana, S., Messerschmidt, MA., Matthies, DJ., Steimle, J., Scholl, PM. and Nanayakkara, S. (2021). ClothTiles: A Prototyping Platform to Fabricate Customized Actuators on Clothing using 3D Printing and Shape-Memory Alloys. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. ACM. pp. 1-12. https://doi.org/10.1145/3411764.3445613

Matthies, DJ., Woodall, A. and Urban, B. (2021). Prototyping Smart Eyewear with Capacitive Sensing for Facial and Head Gesture Detection. In Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing. pp. 476-480. https://doi.org/10.1145/3460418.3479361

Matthies, DJ., Elvitigala, DS., Fu, A., Yin, D. and Nanayakkara, S. (2021). mobiLLD: Exploring the Detection of Leg Length Discrepancy and Altering Gait with Mobile Smart Insoles. In The 14th PErvasive Technologies Related to Assistive Environments Conference. ACM. pp. 37-47. https://doi.org/10.1145/3453892.3453896

Matthies, DJ., Haescher, M., Chodan, W. and Bieber, G. (2021). DIY-PressMat: A Smart Sensor Mat for Posture Detection Applicable for Bed-exit Intention Detection, Pressure Ulcer Prevention, and Sleep Apnea Mitigation. In The 14th PErvasive Technologies Related to Assistive Environments Conference. ACM. https://doi.org/10.1145/3453892.3454001

Matthies, DJ., Weerasinghe, C., Urban, B. and Nanayakkara, S. (2021). CapGlasses: Untethered Capacitive Sensing with Smart Glasses. In Proceedings of the Augmented Humans International Conference 2021 (AHs '21). ACM. https://doi.org/10.1145/3458709.3458945

Kaluarachchi, T., Sapkota, S., Taradel, J., Thevenon, A., Matthies, DJ. and Nanayakkara, S. (2021). EyeKnowYou: A DIY Toolkit to Support Monitoring Cognitive Load and Actual Screen Time using a Head-Mounted Webcam. In Adjunct Publication of the 23rd International Conference on Mobile Human-Computer Interaction (MobileHCI '21). ACM. https://doi.org/10.1145/3447527.3474850

Elvitigala, DS., Matthies, DJ., Weerasinghe, C. and Nanayakkara, S. (2021). GymSoles++: Combining Google Glass with Smart Insoles to Improve Body Posture when Performing Squats. In The 14th PErvasive Technologies Related to Assistive Environments Conference (PETRA 2021). ACM. pp. 48-54. https://doi.org/10.1145/3453892.3453898

Cimdins, M., John, F. and Hellbrück, H. (2021). Flexible Data Acquisition with LoRaWAN and MQTT for Small and Medium-sized Enterprises. In Mobile Communication - Technologies and Applications; 25th ITG-Symposium. pp. 1-6.

John, F., Schmidt, SO. and Hellbrück, H. (2021). Flexible Arbitrary Signal Generation and Acquisition System for Compact Underwater Measurement Systems and Data Fusion. In Global Oceans 2021: San Diego - Porto. pp. 1-6.

John, F., Schmidt, SO. and Hellbrück, H. (2021). High Precision Open Laboratory 3D Positioning System for Automated Underwater Measurements. In Global Oceans 2021: San Diego - Porto. pp. 1-5.

John, F., Cimdins, M. and Hellbrück, H. (2021). Underwater Ultrasonic Multipath Diffraction Model for Short Range Communication and Sensing Applications. In IEEE Sensors Journal. vol. 21. no. 20. pp. 22934-22943. https://doi.org/10.1109/JSEN.2021.3110005

Matthies, DJ.C.., Harder, T., Bretterbauer, F., Ginter, V. and Hellbrück, H. (2021). FitFone: Tracking Home Workout in Pandemic Times. In The 14th PErvasive Technologies Related to Assistive Environments Conference. ACM. pp. 272-276. https://doi.org/10.1145/3453892.3461334

Leugner, S. and Hellbrück, H. (2021). Location Awareness in the Internet of Things. In Advances in Information and Communication: Proceedings of the 2021 Future of Information and Communication Conference (FICC), Volume 1. pp. 249-265.

Meusel, M., Wegerich, P., Bode, B., Stawschenko, E., Kusche-Vihrog, K., Hellbrück, H. and Gehring, H. (2021). Measurement of Blood Pressure by Ultrasound - The Applicability of Devices, Algorithms and a View in Local Hemodynamics. In Diagnostics. vol. 11. no. 12. https://doi.org/10.3390/diagnostics11122255

Hellbrück, H., Ardelt, G., Wegerich, P. and Gehring, H. (2021). Brachialis Pulse Wave Measurements with Ultra-Wide Band and Continuous Wave Radar, Photoplethysmography and Ultrasonic Doppler Sensors. In Sensors. MDPI. vol. 21. no. 165. https://doi.org/10.3390/s21010165

Hauschild, S. and Hellbrück, H. (2021). Sind portable intelligente Geräte für die Diagnostik in der Hausarztpraxis geeignet?. Chapter in Deutsche Gesellschaft für Allgemeinmedizin und Familienmedizin. 55. Kongress für Allgemeinmedizin und Familienmedizin. German Medical Science GMS Publishing House. https://doi.org/10.3205/21degam204

Cimdins, M., Schmidt, SO. and Hellbrück, H. (2021). Comparison of I/Q- and Magnitude-based UWB Channel Impulse Responses for Device-free Localization. In International Conference on Localization and GNSS.

Schmidt, SO. and Hellbrueck, H. (2021). Detection and Identification of Multipath Interference with Adaption of Transmission Band for UWB Transceiver Systems. In International Conference for Indoor Positioning and Navigation (IPIN) 2021. pp. 1-16. [pdf]

2020

Muthukumarana, S., Elvitigala, DS., Forero Cortes, JP., Matthies, DJ. and Nanayakkara, S. (2020). Touch me gently: recreating the perception of touch using a shape-memory alloy matrix. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. ACM. pp. 1-12. https://doi.org/10.1145/3313831.3376491

Elvitigala, DS., Matthies, DJ. and Nanayakkara, S. (2020). StressFoot: Uncovering the Potential of the Foot for Acute Stress Sensing in Sitting Posture. In Sensors. MDPI. vol. 20. no. 10. pp. 2882. https://doi.org/10.3390/s20102882

Boldu, R., Matthies, DJ., Zhang, H. and Nanayakkara, S. (2020). AiSee: An Assistive Wearable Device to Support Visually Impaired Grocery Shoppers. In Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies. ACM. vol. 4. no. 4. pp. 1-25. https://doi.org/10.1145/3432196

John, F., Kusche, R., Adam, F. and Hellbrück, H. (2020). Differential Ultrasonic Detection of Small Objects for Underwater Applications. In Global Oceans 2020: Singapore - U.S. Gulf Coast. pp. 1-7. https://doi.org/10.1109/IEEECONF38699.2020.9389186

Cimdins, M., Schmidt, SO. and Hellbrück, H. (2020). MAMPI-UWB - Multipath-Assisted Device-Free Localization with Magnitude and Phase Information with UWB Transceivers. In Sensors. MDPI. vol. 20. no. 24. pp. 7090.

Kusche, R., John, F., Cimdins, M. and Hellbrück, H. (2020). Contact-Free Biosignal Acquisition via Capacitive and Ultrasonic Sensors. In IEEE Access. IEEE. vol. 8. pp. 95629-95641. https://doi.org/10.1109/access.2020.2995861