AG Datenanalyse in den Lebenswissenschaften

>>Forschungsschwerpunkte

Within ThiMEDOP, the research group “Data Analysis in Life Sciences" focuses on the areas of:

Sensor technologies for biosignals (especially bioelectric signals including EEG, ECG, EMG)
Methods for automatic artefact detection and correction in biosignals
Multimodal data acquisition and data fusion
Close-to-hardware and close-to-sensor biosignal processing
Machine Learning for biomedical applications

Our group is interested in supporting R&D on novel mobile and intelligent sensor technologies and signal processing for monitoring electrophysiological, respiratory and hemodynamic activity in medical applications. Within the overall frame of R&D on sensor technologies, signal processing, and analysis for mobile medical monitoring and body sensor network applications, we collaborate with partners in industry and academia and cover three main areas of expertise:

Integration of novel materials and composites into comprehensive electronic sensor components for sequential or simultaneous multimodal biosignal acquisition.
Development and integration of mechanical components for sensor placement and fixation on the human body for optimal data quality and applicability in mobile use cases.
Development and integration of biosignal processing methods for signal enhancement, artefact detection / correction, and machine learning approaches for automated analysis and classification.

Publikationen

2024

Tamburro, G., Bruna, R., Fiedler, P., De Fano, Antonio, Raeisi, K., Khazaei, M., Zappasodi, F., Comani, S.: An Analytical Approach for Naturalistic Cooperative and Competitive EEG-Hyperscanning Data: A Proof-of-Concept Study, Sensors, 2024, vol. 24, 2995 https://doi.org/10.3390/s24102995

2023

Fiedler, P., Graichen, U.; Zimmer, E.; Haueisen, J.: Simultaneous dry and gel-based high-density EEG recordings, Sensors, 2023, vol. 23, 9745 https://doi.org/10.3390/s23249745

Tamburro, G.*; Fiedler, P.*; De Fano, A.; Raeisi Nafchi, K.; Khazaei, M.; Bruña, R.; Filho, E.; Zappasodi, F.; Comani, S.: An ecological study protocol for the multimodal investigation of the neurophysiological underpinnings of dyadic joint action, Frontiers in Human Neuroscience, 2023, vol. 17, 1305331 https://doi.org/10.3389/fnhum.2023.1305331

Warsito, I.F.; Komosar, M.; Bernhard, M.A.; Fiedler, P.; Haueisen, J.: Flower electrodes for comfortable dry electroencephalography; Scientific Reports, 2023, Vol. 13, 16589 http://dx.doi.org/10.1038/s41598-023-42732-8

Pusil, S.; Zegarra-Valdivia, J.; Cuesta, P.; Laohathai, C.; Cebolla, A.M.; Haueisen, J.; Fiedler, P.; Funke, M.; Maestú, F.; Cheron, G.: Effects of spaceflight on the default mode network: EEG insights in brain alpha power and functional connectivity; Scientific Reports, 2023, Vol. 13, 9489 https://doi.org/10.1038/s41598-023-34744-1

Fiedler, P.; Haueisen, J.; Cebolla Alvarez A.M.; Cheron, G.; Cuesta, P.; Maestú, F.; Funke, M.: Noise characteristics in spaceflight multichannel EEG; PLoS One, 2023, Vol. 18, No. 2, e0280822 https://doi.org/10.1371/journal.pone.0280822

2022

Ng, C.R.; Fiedler, P.; Kuhlmann, L.; Liley, D.; Vasconcelos, B.; Fonseca, C.; Tamburro, G.; Comani, S.; Lui, T. K.-Y.; Tse, C.-Y.; Warsito, I.F.; Supriyanto, E.; Haueisen, J.: Multi-center evaluation of gel-based and dry Multipin EEG caps, Sensors, 2022, Vol. 22, No. 20, 8079 https://doi.org/10.3390/s22208079

Croce, P.; Franca, T.; Tamburro, G.; Fiedler, P.; Comani, S.; Zappasodi, F.: Brain Electric Microstates for the Control of the Steady State Motor Output; Journal of Neural Engineering, 2022, Vol. 19, 056042 https://doi.org/10.1088/1741-2552/ac975b

Fiedler, P.; Fonseca, C.; Supriyanto, E.; Zanow, F.; Haueisen, J.: A high-density 256-channel cap for dry electroencephalography; Human Brain Mapping, 2022, Vol. 43, No. 4, pp. 1295-1308 https://doi.org/10.1002/hbm.25721

2021

Lopes, C.; Fiedler, P.; Alves, E.; Barradas, N.P.; Vaz, F.: Me doped Ti-Me intermetallic thin films used for dry biopotential electrodes: A comparative case study; Sensors, 2021, Vol. 21, No. 23, 8143 https://doi.org/10.3390/s21238143

Vasconcelos, B.*; Fiedler, P.*; Machts, R.; Haueisen, J.; Fonseca, C.: The Arch Electrode: A Novel Dry Electrode Concept for Improved Wearing Comfort; Frontiers in Neurosciences, 2021, Vol. 15, 748100 *First two authors acknowledge equal authorship https://doi.org/10.3389/fnins.2021.748100

Heijs, J.J.A.; Havelaar, R.J.; Fiedler, P.; Van Wezel, R.J.A.; Heida, T.: Validation of soft, multipin, dry EEG electrodes; Sensors, 2021, Vol. 21, 6827 https://doi.org/10.3390/s21206827

Mulyadi, I.H.; Fiedler, P.; Eichardt, R.; Haueisen, J.; Supriyanto, E.: Pareto Optimization for Electrodes Placement on ECG Smart Shirts: Compromises between Electrophysiological and Practical Aspects; Medical & Biological Engineering & Computing, 2021, Vol. 59, No. 2, pp. 431-447

2020

Rodrigues, M.S.; Fiedler, P.; Küchler, N.; Domingues, R.P. ; Lopes, C. ; Borges, J.; Haueisen, J.; Vaz, F.: Dry Electrodes for Surface Electromyography Based on Architectured Titanium Thin Films; Materials, 2020, Vol. 13, 2135

2019

di Fronso, S.; Fiedler, P.; Tamburro, G.; Haueisen, J.; Bertollo, M.; Comani, S.: Dry EEG in Sports Sciences: A Fast and Reliable Tool to Assess Individual Alpha Peak Frequency Changes Induced by Physical Effort; Frontiers in Neuroscience, 2019, Vol. 13:982 *First two authors acknowledge equal authorship

2018

Piątek, Ł.; Fiedler, P.; Haueisen, J.: Eye State Classification from EEG Recordings using Machine Learning Algorithms; Digital Medicine, 2018, Vol. 4, No. 2, pp. 84-95

Virtanen, J.; Somppi, S.; Törnqvist, H.; Jeyhani, V.; Fiedler, P.; Gizatdinova, Y.; Majaranta, P.; Väätäjä, H.; Cardó A.V.; Lekkala, J.; Tuukkanen, S.; Surakka, V.; Vainio, O.; Vehkaoja, A.: Evaluation of Dry Electrodes in Canine Heart Rate Monitoring; Sensors, 2018, Vol., 18, No. 6

Wunder, S.; Hunold, A.; Fiedler, P.; Schlegelmilch, F.; Schellhorn, K.; Haueisen, J.: Novel bifunctional cap for simultaneous electroencephalography and transcranial electrical stimulation; Nature Scientific Reports, 2018, Vol. 8, 7259

Stone, D.; Tamburro, G.; Fiedler, P.; Haueisen, J.; Comani, S.: Automatic removal of physiological artifacts in EEG: the Optimized Fingerprint Method for sports science applications; Frontiers in Human Neuroscience, 2018, Vol. 12:96, No. 96

Tamburro, G.; Fiedler, P.; Stone, D.; Haueisen, J.; Comani, S.: A new ICA-based fingerprint method for the automatic removal of physiological artifacts from EEG recordings; PeerJ, 2018, Peer J, 2018, Vol. 6, e4380

Fiedler, P.; Mühle, R.; Griebel, S.; Pedrosa, P.; Fonseca, C.; Vaz, F.; Zanow, F.; Haueisen, J.: Contact Pressure and Flexibility of Multipin Dry EEG Electrodes; IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2018, Vol. 26, No. 4, pp. 750-757