Relevant for Research Area

A - Foundations

B - Core Technologies


The BrainLinks-BrainTools (BLBT) project ComBiNE is aiming to create a miniaturized and next-geration wireless bidirectional neural interface, incorporating various technical key achievements of the BLBT cluster and applying this novel system in the closed-loop treatment of Parkinson’s disease (PD).On one hand, ComBiNE revealed a system platform which integrates custom neural read-out and stimulation circuits developed in BLBT, while focusing on multi-channel silicon needle probes with massive data output of several 10 MBit/s. Novel research approaches like segmented wireless power transfer inductors and fully adaptive energy conditioning electronics with power feedback and dynamic impedance matching have been investigated, optimized and applied to the ComBiNE implant platform. The project’s wireless implant interface is, to the authors’ best knowledge, the first to reveal automatic tuning for maximized efficiency and minimized electromagnetic emissions in the dynamic biological environment, while providing a very high bit rate data link to the signal processing electronics.

On the other hand, the project has investigated methods to establish a closed-loop adaptive deep brain stimulation for a rodent model of Parkinson’s disease. Therefore, a custom in-vivo setup for online recording, signal analysis and electrical stimulation was developed and utilized to investigate neural markers that give information about the state of the patient’s motor system and algorithmic control strategies which translate the observed markers into stimulation patterns. Enabling the resulting online monitoring and stimulation feedback system in this experimental setup, it was possible to evoke a significant improvement in the behavioral features of the PD rats in rotarod, open field and cylinder test scenarios, which shows the positive effect of the closed-loop system for the case of Parkinson’s disease.

Publications and Achievements

Journal publications:

[1]        S. Stöcklin, A. Yousaf, T. Volk and L. Reindl, “Efficient Wireless Powering of Biomedical Sensor Systems for Multichannel Brain Implants,” in IEEE Transactions on Instrumentation and Measurement, vol. 65, no. 4, pp. 754-764, April 2016. doi: 10.1109/TIM.2015.2482278

[2]        S. Stöcklin and L. Reindl, “Induktive kontaktlose Energieübertragung: Adaptive Impedanz- anpassung für maximalen Wirkungsgrad,“ in Elektronik Reader’s Choice 2018, August 2018.

Conference publications:

[4]        S. Stöcklin, A. Yousaf, T. Volk, L. Reindl, “A Maximum Efficiency Point Tracking System for Wireless Powering of Biomedical Implants,” Eurosensors XXIX, Freiburg, Germany, 2015.

[5]        S. Stöcklin, T. Volk, A. Yousaf, L. Reindl, “A Programmable and Self-Adjusting Class E Amplifier for Efficient Wireless Powering of Biomedical Implants,” 37th Annual International Conference of the IEEE EMBS, Milano, Italy, 2015.

[6]        S. Stöcklin, A. Yousaf, L. Reindl, “Adaptive Elektronik zur effizienten drahtlosen Energieversorgung biomedizinischer Implantate,“ 18. GMA/ITG Fachtagung Sensoren und Mess- systeme, Nürnberg, Germany, 2016.

[7]        S. Stöcklin, A. Yousaf and L. Reindl, “Adaptive Very High Frequency Wireless Power Transfer Systems for Biomedical Brain Implants,” Wireless Power Congress, Munich, 2017.

[8]        S. Castano-Candamil S. Mottaghi, V.A. Coenen, U.G. Hofmann and M. Tangermann, “Closed- loop Deep Brain Stimulation System for an Animal Model of Parkison’s Disease: A Pilot Study,” Proceedings of the 7th Graz Brain-Computer Interface Conference, 2017.

[9]        S. Mottaghi et al., “Hemi-Parkinsonian Rat Motor/Non-Motor Symptom Evaluation with Deep Brain Stimulation,” submitted for the 9th International IEEE EMBS Neural Engineering Conference, CA, USA, 2019.