Multipolar Stimulator for Deep Brain Stimulation With Suppression of Stimulation-Induced Common-Mode Artifacts
A crucial part of treating neurological disorders like Parkinson's and epilepsy involves using Deep Brain Stimulation (DBS) systems. This paper describes a system that provides stimulation through a multipolar biphasic current source. It consists of two identical instances, one for each cerebral hemisphere, each containing five stimulators: four of them are locally connected, while the fifth is connected to an implantable pulse generator for monopolar stimulation. Each stimulator can deliver a maximum current of 12 mA with 9-bit resolution and offers passive charge balancing. Safety features include a DC blocking capacitor for electrical isolation, ensuring minimal DC current flow in case of system failure. The proposed design compensates for up to ±50% mismatch in stimulation current sinks by utilizing current sources, thereby distributing current errors in ideal proportions. The stimulator's voltage can be adjusted up to 30V. Based on post-layout Monte Carlo simulations, the common-mode voltage variates from its nominal value only by a standard deviation σ equal to 2 mV. Thus, referring to an overall 3σ variation, the proposed topology shows a 4× improvement in anchoring the brain voltage compared to the state-of-the-art. This architecture enables concurrent recording and stimulation, minimizing the artifacts generated by stimulation.
Authors
- Y. Koolivand (ORCID: https://orcid.org/0000-0002-3466-8768)
- Daniele D. Caviglia (ORCID: https://orcid.org/0000-0002-2145-1869)
- Orazio Aiello (ORCID: https://orcid.org/0000-0002-6938-9806)
- O. Shoaei (ORCID: https://orcid.org/0000-0002-8280-1834)
- R. Shokri (ORCID: https://orcid.org/0009-0006-5576-3808)
Institutions
- University of Tehran (IR)
- K. N. Toosi University of Technology (IR)
- University of Genoa (IT)
Publication Details
- Journal
- IEEE Access
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/access.2025.3602824
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 0.00