Project Details
Abstract
The research team proposed “Research of Digital Signal Processing Chip Design for
Closed-Loop Parkinson Deep Brain Stimulation SoC System” to is responsible for digital signal
processing algorithms and architecture design for the overall integrated Closed-Loop DBS project. In
the first year, our target is for the development of a new closed-loop deep brain electrical stimulation
of discrete elements of the system platform, for Parkinson's disease patients. Through local field
potentials recorded waveform sensed by the patientssubthalamic nucleus of Parkinson's, the system
preamp and analog-digital conversion circuit processing, and then according to the DBS control
algorithms to control electrical stimulation output parameters. With adaptive DBS stimulation control,
a real-time adjustable closed-loop electrical stimulation for Parkinson disease can be realized. The
operator can execute the analyzing algorithms based on the calculation result of LFP in the band of
13~35Hz through the human--machine interface to decide the DBS stimulation trigger threshold. In
the second year, the DSP control chip for closed-loop DBS is designed based on clinical data and
parameters and is realized ready to be integrated with other sub-projects. In the third year, a complete
DBS system in SoC integration is realized to achieve real-time adaptive closed-loop DBS stimulation.
In this sub-project, we will implement the adaptive TH adjustable high-precision closed-loop
DBS signal processing chip. The adaptive control algorithm is designed based on the system
parameters variation tolerable LZC analysis, multi-reference sources light machine learning. The low
power, high-efficient stimulation pattern is designed based on low-frequency phase-alignment
disrupting mechanism to break the over-synchronization signal in STN, which is totally different
from the traditional high frequency stimulation pattern. With algorithmic low power architecture
design, a high stimulation accuracy closed-loop DBS signal processing control chip can be realized to
operate for longer time. With SoC, the real-time adaptive closed-loop DBS can be realized with
immediate and effective Parkinson detection and treatment. In this way, the real-time adaptive brain
pacemaker with self-learning mechanism can be realized in clinical applications and the main goal in
this sub-project is achieved at the same time. Once we can find the find theoretical and clinical
mechanism of DBS system for the treatment of Parkinson's disease through the research study of
adaptive closed-loop DBS control and stimulation, it would be a great breakthrough progress for the
clinical treatment of Parkinson's disease.
Project IDs
Project ID:PB10507-1725
External Project ID:MOST105-2221-E182-078
External Project ID:MOST105-2221-E182-078
Status | Finished |
---|---|
Effective start/end date | 01/08/16 → 31/07/17 |
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