Emulation Apparatus for Closed-Loop DBS Algorithm Testing
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Solution Overview
Problem
Current deep brain stimulation (DBS) systems deliver constant stimulation, lacking adaptability and real-time adjustment based on brain response, which limits their efficacy and increases side effects, and the difficulty in testing control algorithms in real patients hinders advancements in closed-loop stimulation protocols.
Innovation Solution
An emulation apparatus that models the temporal evolution of electrophysiological signals under stimulation, allowing for the simulation of DBS effects, enabling the testing of complex control algorithms and parameter adjustments in a controlled environment before clinical use.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If closed-loop DBS control is implemented to automatically adjust stimulation parameters based on brain response, then treatment efficacy is improved and side effects are reduced, but the complexity of the system increases and regulatory approval becomes more difficult
Solution Approach 1:
The patent creates a virtual copy of the human nervous system through the NEUROSCAPE emulation apparatus. This digital twin includes realistic neuronal models, network architectures, and physiological responses that replicate actual brain behavior under DBS stimulation. Researchers can test control algorithms on this virtual copy before clinical deployment, reducing regulatory barriers while maintaining treatment efficacy.
Solution Approach 2:
The emulation apparatus enables preliminary testing and validation of closed-loop control algorithms in a virtual environment before actual clinical implementation. This preliminary action allows comprehensive evaluation of algorithm performance, safety, and efficacy without risking patient safety, thereby simplifying the regulatory approval process for complex DBS systems.
2Measurement precision
If control algorithms are tested in real patients to improve closed-loop stimulation protocols, then algorithm performance is validated, but patient safety risks increase and the difficulty of testing remains high
Solution Approach 1:
Instead of testing directly on real patients, the patent uses a virtual copy (digital twin) of the nervous system that replicates physiological responses. This allows accurate validation of control algorithms through realistic simulation of brain responses to stimulation, eliminating patient safety risks while maintaining measurement precision.
Solution Approach 2:
The emulation apparatus serves as a protective buffer before clinical testing. By thoroughly validating algorithms in the virtual environment first, potential safety issues are identified and resolved beforehand, cushioning against harmful effects that might occur during actual patient testing.
3Ease of operation
If constant amplitude stimulation is delivered at fixed high frequency, then the treatment is simple to implement, but adaptability to individual patient responses is lost
Solution Approach 1:
The patent implements dynamic stimulation parameters that adapt in real-time based on measured brain activity. The system continuously monitors local field potentials and adjusts stimulation amplitude, frequency, or pulse width according to detected neural oscillations and patient response, transforming fixed constant stimulation into an adaptive dynamic system.
Solution Approach 2:
The closed-loop system incorporates feedback mechanisms where brain activity measurements (local field potentials) are continuously fed back to the stimulation controller. This feedback enables automatic adjustment of stimulation parameters to optimize therapeutic effect while minimizing side effects, providing adaptability while maintaining ease of operation through automated control.
Data Source
AI summary
An emulation apparatus emulates an electrophysiological signal derived from a target area of a human or animal nervous system under the influence of a stimulation signal applied to the human or animal body. A prior signal generator generates a prior signal representing an electrophysiological signal in the absence of stimulation. A test signal representing a stimulation signal is received and used by a modelling unit to derive a modulation signal representing the degree of modulation of the electrophysiological signal, in accordance with a model of the temporal evolution of the modulation of the electrophysiological signal caused by the stimulation signal. A modulation unit modulates the prior signal in accordance with the modulation signal to output an emulation signal representing an electrophysiological signal derived under the influence of the stimulation signal. The emulation apparatus has wide use in neuroscience research, bioengineering and clinical applications.