Implanted DBS Controller for Autonomous Stimulation Adjustment
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Solution Overview
Problem
Deep brain stimulation (DBS) systems face challenges in optimizing stimulation parameter settings, leading to time-consuming and often suboptimal outcomes, requiring frequent adjustments and clinician involvement, which is costly and inconvenient for patients.
Innovation Solution
An implanted controller capable of semi-autonomously adjusting therapeutic stimulation based on patient feedback, using a processor to generate and adjust stimulation signals without external input, and executing machine learning algorithms to determine optimal parameters for improved efficacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If stimulation parameters are adjusted manually by clinicians during fitting sessions, then therapeutic efficacy can be optimized, but the process becomes time-consuming and requires frequent patient visits to clinics
Solution Approach 1:
The implanted controller autonomously adjusts stimulation parameters by receiving patient feedback through the patient input device and automatically modifying stimulation signals without requiring clinician intervention or external controllers, enabling the system to serve itself
Solution Approach 2:
The system implements a closed-loop feedback mechanism where patient responses to stimulation efficacy are continuously received via the patient input device, processed by the implanted controller, and used to automatically adjust stimulation parameters for optimized therapeutic outcomes
2Reliability
If stimulation parameters are adjusted frequently to maintain efficacious therapy, then therapeutic outcomes are maintained, but the cost and inconvenience to patients increase due to required clinic visits
Solution Approach 1:
The implanted controller performs autonomous parameter adjustment using internally processed patient feedback, eliminating the need for patients to travel to clinics for frequent fitting sessions while maintaining consistent therapeutic outcomes
Solution Approach 2:
The patient input device serves as an intermediary between the patient and the implanted controller, enabling remote feedback transmission that allows parameter adjustment without direct clinician-patient interaction at the clinic
3Adaptability or versatility
If manual fitting processes are used with ex-vivo controllers, then parameter adjustment is possible, but the system requires external devices and clinician involvement increasing complexity
Solution Approach 1:
The system merges the patient input device with the implanted controller into an integrated system, combining feedback reception and parameter adjustment functions within the implant to reduce external components and simplify the overall system architecture
Solution Approach 2:
The invention extracts the parameter adjustment capability from external ex-vivo controllers and relocates it directly into the implanted controller, eliminating the need for separate external programming devices and reducing system complexity
Data Source
AI summary
Some embodiments relate to a method of adjusting therapeutic stimulation from a therapeutic stimulation system. The method comprising: providing therapeutic stimulation based on a plurality of stimulation parameters to a patient with an implanted controller and at least two electrodes; receiving data indicative of feedback associated with a patient rating of the therapeutic stimulation via a patient input device; automatically adjusting, with the implanted controller, at least one of the plurality of stimulation parameters; and providing adjusted therapeutic stimulation based on the adjusted at least one stimulation parameter to the patient with the controller and the at least two electrodes. The method further comprises receiving additional data indicative of feedback associated with another patient rating of the adjusted therapeutic stimulation; and executing a machine learning algorithm based on the stimulation parameters and received data indicative of feedback, to determine preferred stimulation parameters.