Adaptive Deep Brain Stimulation for Mood Disorder Treatment
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Solution Overview
Problem
Current deep brain stimulation techniques for mood disorders lack adaptability to a patient's changing emotional state, leading to potential over- or under-stimulation and difficulty in differentiating between normal and pathological mood changes, especially in patients with variable brain signals.
Innovation Solution
A closed-loop system that includes implantable sensors and electrodes for continuous monitoring of physiological and environmental measures, such as brain activity, motor activity, speech patterns, and environmental conditions, to adjust stimulation amplitude and frequency based on real-time mood indicators, ensuring personalized and adaptive neuromodulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous open-loop stimulation is applied to the superolateral medial forebrain bundle, then mood disorder treatment effectiveness is improved, but emotional flexibility and adaptability to changing emotional states deteriorates
Solution Approach 1:
The patent implements a closed-loop system that continuously monitors physiological signals (heart rate, skin conductance, temperature, respiration) and uses this feedback to dynamically adjust stimulation parameters. This feedback mechanism enables the system to adapt to changing emotional states in real-time, resolving the contradiction between maintaining treatment effectiveness and preserving emotional flexibility.
Solution Approach 2:
The system transitions from static continuous stimulation to dynamic adaptive stimulation by continuously adjusting stimulation parameters based on real-time physiological monitoring. This dynamic approach allows the system to maintain therapeutic efficacy while adapting to the patient's changing emotional state, thereby preserving emotional flexibility.
2Stability of the object's composition
If continuous stimulation is applied regardless of emotional state, then consistent neuromodulation is achieved, but over-stimulation or under-stimulation occurs depending on patient's current emotional state
Solution Approach 1:
The closed-loop system uses real-time physiological feedback to continuously adjust stimulation parameters, ensuring that the stimulation precision matches the patient's current emotional state. This prevents both over-stimulation and under-stimulation by adapting the stimulation intensity to the actual emotional condition.
Solution Approach 2:
The system dynamically changes stimulation parameters (amplitude, frequency, pulse width) based on physiological signal analysis. This parameter adaptation allows the system to maintain consistent therapeutic effect while avoiding the pitfalls of fixed-parameter stimulation that leads to over- or under-stimulation.
3Reliability
If continuous stimulation is applied, then therapeutic effect is maintained, but brain adaptation to stimulation may occur reducing long-term effectiveness
Solution Approach 1:
The system implements periodic or intermittent stimulation patterns based on physiological state detection rather than continuous stimulation. By activating stimulation only when pathological emotional states are detected, the system maintains therapeutic effectiveness while reducing the risk of neural adaptation that occurs with continuous exposure.
Solution Approach 2:
The system autonomously determines when stimulation is needed based on real-time physiological monitoring, activating only during pathological states. This self-regulating approach prevents unnecessary continuous stimulation that would lead to adaptation, thereby maintaining long-term therapeutic effectiveness.
4Adaptability or versatility
If brain signals are monitored to detect mood changes, then adaptive stimulation can be implemented, but difficulty arises in differentiating between normal and pathological mood changes
Solution Approach 1:
The system employs a multi-parameter monitoring approach, simultaneously measuring multiple physiological signals (heart rate, skin conductance, temperature, respiration) rather than relying on a single indicator. This multi-functional sensing approach enables more precise differentiation between normal and pathological mood changes by analyzing patterns across multiple physiological dimensions.
Solution Approach 2:
The system detects mood states through changes in multiple physiological parameters simultaneously, using pattern recognition across these parameters to distinguish pathological from normal mood variations. This multi-parameter analysis approach improves measurement precision in mood state differentiation.
Data Source
AI summary
A system for brain stimulation of a patient is provided, the system having an implantable stimulator, at least one sensor component for acquiring at least one measure indicative of patient's mood, and at least one implantable stimulation electrode, designed for providing electrical pulses stimulating inside the patient's brain. The at least one stimulation electrode is connectable, through an implantable connector, to the implantable stimulator, the implantable stimulator having at least one programmable channel for conducting the electrical stimulation pulses to the at least one stimulation electrode, and being adapted for receiving continuous input signals from the at the least one sensor component. The system also has a computational unit for processing the at least one measure, and a patient's body external control interface (5) for patient and/or physician interactions.