Implantable Tinnitus Stimulator with Closed-Loop Sensor Feedback
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Solution Overview
Problem
Current treatments for tinnitus are inadequate in providing full relief for the majority of sufferers, as the mechanisms of tinnitus are not well understood and existing methods such as behavioral therapy and drug treatments are not effective for many individuals.
Innovation Solution
A sensor-based tinnitus treatment system that includes an implantable stimulator and sensors to apply electrical stimulation, with a controller that modulates the stimulation based on sensor data from both internal and external sensors to effectively treat tinnitus, utilizing feedback and machine learning algorithms to improve treatment outcomes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional behavioral therapy and drug treatments are used for tinnitus, then treatment can be provided, but they do not provide full relief for the majority of sufferers
Solution Approach 1:
The system incorporates sensors that continuously monitor physiological parameters (such as heart rate, skin conductance, and muscle activity) and provide real-time feedback to adjust the electrical stimulation parameters. This closed-loop feedback mechanism allows the treatment to adapt to the patient's changing physiological state, improving effectiveness where traditional static treatments fail
Solution Approach 2:
The electrical stimulation parameters (amplitude, frequency, pulse width) are dynamically adjusted based on real-time sensor data rather than remaining fixed. This dynamic adaptation enables the treatment to respond to fluctuating tinnitus symptoms and physiological conditions, achieving better relief completion rates
2Reliability
If electrical stimulation is applied to treat tinnitus, then symptom reduction can be achieved, but the treatment lacks personalization and adaptability
Solution Approach 1:
Multiple sensors monitor various physiological parameters simultaneously, providing comprehensive feedback about the patient's state. This enables highly personalized treatment parameters to be established and adjusted over time based on individual physiological responses, achieving both symptom reduction and personalization
Solution Approach 2:
The system changes multiple electrical stimulation parameters (voltage, frequency, pulse duration, electrode configuration) based on sensor feedback and machine learning analysis. These parameter changes are personalized to each patient's physiological characteristics and response patterns, providing adaptable treatment
3Ease of operation
If fixed electrical stimulation parameters are used, then treatment can be applied, but it cannot dynamically respond to changing physiological conditions
Solution Approach 1:
The system automatically adjusts stimulation parameters based on sensor input without requiring manual intervention from a clinician. The embedded processing and control circuits enable the device to self-regulate in real-time, maintaining ease of operation while achieving dynamic adaptability to changing conditions
Data Source
AI summary
An exemplary system includes an implantable stimulator configured to be implanted within a recipient and apply electrical stimulation configured to treat tinnitus within the recipient. The system further includes an implantable sensor configured to be implanted within the recipient and output first sensor data representative of a first property associated with the recipient. The system further includes an external sensor configured to be external to the recipient and output second sensor data representative of a second property associated with the recipient. The system further includes a controller communicatively coupled to the implant, the implantable sensor, and the external sensor. The controller is configured to receive the first and second sensor data, and control, based on the first and second sensor data, the electrical stimulation.