Brain Interface Autocalibration for Neural Response Stability
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Solution Overview
Problem
Existing computer brain interface (CBI) devices face challenges in maintaining consistent and long-term stability of artificial sensory perceptions due to positional sensitivity of neurostimulation electrodes, which can lead to changes in neural responses during movement or tissue alterations.
Innovation Solution
A closed-loop, on-line autocalibration method that observes the excitation behavior of afferent sensory nerve fibers to recalibrate neurostimulation signal parameters, ensuring consistent artificial sensory perceptions by using bioelectric responses as fingerprints for calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If neurostimulation electrodes are initially calibrated to elicit a certain neural response, then the desired neural response is achieved at the calibration moment, but the neural response becomes inconsistent when electrodes move relative to the stimulation target during movement or tissue alteration
Solution Approach 1:
The system continuously monitors the actual neural response evoked by neurostimulation signals and uses this feedback to dynamically adjust stimulation parameters. The processor compares the measured neural response against the desired response and automatically recalibrates the stimulation parameters to maintain consistent artificial sensory perceptions despite electrode movement or tissue changes.
Solution Approach 2:
The calibration parameters are made dynamic rather than static. The system performs initial calibration to establish baseline parameters, then continuously adapts these parameters in real-time based on monitored neural responses. This dynamic adjustment allows the system to compensate for electrode migration, tissue relaxation, or movement-induced changes in the electrode-tissue interface.
2Reliability
If neurostimulation parameters are manually recalibrated by trained medical personnel, then the neural response consistency can be restored, but the process requires intervention by trained medical personnel and cannot be performed on-line
Solution Approach 1:
The system performs self-calibration automatically without requiring external intervention by medical personnel. The processor autonomously monitors neural responses, detects deviations from desired responses, and adjusts stimulation parameters to restore consistency. This self-service capability enables on-line recalibration during normal device operation, eliminating the need for periodic manual recalibration sessions.
Solution Approach 2:
The system automatically modifies stimulation parameters (such as amplitude, pulse width, frequency, or electrode selection) based on real-time neural response monitoring. When a deviation in neural response is detected, the processor systematically adjusts one or more parameters to restore the desired neural response, thereby maintaining consistent artificial sensory perceptions without human intervention.
3Device complexity
If the same neurostimulation signal is used after electrode movement, then the signal structure remains unchanged, but the evoked neural response changes due to altered electrode-nerve fiber distance
Solution Approach 1:
The system dynamically adjusts neurostimulation signal parameters (such as amplitude, pulse width, frequency, or wavelet characteristics) based on monitored neural responses. When electrode movement alters the electrode-nerve fiber distance, the processor automatically modifies one or more signal parameters to compensate for the changed tissue interface conditions and restore the desired neural response magnitude and quality.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method enables continuous optimal information transmission to the brain, maintaining the intensity, quality, and locus of artificial sensory perceptions despite changes in electrode position or neural responsivity, thereby ensuring long-term stability and consistency of sensory communication.
Implementation Method 1
applying a stimulus from the array which evokes a neural compound action potential response in the neural tissue proximal to the array using the first plurality of electrodes
Implementation Method 2
sensing, via the neurostimulation interface, one or more bioelectric responses of the one or more stimulated afferent sensory nerve fibers
Data Source
AI summary
A computer brain interface (CBI) device of an individual is self-calibrated. A neurostimulation test signal is generated based on a selected set of test signal parameters. The neurostimulation signal is applied to the afferent sensory nerve fibers to elicit a bioelectric response via a neurostimulation interface operably connected to or integrated with the CBI device. The neurostimulation interface senses the bioelectric responses of the stimulated afferent sensory nerve fibers. The CBI devices determines, based on the sensed bioelectric responses, whether an excitation behavior of the stimulated afferent sensory nerve fibers with respect to the neurostimulation interface has changed. When the excitation behavior has changed, a set of recalibrated neurostimulation signal parameters is determined based on the sensed bioelectric responses. The CBI device is operated using the recalibrated neurostimulation signal parameters to communicate information to the individual via neurostimulation of the afferent sensory nerve fibers.