Cochlear Implant Parameter Reduction via Dimensionality Analysis

The patent segments the configuration process into two distinct phases: (1) an automated initial fitting phase that quickly establishes a baseline configuration using a reduced parameter set, and (2) a subsequent fine-tuning phase that adjusts specific parameters based on recipient feedback. This segmentation allows the system to achieve precise sound perception control while significantly reducing the overall configuration time by handling the bulk of parameter optimization automatically.

The patent transforms the configuration approach by changing from manually adjusting all individual parameters to using an automated algorithm that derives optimal parameter values through mathematical optimization. The system changes the state of multiple parameters simultaneously based on objective measurements and recipient responses, rather than requiring sequential manual adjustment of each parameter, thereby reducing configuration time while maintaining precision.

The patent implements a feedback-driven configuration system where the algorithm iteratively adjusts parameters based on objective measurements (such as speech reception thresholds) and subjective recipient feedback. This feedback loop allows the system to efficiently navigate the large parameter space by eliminating suboptimal combinations early and focusing adjustments on the most impactful parameters, thereby maintaining high adaptability while reducing the effective complexity of the configuration process.

The patent applies preliminary action by having the automated algorithm perform initial parameter optimization before recipient fine-tuning. The system pre-calculates optimal parameter values based on objective test results, establishing a well-founded starting point that reduces the subsequent adjustment burden. This preliminary configuration handles the complex parameter interactions in advance, leaving only minor adaptations needed for individual recipient preferences.

The patent employs a dynamic configuration approach where the algorithm adaptively determines which parameters to adjust at each step based on current system state and optimization progress. Rather than simultaneously adjusting all parameters, the system dynamically selects and adjusts only the most impactful parameters at each iteration, making the optimization process manageable and interpretable while still achieving comprehensive system optimization over time.

The patent applies partial action by having the automated algorithm focus on optimizing only the most critical parameters that have the greatest impact on sound perception, rather than attempting to simultaneously optimize all parameters. This selective approach allows the system to achieve reliable optimization of the key performance drivers while avoiding the complexity of analyzing every parameter's individual impact, with less critical parameters being adjusted subsequently based on recipient feedback.