Biomimetic Microphone Array for Single-Implant Sound Localization

The patent extracts the binaural processing function from bilateral implants and consolidates it into a single implant with enhanced audio receivers. By taking out the sound localization capability from the bilateral configuration and implementing it through multiple audio receivers sampling sound cyclically, the system achieves accurate sound localization with a single implant, resolving the contradiction between hearing coverage and localization accuracy.

The single hearing implant is segmented into multiple audio receivers that are spatially distributed and configured to sample sound from different orientations. This segmentation allows the implant to capture binaural-like information from a single device, enabling accurate sound localization while maintaining hearing coverage through the distributed receiver architecture.

The audio receivers operate in a cyclic sampling pattern where each receiver is activated in sequence to sample sound from different spatial orientations. This periodic action allows multiple receivers to function as a coordinated system for spatial audio capture, achieving sound localization accuracy while managing complexity through time-division multiplexing of the receivers.

Each audio receiver in the array is designed to perform multiple functions: capturing sound from its specific orientation, contributing to the spectral transformation, and providing data for source localization. This multi-functionality reduces the need for separate dedicated components for each function, thereby managing device complexity while maintaining high sound localization accuracy.

The system performs spectral transformation and identifies dominant spectral components in advance during the cyclic sampling process. By preparing the spectral data and identifying key frequency components before the final speech perception task, the system reduces real-time processing requirements and improves speech perception accuracy in noisy environments through pre-computed spectral information.

The processing algorithm extracts and focuses on only the dominant spectral components rather than processing the entire frequency spectrum. By taking out and concentrating on the most relevant frequency information, the system reduces computational complexity and processing time while maintaining high speech perception accuracy in noise through selective spectral analysis.