Publication: Hearing-Aid Directionality Index (HADI): A Proposed Metric to Measure Heading-Aid Off-Axis Noise Rejection Performance
| datacite.rights | restricted | |
| dc.contributor.advisor | Choueiri, Edgar Yazid | |
| dc.contributor.author | Wallar, John W. | |
| dc.date.accessioned | 2025-08-12T13:56:13Z | |
| dc.date.available | 2025-08-12T13:56:13Z | |
| dc.date.issued | 2025-04-14 | |
| dc.description.abstract | This thesis introduces the Hearing-Aid Directionality Index (HADI), a novel two-factor metric designed to quantify and compare the off-axis noise rejection performance of hearing aids and directional digital signal processing (DSP) algorithms. The metric consists of HADI_A, which measures the relative energy difference between the active and peripheral listening zones, and HADI_B, which evaluates the consistency of energy distribution within each zone. Using a combination of high-order ambisonics microphone polar pattern emulation and physical head simulator testing, HADI scores were calculated for both simulated microphone polar patterns and a commercial hearing-aid device, the Apple AirPods Pro, specifically with respect to its FDA approved hearing-aid mode. Results reveal that high-order DSP filters, particularly the 4th order MaxRe, achieve superior directional performance, while the commercial device shows minimal spatial shaping. HADI provides a standardized, interpretable framework for comparing directional performance in hearing aids, enabling engineers and users to make informed decisions based on real spatial data. By supplementing manufacturer specifications with independently verified testing, it establishes a foundation for a more comprehensive and meaningful evaluation protocol. | |
| dc.identifier.uri | https://theses-dissertations.princeton.edu/handle/88435/dsp011j92gb95r | |
| dc.language.iso | en_US | |
| dc.title | Hearing-Aid Directionality Index (HADI): A Proposed Metric to Measure Heading-Aid Off-Axis Noise Rejection Performance | |
| dc.type | Princeton University Senior Theses | |
| dspace.entity.type | Publication | |
| dspace.workflow.startDateTime | 2025-04-15T02:52:01.475Z | |
| pu.contributor.authorid | 920246123 | |
| pu.date.classyear | 2025 | |
| pu.department | Electrical and Computer Engineering |
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