In Brief:
Adaptive anti-feedback algorithms are now common features in digital hearing aids, but there have been few attempts to quantify the benefits and compare different algorithms. In this study, performance metrics were developed to quantify several aspects of anti-feedback algorithm performance: (1) additional gain made available before oscillation, (2) gain lost in specific frequency regions, (3) reduction of suboscillatory peaks in the frequency response, (4) speed of adaptation to changing acoustic conditions, and (5) robustness in the presence of tonal input signals. The metrics were used to evaluate nine algorithms, revealing a wide range of performance. Patterns in the results suggest that different algorithm classes have different strengths and weaknesses.
