One of the most important jobs of any hearing aid is to control the amplification process by attenuating the right sounds at the right frequencies, times, and arrival directions for the individual. Modern hearing aids use machine learning and sophisticated noise reduction technology to try and identify what is meaningful to the wearer and what the average person’s ear and brain need to process to communicate effectively in adverse listening conditions. The challenge, of course, is that machines don’t know the intent, expectations, or even the wearer's mood. Yet hearing aid companies are obligated to provide evidence supporting the effectiveness of their new features.
Aspire Member
Aspire Member
One of the most important jobs of any hearing aid is to control the amplification process by attenuating the right sounds at the right frequencies, times, and arrival directions for the individual. Modern hearing aids use machine learning and sophisticated noise reduction technology to try and identify what is meaningful to the wearer and what the average person’s ear and brain need to process to communicate effectively in adverse listening conditions. The challenge, of course, is that machines don’t know the intent, expectations, or even the wearer's mood. Yet hearing aid companies are obligated to provide evidence supporting the effectiveness of their new features. This course will address how Signia creates this clinical evidence to support their innovative technology and how those claims can be applied in your clinic.
