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Programmable audiogram matching using a frequency …
https://ieeexplore.ieee.org/document/226079/
A frequency sampling filter which has been implemented on a master digital hearing aid comprising a Texas TMS 320C30 DSP and associated circuitry is presented. The filter runs in real time and is used to provide a response, determined from the human audiogram, which compensates for loss of gain. The algorithm matches given requirements using a filter …
Optimization of frequency sampling filter through ...
https://ieeexplore.ieee.org/document/647540
An recursive frequency sampling filter, based on the frequency response characteristic of realistic audiograms, is discussed. An optimization technique is used to minimize the maximum deviation of the filter from the audiogram over frequency transition bands. Finally experimental results are presented.
Audiogram matching in hearing aid using approximate ...
https://link.springer.com/article/10.1007/s11045-021-00782-z
Frequency response masking approach is used for the development of a 10-band non-uniform approximate FIR filter bank with a minimum stop band attenuation of greater than 50 dB. Audiogram matching is done with audiograms of different types of moderate hearing loss and the matching error is computed.
FIR filter bank design for Audiogram Matching
https://www.irjet.net/archives/V3/i12/IRJET-V3I1276.pdf
the filters to match the audiogram of the specific user with individual hearing loss (Kuo et. al., 2008). hence the basic requirement of any hearing aid is to provide correct adjustment of the gain versus frequency, which is also called audiogram matching/fitting.
Filtering to Match Hearing Aid Insertion Gain to ...
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4111436/
One issue with trying to match an FIR filter to targets based on the audiogram is that the audiogram is viewed on a logarithmic frequency scale (and real-ear measurement results are commonly viewed with a log frequency axis), so there is more resolution at low frequency.
Study and Analysis of Audiogram Matching for ...
https://www.ripublication.com/ijaer20/ijaerv15n8_15.pdf
patient hearing loss characteristics. These filter designs use filter banks with fixed sub-bands. Current research focus is on to reduce the algorithm complexity. In this paper, we are focusing our study of Audiogram matching for different types of hearing loss use by using single reconfigurable transfer
Efficient hearing aid algorithm using DCT with uniformly ...
http://ijeecs.iaescore.com/index.php/IJEECS/article/download/25376/15173
3.1. Audiogram re-sampling Graph in Figure 3 (a) represents the audiogram values for the hearing loss case with mild hearing loss at mid frequency. Graph in Figure 3 (b) is the uniformly re-samples audiogram values at 100 Hz that mean sampling interval in frequency domain is 100 Hz. From the audiogram in Figure 4 (a), it is observed
18 band ANSI S1.11 filter bank based on interpolated ...
https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/joe.2019.1009
using Kaiser window based parallel FIR filters. In uniform FB, a large number of bands are required to get sufficient frequency resolution to match the audiograms at lower frequencies compared to non-uniform architectures. Research interest shifted to non-uniform architectures for hearing aid application in recent years.
Efficient variable bandwidth filters for digital hearing ...
https://www.sciencedirect.com/science/article/pii/S2090123215000594
The variable bandwidth filter is shifted and provided gain to match an audiogram of mild hearing loss at all frequencies. This forms an approximation model of the audiogram and can be altered during simulation until a minimum matching error is obtained. Matching error is the overall error between the filter output and the audiogram [7].
Study of digital hearing aid using frequency shaping function
https://www.ijert.org/research/study-of-digital-hearing-aid-using-frequency-shaping-function-IJERTV2IS50123.pdf
channels at a 32 KHz sampling rate for each channel and driving a stereo headphone output. It provided for frequency shaping using multichannel FIR filters, noise suppression, multiband amplitude compression, and frequency dependent intraoral time delay algorithms. In [11], a 3-channel VFB approach has been
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