Medial Olivocochlear Reflex Sound Coding with Bandwidth Normalization

Abstract

A signal processing arrangement is described for signal processing in a bilateral hearing implant system. A channel compression module develops a inhibition-adjusted band pass signal for each band pass signal using a channel-specific dynamic inhibition adjustment based on a channel-normalized medial olivocochlear reflex model that reflects bandwidth energy for a corresponding contralateral band pass signal and bandwidth energy for a selected reference contralateral band pass signal.

Claims

1. A signal processing system for signal processing in a bilateral hearing implant system having left side and right side hearing implants, the system for each hearing implant comprising: at least one sensing microphone configured for sensing a sound environment to develop a corresponding microphone signal output; a filter bank configured for processing the microphone signal to generate a plurality of band pass signals, wherein each band pass signal represents an associated band of audio frequencies; a channel compression module configured to develop an inhibition-adjusted band pass signal for each band pass signal using a channel-specific dynamic inhibition adjustment based on a channel-normalized medial olivocochlear reflex model reflecting bandwidth energy for a corresponding contralateral band pass signal and bandwidth energy for a selected reference contralateral band pass signal; a pulse timing and coding module configured for processing the inhibition-adjusted band pass signals to develop stimulation timing signals; and a pulse generation module configured for processing the stimulation timing signals to develop electrode stimulation signals for the hearing implant for perception as sound.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0022] FIG. 1 shows a section view of a human ear with a typical cochlear implant system designed to deliver electrical stimulation to the inner ear.

[0023] FIG. 2 shows various functional blocks in a continuous interleaved sampling (CIS) processing system.

[0024] FIG. 3 shows an example of a short time period of an audio speech signal from a microphone.

[0025] FIG. 4 shows an acoustic microphone signal decomposed by band-pass filtering by a bank of filters into a set of signals.

[0026] FIG. 5 shows various functional blocks in a system for signal processing according to an embodiment of the present invention.

[0027] FIG. 6 shows various logical blocks in a method for signal processing according to an embodiment of the present invention.

DETAILED DESCRIPTION OF SPECIFIC EMBODIMENTS

[0028] Previous signal processing arrangements that used a medial olivocochlear reflex (MOCR) model, were based on a inhibition parameter c for each band pass channel that depended on output energy E from the corresponding contralateral band pass channel. For broadband signals, the resulting contralateral inhibition could have been greater for higher frequency channels than for lower frequency channels because high-frequency channels were broader in frequency and may have contained more energy than lower frequency channels. Embodiments of the present invention address that problem for binaural CI sound coding using a channel-specific dynamic inhibition adjustment based on a channel-normalized MOCR model that reflects bandwidth energy for a corresponding contralateral band pass signal and bandwidth energy for a selected reference contralateral band pass signal.

[0029] FIG. 5 shows various functional blocks in a system, and FIG. 6 shows various logical blocks in a method, for signal processing according to embodiments of the present invention for a bilateral hearing implant system having a left side hearing implant 500 and a right side hearing implant 501. The system shown in FIG. 5 is based on the system discussed above with respect to FIG. 2 for CIS-based sound coding. So on each side there initially is at least one sensing microphone configured for sensing a sound environment to develop a corresponding microphone signal output, step 601, that is processed by a Filter Bank 201, step 602, to generate multiple band pass signals B.sub.1 to B.sub.M (which can also be thought of as frequency channels), each representing an associated band of audio frequencies. For example, the Filter Bank 201 might specifically include a high-pass pre-emphasis filter such as a first-order Butterworth filter with a 3-dB cutoff frequency of 1.2 kHz, followed by a bank of 12 sixth-order Butterworth band-pass filters with 3-dB cutoff frequencies that follow a modified logarithmic distribution between 100 and 8500 Hz.

[0030] A Signal Processor-Channel Compression Module 502 then processes the band pass signals B.sub.1 to B.sub.M as described above with respect to FIG. 2 (e.g., performing envelope extraction via full-wave rectification and low-pass filtering using a fourth-order Butterworth low-pass filter with a 3-dB cutoff frequency of 400 Hz) and additionally performing a channel-specific dynamic logarithmic inhibition adjustment, step 603, as discussed more fully below that is based on a channel-normalized medial olivocochlear reflex model to produce adjusted band pass signals S.sub.1 to S.sub.N.

[0031] Pulse Timing and Coding Module 203 then applies pulse coding (e.g., using a continuous interleaved sampling (CIS) coding strategy) and a non-linear mapping function as described above, step 604, to the adjusted band pass signals S.sub.1 to S.sub.N to produce a set of electrode stimulation signals A.sub.1 to A.sub.M that the Pulse Generation Module 204 develops into the output electrode pulses E.sub.1 to E.sub.M, step 605, for the electrode contacts in the implanted electrode array.

[0032] MOC Module 503 applies the channel-normalized medial olivocochlear reflex model to the band pass signals B.sub.1 to B.sub.M from each Filter Bank 201 for the Signal Processor-Channel Compression Module 502 to perform the channel-specific dynamic inhibition adjustment in step 603, which may specifically be configured to produce larger channel-specific dynamic inhibition adjustments for lower frequency band pass signals. For example, this may be based on a channel-specific dynamic inhibition adjustment

[00002]$\mathrm{function}y=\frac{\ln \left(1+c.Math.x\right)}{\ln \left(1+c\right)},$

where x represents amplitude of the input band pass signal, y represents amplitude of the adjusted band pass signal, and c is a dynamically determined inhibition factor that determines amount of the inhibition adjustment. For further details, refer to the discussion in Boyd P J, Effects of programming threshold and maplaw settings on acoustic thresholds and speech discrimination with the MED-EL COMBI 40+ cochlear implant. Ear Hear. 27, 608-618, 2006; which is incorporated herein by reference in its entirety. In another example the channel-specific dynamic inhibition adjustment function y=αx.sup.p+k, where x represents amplitude of the input band pass signal, y represents amplitude of the adjusted band pass signal, k a constant, and p is a dynamically determined inhibition factor that determines amount of the inhibition adjustment. It is however understood, that the invention is not limited to these two dynamic inhibition adjustment functions, but other suitable functions may be used. More formally, inhibition factor c (or p) is controlled using the output energy E, normalized to the channel bandwidth E′:

[00003]$E^{\prime }=E.Math.{\left(\frac{B{W}_{ref}}{BW}\right)}^{0.5}$

where BW is the channel bandwidth, and BW.sub.ref is a reference channel bandwidth.

[0033] In a typical embodiment, x and y may range within an interval [0, 1]. The dynamically determined inhibition factor c and the bandwidth energy for the corresponding contralateral band pass signal may be inversely related such that the greater the bandwidth energy for the corresponding contralateral band pass signal, the smaller the value of the dynamically determined inhibition factor c. For example, the relationship between the instantaneous value of c and the instantaneous contralateral output energy may be such that the greater the output energy, the smaller the value of c. In one example the relationship may be given by

[00004]$c\left(t\right)=\frac{c_a-c_b}{1+\exp \left[-\alpha \left(E^{\prime }\left(t\right)-\beta \right)\right]}+c_b$

where c.sub.a, c.sub.b and β are constants and E′ is the normalized instantaneous output energy E for a given time t, as described in Patent Cooperation Treaty Publication WO2015/169649 more detailed, incorporated herein by reference. In another example, the relationship may be given by

[00005]${\log }_{10}\left(c\left(t\right)\right)=\frac{{\log }_{10}\left(c_a\right)-{\log }_{10}\left(c_b\right)}{1+\exp \left[-\alpha \left({\log }_{10}\left(E^{\prime }\left(t\right)\right)-{\log }_{10}\left(\beta \right)\right)\right]}+{\log }_{10}\left(c_b\right)$

where c.sub.a, c.sub.b and β are constants and E′ is the normalized instantaneous output energy E for a given time t. It is however understood, that the invention is not limited to these two functions, but other suitable functions may be used.
Specifically, c might vary between approximately 30 and 1000 for contralateral output energies of 0 and −20 dB full scale (FS; where 0 dB FS corresponds to peak amplitude at unity), respectively.

[0034] Based on the exponential time-course of activation and deactivation of the MOC effect (see, e.g., Backus and Guinan, Time-course of the human medial olivocochlear reflex, J. Acoust. Soc. Am. 119, 2889-2904, 2006; which is incorporated herein by reference in its entirety), the bandwidth energy for the corresponding contralateral band pass signal may be based on root mean square output amplitude integrated over a preceding exponentially decaying time window with two time constants, τ.sub.a and τ.sub.b. For example, to reflect the time course of activation and deactivation of the natural MOCR, time constants might be set to τ.sub.a=2 ms and τ.sub.b=300 ms.

[0035] For example, in an embodiment where channels #1 and #12 are respectively the lowest and highest in frequency, overall inhibition will be greatest when BW.sub.ref equals the bandwidth of channel #12 (BW.sub.#12), and gradually decreases for lower number channels. Bandwidth normalizations that produce greater inhibition can compromise audibility and reduce intelligibility. In addition, for normal hearing listeners, it has been observed that a contralateral broadband noise at 60 dB SPL increases auditory thresholds by about 1 to 9 dB. The inventor has observed, that normalization with BW.sub.ref=BW.sub.#6, BW.sub.#7, or BW.sub.#8 produces more reasonable overall inhibition, with effectively equal or greater inhibition in the lower than in the higher frequency channels without compromising audibility significantly.

[0036] Embodiments of the invention may be implemented in part in any conventional computer programming language. For example, preferred embodiments may be implemented in a procedural programming language (e.g., “C”) or an object oriented programming language (e.g., “C++”, Python). Alternative embodiments of the invention may be implemented as pre-programmed hardware elements, other related components, or as a combination of hardware and software components.

[0037] Embodiments can be implemented in part as a computer program product for use with a computer system. Such implementation may include a series of computer instructions fixed either on a tangible medium, such as a computer readable medium (e.g., a diskette, CD-ROM, ROM, or fixed disk) or transmittable to a computer system, via a modem or other interface device, such as a communications adapter connected to a network over a medium. The medium may be either a tangible medium (e.g., optical or analog communications lines) or a medium implemented with wireless techniques (e.g., microwave, infrared or other transmission techniques). The series of computer instructions embodies all or part of the functionality previously described herein with respect to the system. Those skilled in the art should appreciate that such computer instructions can be written in a number of programming languages for use with many computer architectures or operating systems. Furthermore, such instructions may be stored in any memory device, such as semiconductor, magnetic, optical or other memory devices, and may be transmitted using any communications technology, such as optical, infrared, microwave, or other transmission technologies. It is expected that such a computer program product may be distributed as a removable medium with accompanying printed or electronic documentation (e.g., shrink wrapped software), preloaded with a computer system (e.g., on system ROM or fixed disk), or distributed from a server or electronic bulletin board over the network (e.g., the Internet or World Wide Web). Of course, some embodiments of the invention may be implemented as a combination of both software (e.g., a computer program product) and hardware. Still other embodiments of the invention are implemented as entirely hardware, or entirely software (e.g., a computer program product).

[0038] Although various exemplary embodiments of the invention have been disclosed, it should be apparent to those skilled in the art that various changes and modifications can be made which will achieve some of the advantages of the invention without departing from the true scope of the invention.