Distortion reduction in noise cancellation systems

Abstract

Presented herein are techniques for reducing distortions in noise cancellation systems, including but not limited to body noise cancellation filtering systems. In one aspect, a method is provided. The method comprises: receiving at least one input signal at a noise cancellation system; and processing the at least one input signal using the noise cancellation system to generate a noise cancellation output signal, wherein the noise cancellation system is controlled by a variable filtering strength parameter that is a function of a level of the at least one input signal.

Description

DISTORTION REDUCTION IN NOISE CANCELLATION SYSTEMSBACKGROUNDField of the Invention[oooi] The present invention relates generally to techniques for reducing distortions in noise cancellation systems.Related Art

[0002] Medical devices have provided a wide range of therapeutic benefits to recipients over recent decades. Medical devices can include internal or implantable components / devices, external or wearable components / devices, or combinations thereof (e.g., a device having an external component communicating with an implantable component). Medical devices, such as traditional hearing aids, partially or fully-implantable hearing prostheses (e.g., bone conduction devices, mechanical stimulators, cochlear implants, etc.), pacemakers, defibrillators, functional electrical stimulation devices, and other medical devices, have been successful in performing lifesaving and / or lifestyle enhancement functions and / or recipient monitoring for a number of years.

[0003] The types of medical devices and the ranges of functions performed thereby have increased over the years. For example, many medical devices, sometimes referred to as “implantable medical devices,” now often include one or more instruments, apparatus, sensors, processors, controllers or other functional mechanical or electrical components that are permanently or temporarily implanted in a recipient. These functional devices are typically used to diagnose, prevent, monitor, treat, or manage a disease / injury or symptom thereof, or to investigate, replace or modify the anatomy or a physiological process. Many of these functional devices utilize power and / or data received from external devices that are part of, or operate in conjunction with, implantable components.SUMMARY

[0004] In one aspect, a method is provided. The method comprises: receiving at least one input signal at a noise cancellation system; and processing the at least one input signal using the noise cancellation system to generate a noise cancellation output signal, wherein the noise cancellation system is controlled by a variable filtering strength parameter that is a function of a level of the at least one input signal.

[0005] In another aspect, an apparatus is provided. The apparatus comprises: a noise cancellation filter configured to receive at least one input signal, and to process the at least one input signal to generate a noise cancellation output signal; and a controller configured to: determine, based on the at least one input signal, whether the noise cancellation filter is expected to add distortions to the at least one input signal when generating the noise cancellation output signal; and selectively control the noise cancellation filter in response to determining that the noise cancellation filter is expected to add distortions.

[0006] In another aspect, a method is provided. The method comprises: receiving at least one input signal; processing the at least one input signal with a noise cancellation system configured to apply noise cancellation filtering to the at least one input signal to generate a noise cancellation output signal; and processing the at least one input signal with a noise reduction system, wherein the noise reduction system is configured to apply noise reduction gains to the at least one input signal to generate a noise reduction output signal.

[0007] In another aspect, a method is provided. The method comprises: receiving at least one input signal; processing the at least one input signal with a noise cancellation system configured to apply noise cancellation filtering to the at least one input signal to generate a noise cancellation output signal; and processing the noise cancellation output signal with a noise reduction system, wherein the noise reduction system is configured to apply noise reduction gains to the noise cancellation output signal to generate a noise reduction output signal.

[0008] In another aspect, a system is provided. The system comprises: a noise cancellation system configured to: receive at least one input signal; and process the at least one input signal by using a noise cancellation filter to generate a noise cancellation output signal; and a noise reduction system configured to: receive the at least one input signal and the noise cancellation output signal; and selectively process one of the at least one input signal or the noise cancellation output signal by applying noise reduction gains to one of the at least one input signal or the noise cancellation output signal to generate a noise reduction output signal.BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Embodiments of the present invention are described herein in conjunction with the accompanying drawings, in which:

[0010] FIG. 1A is a schematic diagram illustrating a cochlear implant system with which aspects of the techniques presented herein can be implemented;[ooii] FIG. IB is a side view of a recipient wearing a sound processing unit of the cochlear implant system of FIG. 1A;

[0012] FIG. 1C is a schematic view of components of the cochlear implant system of FIG. 1 A;

[0013] FIG. ID is a block diagram of the cochlear implant system of FIG. 1A;

[0014] FIG. IE is a schematic diagram illustrating a computing device with which aspects of the techniques presented herein can be implemented;

[0015] FIG. 2A is a block diagram illustrating a noise cancellation system at a high level;

[0016] FIG. 2B is a schematic diagram illustrating an implantable device system, which can be a cochlear implant system of FIG. ID, operating with an adaptive body noise reduction system;

[0017] FIG. 3A is a block diagram illustrating an adaptive noise cancellation system, according to a first example embodiment of the techniques presented herein;

[0018] FIG. 3B is an example illustration of a variable noise cancellation filtering strength parameter with respect to an input level of an unfiltered input signal, according to the first example embodiment of the techniques presented herein;

[0019] FIG. 4A is a flowchart of a method according to a first example embodiment;

[0020] FIG. 4B is a flowchart of another method according to the first example embodiment;

[0021] FIG. 5 is a block diagram illustrating a noise reduction system according to a second example embodiment of the techniques presented herein;

[0022] FIG. 6 is a flowchart of a method according to a second example embodiment;

[0023] FIG. 7 is a block diagram illustrating a noise reduction system according to a third example embodiment of the techniques presented herein;

[0024] FIG. 8 is a flowchart of a method according to a third example embodiment;

[0025] FIG. 9 is a flowchart of another method according to another example embodiment; and

[0026] FIG. 10 is a schematic diagram illustrating a vestibular stimulator system with which aspects of the techniques presented herein can be implemented.DETAILED DESCRIPTION

[0027] Hearing devices make widespread use of fixed filtering and adaptive filtering techniques to suppress unwanted interference (usually environmental noise, feedback, echo, etc.) from the target signal of interest (usually speech). Example filtering techniques include body noise cancellation (BNC) in totally implantable cochlear implants, acoustic feedback cancellation (AFC) in acoustic implants and hearing aids, acoustic echo cancellation (AEC) in telephony, and beamforming in cochlear implant sound processors and hearing aids. The adaptive filter is adapted (usually continuously) to estimate the time-varying environmental noise (or feedback) signal present in the microphone signal. The output estimate of the adaptive filter is then subtracted from the “noisy” input microphone signal to produce a “clean” output signal with the linear portion of the environmental noise (or feedback) largely removed.

[0028] However, if the estimate of the environmental noise (or feedback) reference signal is not accurate, the subtraction will inevitably result in distortions in the clean output signal. More generally, if the environment noise (or feedback) estimate is not linearly correlated with the noisy microphone input signal (from which it is subtracted), the subtraction can add noise rather than remove it. For example, inaccurate estimation can occur due to imperfections in the acoustic environment (e.g., room reverberation, microphone mismatch, leakage of the speech signal into the noise reference, etc.), in the signals (e.g., saturation, nonlinearities, or other artefacts present in the noise reference), or more simply, when the environmental noise (or feedback) is not present anymore such as during periods of silence.

[0029] These distortions are often relatively soft compared to the target sound and can be mitigated by noise reduction or expansion processing schemes. In specific instances, however, the distortions introduced by the filtering can become audible and thus undesirable. One specific example of such distortion is the audible “hiss” sound that is produced when switching on a noise cancellation mode in headphones while in a silent environment, with this hiss sound being most noticeable when the user is in a silent environment. When the noise cancellationmode is switched on, the system noise floor is amplified (instead of reduced) due to presence of the distortions added by the noise cancelling filter.

[0030] To address the above and other needs, presented herein are several techniques for minimizing distortions in noise cancellation systems, including but not limited to body noise cancellation filtering systems. Conventional systems and techniques to date have not focused on avoiding noise cancellation distortions (i.e., distortions introduced by the adaptive filter / body-noise canceller). In hearing aids, in particular, these distortions are typically small and attenuated by expansion and / or other generic single-channel noise reduction algorithms. By contrast, the systems and methods described herein aim to avoid introducing such noisecancellation distortions associated with conventional adaptive filtering techniques altogether, which is especially important for implantable microphones. In other words, the techniques presented herein avoid the addition of distortions associated with conventional adaptive filtering techniques and can, in certain examples, provide decreased power consumption.

[0031] There are a number of different types of devices in / with which embodiments of the present invention can be implemented. Merely for ease of description, the techniques presented herein are primarily described with reference to a specific device in the form of a cochlear implant system. However, it is to be appreciated that the techniques presented herein can also be partially or fully implemented by any of a number of different types of devices, including hearing devices, implantable medical devices, consumer electronic devices (e.g., mobile phones), wearable devices (e.g., smart watches), etc. As used herein, the term “hearing device” is to be broadly construed as any device that delivers sound signals to a user in any form, including in the form of acoustical stimulation, mechanical stimulation, electrical stimulation, etc. As such, a hearing device can be a device for use by a hearing -impaired person (e.g., hearing aids, middle ear auditory prostheses, bone conduction devices, direct acoustic stimulators, electro-acoustic hearing prostheses, auditory brainstem stimulators, bimodal hearing prostheses, bilateral hearing prostheses, dedicated tinnitus therapy devices, tinnitus therapy device systems, combinations or variations thereof, etc.) or a device for use by a person with normal hearing (e.g., consumer devices that provide audio streaming, consumer headphones, earphones and other listening devices). In other examples, the techniques presented herein can be implemented by, or used in conjunction with, various implantable medical devices, such as vestibular devices (e.g., vestibular implants), visual devices (i.e., bionic eyes), sensors, pacemakers, drug delivery systems, defibrillators, functional electricalstimulation devices, catheters, seizure devices (e.g., devices for monitoring and / or treating epileptic events), sleep apnea devices, electroporation devices, etc.

[0032] FIGs. 1A-1D illustrates an example cochlear implant system 102 with which aspects of the techniques presented herein can be implemented. The cochlear implant system 102 comprises an external component 104 that is configured to be directly or indirectly attached to the body of the user, and an intemal / implantable component 112 that is configured to be implanted in or worn on the head of the user. In the examples of FIGs. 1A-1D, the implantable component 112 is sometimes referred to as a “cochlear implant.” FIG. 1A illustrates the cochlear implant 112 implanted in the head 154 of a user, while FIG. IB is a schematic drawing of the external component 104 worn on the head 154 of the user. FIG. 1C is another schematic view of the cochlear implant system 102, while FIG. ID illustrates further details of the cochlear implant system 102. For ease of description, FIGs. 1A-1D will generally be described together.

[0033] In the examples of FIGs. 1A-1D, the external component 104 comprises a sound processing unit 106, an external coil 108, and generally, a magnet fixed relative to the external coil 108. The cochlear implant 112 includes an implantable coil 114, an implant body 134, and an elongate stimulating assembly 116 configured to be implanted in the user’s cochlea. In one example, the sound processing unit 106 is an off-the-ear (OTE) sound processing unit, sometimes referred to herein as an OTE component, that is configured to send data and power to the implantable component 112. In general, an OTE sound processing unit is a component having a generally cylindrically shaped housing 111 and which is configured to be magnetically coupled to the user’s head 154 (e.g., includes an integrated external magnet 150 configured to be magnetically coupled to an intemal / implantable magnet 152 in the implantable component 112). The OTE sound processing unit 106 also includes an integrated external (headpiece) coil 108 (the external coil 108) that is configured to be inductively coupled to the implantable coil 114.

[0034] It is to be appreciated that the OTE sound processing unit 106 is merely illustrative of the external devices that could operate with implantable component 112. For example, in alternative examples, the external component 104 can comprise a behind-the-ear (BTE) sound processing unit configured to be attached to, and worn adjacent to, the recipient’s ear. In general, a BTE sound processing unit comprises a housing that is shaped to be worn on the outer ear of the user and is connected to the separate external coil assembly via a cable, where the external coil assembly is configured to be magnetically and inductively coupled to theimplantable coil 114. It is also to be appreciated that alternative external components could be located in the user’s ear canal, worn on the body, etc.

[0035] Although the cochlear implant system 102 includes the sound processing unit 106 and the cochlear implant 112, as described below, the cochlear implant 112 can operate independently from the sound processing unit 106, for at least a period, to stimulate the user. For example, the cochlear implant 112 can operate in a first general mode, sometimes referred to as an “external hearing mode,” in which the sound processing unit 106 captures sound signals which are then used as the basis for delivering stimulation signals to the user. The cochlear implant 112 can also operate in a second general mode, sometimes referred as an “invisible hearing” mode, in which the sound processing unit 106 is unable to provide sound signals to the cochlear implant 112 (e.g., the sound processing unit 106 is not present, the sound processing unit 106 is powered-off, the sound processing unit 106 is malfunctioning, etc.). As such, in the invisible hearing mode, the cochlear implant 112 captures sound signals itself via implantable sound sensors and then uses those sound signals as the basis for delivering stimulation signals to the user. Further details regarding operation of the cochlear implant 112 in the external hearing mode are provided below, followed by details regarding operation of the cochlear implant 112 in the invisible hearing mode. It is to be appreciated that reference to the external hearing mode and the invisible hearing mode is merely illustrative and that the cochlear implant 112 could also operate in alternative modes.

[0036] In FIGs. 1A and 1C, the cochlear implant system 102 is shown with an external device 110, configured to implement aspects of the techniques presented. The external device 110, which is shown in greater detail in FIG. IE, is a computing device, such as a personal computer (e.g,, laptop, desktop, tablet), a mobile phone (e.g., smartphone), remote control unit, etc. The external device 110 and the cochlear implant system 102 (e.g., sound processing unit 106 or the cochlear implant 112) wirelessly communicate via a bi-directional communication link 126. The bi-directional communication link 126 can comprise, for example, a short-range communication, such as Bluetooth link, Bluetooth Low Energy (BLE) link, a proprietary link, etc.

[0037] Returning to the example of FIGs. 1A-1D, the sound processing unit 106 of the external component 104 also comprises one or more input devices configured to capture and / or receive input signals (e.g., sound or data signals) at the sound processing unit 106. The one or more input devices include, for example, one or more sound input devices 118 (e.g., one or more external microphones, audio input ports, telecoils, etc.), one or more auxiliary input devices119 (e.g., audio ports, such as a Direct Audio Input (DAI), data ports, such as a Universal Serial Bus (USB) port, cable port, etc.), and a short-range wireless transmitter / receiver (wireless transceiver) 120 (e.g., for communication with the external device 110), each located in, on or near the sound processing unit 106. However, it is to be appreciated that one or more input devices can include additional types of input devices and / or less input devices (e.g., the short- range wireless transceiver 120 and / or one or more auxiliary input devices 119 could be omitted).

[0038] The sound processing unit 106 also comprises a charging coil 121, a closely-coupled radio frequency transmitter / receiver (RF transceiver) 122, at least one rechargeable battery 123, and an external sound processing module 124. The external sound processing module 124 can be configured to perform a number of operations and can be formed by one or more processors (e.g., one or more Digital Signal Processors (DSPs), one or more uC cores, etc.), firmware, software, etc. arranged to perform operations described herein. That is, external sound processing module 124 can be implemented as firmware elements, partially or fully implemented with digital logic gates in one or more application-specific integrated circuits (ASICs), partially or fully in software, etc.

[0039] Returning to the example of FIGs. 1A-1D, the implantable component 112 comprises an implant body (main module) 134, a lead region 136, and the intra-cochlear stimulating assembly 116, all configured to be implanted under the skin (tissue) 115 of the user. The implant body 134 generally comprises a hermetically-sealed housing 138, in which RF interface circuitry 140, at least one power source 141 (e.g., one or more batteries, one or more capacitors, etc.), and a stimulator unit 142 are disposed. The implant body 134 also includes the intemal / implantable coil 114 that is generally external to the housing 138, but which is connected to the RF interface circuitry 140 via a hermetic feedthrough (not shown in FIG. ID).

[0040] As noted, stimulating assembly 116 is configured to be at least partially implanted in the user’s cochlea. Stimulating assembly 116 includes a plurality of longitudinally spaced intra-cochlear electrical stimulating contacts (electrodes) 144 that collectively form a contact array (electrode array) 146 for delivery of electrical stimulation (current) to the recipient’s cochlea. Stimulating assembly 116 extends through an opening in the recipient’s cochlea (e.g., cochleostomy, the round window, etc.) and has a proximal end connected to stimulator unit 142 via lead region 136 and a hermetic feedthrough (not shown in FIG. ID). Uead region 136 includes a plurality of conductors (wires) that electrically couple the electrodes 144 to thestimulator unit 142. The implantable component 112 also includes an electrode outside of the cochlea, sometimes referred to as the extra-cochlear electrode (ECE) 139.

[0041] As noted, the cochlear implant system 102 includes the external coil 108 and the implantable coil 114. The external magnet 150 is fixed relative to the external coil 108 and the intemal / implantable magnet 152 is fixed relative to the implantable coil 114. The external magnet 150 and the intemal / implantable magnet 152 fixed relative to the external coil 108 and the intemal / implantable coil 114, respectively, facilitate the operational alignment of the external coil 108 with the implantable coil 114. This operational alignment of the coils enables the external component 104 to transmit data and power to the implantable component 112 via a closely-coupled wireless link 148 formed between the external coil 108 with the implantable coil 114. In certain examples, the closely-coupled wireless link 148 is a radio frequency (RF) link. However, various other types of energy transfer, such as infrared (IR), electromagnetic, capacitive and inductive transfer, can be used to transfer the power and / or data from an external component to an implantable component and, as such, FIG. ID illustrates only one example arrangement.

[0042] As noted above, sound processing unit 106 includes the external sound processing module 124. The external sound processing module 124 is configured to process the received input audio signals (received at one or more of the input devices, such as sound input devices 118 and / or auxiliary input devices 119), and convert the received input audio signals into output control signals for use in stimulating a first ear of a recipient or user (i.e., the external sound processing module 124 is configured to perform sound processing on input signals received at the sound processing unit 106). Stated differently, the one or more processors (e.g., processing element(s) implementing firmware, software, etc.) in the external sound processing module 124 are configured to execute sound processing logic in memory to convert the received input audio signals into output control signals (stimulation signals) that represent electrical stimulation for delivery to the recipient.

[0043] As noted, FIG. ID illustrates an embodiment in which the external sound processing module 124 in the sound processing unit 106 generates the output control signals. In an alternative embodiment, the sound processing unit 106 can send less processed information (e.g., audio data) to the implantable component 112 and the sound processing operations (e.g., conversion of input sounds to output control signals 156) can be performed by a processor within the implantable component 112.

[0044] In FIG. ID, according to an example embodiment, output control signals (stimulation signals) are provided to the RF transceiver 122, which transcutaneously transfers the output control signals (e.g., in an encoded manner) to the implantable component 112 via external coil 108 and implantable coil 114. That is, the output control signals (stimulation signals) are received at the RF interface circuitry 140 via implantable coil 114 and provided to the stimulator unit 142. The stimulator unit 142 is configured to utilize the output control signals to generate electrical stimulation signals (e.g., current signals) for delivery to the user’s cochlea via one or more of the stimulating contacts (electrodes) 144. In this way, cochlear implant system 102 electrically stimulates the user’s auditory nerve cells, bypassing absent or defective hair cells that normally transduce acoustic vibrations into neural activity, in a manner that causes the recipient to perceive one or more components of the input audio signals (the received sound signals).

[0045] As detailed above, in the external hearing mode the cochlear implant 112 receives processed sound signals from the sound processing unit 106. However, in the invisible hearing mode, the cochlear implant 112 is configured to capture and process sound signals for use in electrically stimulating the user’s auditory nerve cells. In particular, as shown in FIG. ID, an example embodiment of the cochlear implant 112 can include a plurality of implantable sound sensors 165(1), 165(2) that collectively form a sensor array 160, and an implantable sound processing module 158. Similar to the external sound processing module 124, the implantable sound processing module 158 can comprise, for example, one or more processors and a memory device (memory) that includes sound processing logic. The memory device can comprise any one or more of: Non-Volatile Memory (NVM), Ferroelectric Random Access Memory (FRAM), read only memory (ROM), random access memory (RAM), magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical, or other physical / tangible memory storage devices. The one or more processors are, for example, microprocessors or microcontrollers that execute instructions for the sound processing logic stored in memory device.

[0046] In the invisible hearing mode, the implantable sound sensors 165(1), 165(2) of the sensor array 160 are configured to detect / capture input sound signals 166 (e.g., acoustic sound signals, vibrations, etc.), which are provided to the implantable sound processing module 158. The implantable sound processing module 158 is configured to convert received input sound signals 166 (received at one or more of the implantable sound sensors 165(1), 165(2)) into output control signals 156 for use in stimulating the first ear of a recipient or user (i.e., theimplantable sound processing module 158 is configured to perform sound processing operations). Stated differently, the one or more processors (e.g., processing element(s) implementing firmware, software, etc.) in implantable sound processing module 158 are configured to execute sound processing logic in memory to convert the received input sound signals 166 into output control signals 156 that are provided to the stimulator unit 142. The stimulator unit 142 is configured to utilize the output control signals 156 to generate electrical stimulation signals (e.g., current signals) for delivery to the user’s cochlea, thereby bypassing the absent or defective hair cells that normally transduce acoustic vibrations into neural activity.

[0047] It is to be appreciated that the above description of the so-called external hearing mode and the so-called invisible hearing mode are merely illustrative and that the cochlear implant system 102 could operate differently in different embodiments. For example, in one alternative implementation of the external hearing mode, the cochlear implant 112 could use signals captured by the sound input devices 118 and the implantable sound sensors 165(1), 165(2) of sensor array 160 in generating stimulation signals for delivery to the user.

[0048] FIG. IE is a block diagram illustrating one example arrangement for an external computing device 110 configured to perform one or more operations in accordance with certain embodiments presented herein. As shown in FIG. IE, in its most basic configuration, the external computing device 110 includes at least one processing unit 183 and a memory 184. The processing unit 183 includes one or more hardware or software processors (e.g., Central Processing Units) that can obtain and execute instructions. The processing unit 183 can communicate with and control the performance of other components of the external computing device 110. The memory 184 is one or more software or hardware-based computer-readable storage media operable to store information accessible by the processing unit 183. The memory 184 can store, among other things, instructions executable by the processing unit 183 to implement applications or cause performance of operations described herein, as well as other data. The memory 184 can be volatile memory (e.g., RAM), non-volatile memory (e.g., ROM), or combinations thereof. The memory 184 can include transitory memory or non-transitory memory. The memory 184 can also include one or more removable or non-removable storage devices. In examples, the memory 184 can include random access memory (RAM), read only memory (ROM), EEPROM (Electronically-Erasable Programmable Read-Only Memory), flash memory, optical disc storage, magnetic storage, solid state storage, or any other memory media usable to store information for later access. By way of example, and not limitation, thememory 184 can include wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared and other wireless media or combinations thereof. In certain embodiments, the memory 184 comprises logic 185 that, when executed, enables the processing unit 183 to perform aspects of the techniques presented.

[0049] In the illustrated example of FIG. IE, the external computing device 110 further includes a network adapter 186, one or more input devices 187, and one or more output devices 188. The external computing device 110 can include other components, such as a system bus, component interfaces, a graphics system, a power source (e.g., a battery), among other components. The network adapter 186 is a component of the external computing device 110 that provides network access (e.g., access to at least one network 189). The network adapter 186 can provide wired or wireless network access and can support one or more of a variety of communication technologies and protocols, such as ETHERNET, cellular, BLUETOOTH, near-field communication, and RF (Radiofrequency), among others. The network adapter 186 can include one or more antennas and associated components configured for wireless communication according to one or more wireless communication technologies and protocols. The one or more input devices 187 are devices over which the external computing device 110 receives input from a user. The one or more input devices 187 can include physically- actuatable user-interface elements (e.g., buttons, switches, or dials), a keypad, keyboard, mouse, touchscreen, and voice input devices, among other input devices that can accept user input. The one or more output devices 188 are devices by which the external computing device 110 is able to provide output to a user. The output devices 188 can include a display 190 (e.g., a liquid crystal display (LCD)) and one or more speakers 191, among other output devices for presentation of visual or audible information to the recipient, a clinician, an audiologist, or other user.

[0050] It is to be appreciated that the arrangement for the external computing device 110 shown in FIG. IE is merely illustrative and that aspects of the techniques presented herein can be implemented at a number of different types of systems / devices including any combination of hardware, software, and / or firmware configured to perform the functions described herein. For example, the external computing device 110 can be a personal computer (e.g., a desktop or laptop computer), a hand-held device (e.g., a tablet computer), a mobile device (e.g., a smartphone), a surgical system, and / or any other electronic device having the capabilities to perform the associated operations described elsewhere herein.

[0051] As noted, various devices can use adaptive filtering techniques to suppress an unwanted interference (usually environmental noise, feedback, echo, etc.) from the target signal of interest (usually speech). FIG. 2A is a block diagram illustrating one such example noise cancellation system 200. As shown in FIG. 2A, a signal processing path 250 of the noise cancellation system 200 includes an input (source) 251, a noise cancellation filter system 253, and an output (sink) 255. The input (source) 251 corresponds to one or more sensors, such as microphone(s), accelerometer(s), etc., and provides a noisy input signal 252 to the noise cancellation filter system 253. The noise cancellation filter system 253 processes the noisy input signal 252 (e.g., using adaptive filtering / phase cancelling) to cancel or reduce body noise present in the noisy input signal 252, and as a result, provides a clean output signal 254 at the output (sink) 255. The output (sink) 255 can correspond to a stimulator, such as the stimulator unit 142 of FIG. ID, for example. It should be appreciated that there can be one or more pre-processing blocks between the input (source) 251 and the noise cancellation filter system 253, and / or one or more post-processing blocks between the noise cancellation filter system 253 and the output (sink) 255. By way of example and not by limitation, various details of one exemplary noise cancellation filter system will be described below with reference to FIG. 2B.

[0052] As noted, it is beneficial to remove noise from a sound signal, such as the sound signals 166 (refer to FIG. ID). For example, during operation of a cochlear implant system, such as the cochlear implant system 102 including the cochlear implant 112 (refer to FIG. ID), the cochlear implant is configured to receive sound signals for further processing. External sound (e.g., speech) is detected along with noise generated by the body of a recipient of the implantable device, commonly referred to as “body noise.” Therefore, sound signals can include a mixture of both external sounds and body noises. However, it generally is undesirable to include the body noises in the output signals that are used to deliver a hearing percept to the recipient. For instance, the body noise can distort the external sounds that are of interest to the recipient. Accordingly, hearing devices can include implantable body noise cancellation systems that are configured to substantially reduce or remove undesirable body noise from sound signals to enable the recipient to perceive sound (e.g., external sound without distortions caused by body noises) more desirably.

[0053] FIG. 2B is a schematic diagram illustrating an implantable device system 202, which can be a cochlear implant 112 as described above with reference to FIG. ID for example, operating with an implantable adaptive body noise reduction system 300, in accordance withcertain embodiments presented herein. It is noted that the implantable adaptive body noise reduction system 300 of FIG. 2B is provided as one specific, but non-limiting, illustrative example of the noise cancellation filter system 253 of FIG. 2A, and other suitable noise cancellation / reduction techniques are also possible. The implantable adaptive body noise reduction system 300 has a “calibration mode” and a “run-time” mode, and the specific example of FIG. 2B primarily illustrates the “run-time” mode.

[0054] As shown in FIG. 2B, the input (source) of the implantable device system 202 includes a sensor array 260, which includes a first sensor 265A (e.g., a microphone, a sound sensor, etc.) and a second sensor 265B (e.g., an accelerometer, a vibration sensor, etc.). The first sensor 265A is primarily configured to capture external sound, whereas the second sensor 265B is primarily configured to capture vibrations.

[0055] More specifically, the sensor array 260 is implanted in a recipient (e.g., embedded in a skull), and the first sensor 265A can capture external sound generated from a sound source outside of the body of the recipient, such as from an external environment and / or from another person, and the external sounds are of interest for processing for perception by the recipient. The second sensor 265B can capture body vibrations (body noises) of the recipient, which can be conducted through the body of the recipient and to the sensor array 260. In certain examples, the first sensor 265A and the second sensor 265B can be equally sensitive to vibrations from the skull (body noise = internal sound), but the second sensor 265B can be less sensitive to airborne sound (external sound). In general, the term "skull vibrations" is sometimes used herein to refer refers to internal sound transmitted to the sensor array 260, mostly via the skull bone where the sensor array 260 is anchored. In the broader sense, "sound" is any vibration, of air molecules or other mediums. Although the present disclosure discusses operations of the sensor array 260 implanted in the recipient, the techniques described herein can be applied to a sensor array at any suitable location, such as on an external body part (e.g., the scalp) of the recipient.

[0056] During operation of the implantable device system 202, the first sensor 265A can also capture body noise provided by the body of the recipient. The body noise can mix with and distort the external sound that is of interest for perception by the recipient. The implantable adaptive body noise reduction system 300 is configured to filter signals captured by the sensor array 260 to reduce, remove, or cancel body noise.

[0057] As shown in FIG. 2B, during the run-time mode, the implantable adaptive body noise reduction system 300 is configured to receive and process an input sound signal 302 captured by the first sensor 265 A and / or an input vibration signal 304 captured by the second sensor 265B to provide a processed signal 306 used for enabling the recipient to perceive sound. For example, the input sound signal 302 includes external sound that is of interest for perception by the recipient. However, the input sound signal 302 can also include body noise, and the input vibration signal 304 is representative of the body noise portion of the input sound signal 302. The implantable adaptive body noise reduction system 300 operates in the run-time mode to filter the input vibration signal 304 from the input sound signal 302 to provide a processed signal 306 that includes reduced amounts of body noise (e.g., primarily includes external sound) for perception by the recipient.

[0058] By way of example and not limitation, the implantable adaptive body noise reduction system 300 is a part of a sound processing module 308, such as the implantable sound processing module 158 of the cochlear implant 112 described above with reference to FIG. ID (or another non-transitory computer-readable medium), and can be implemented in a memory 310 and / or in a processor 312 of the sound processing module 308. As such, the processed signal 306 output by the implantable adaptive body noise reduction system 300 can be provided to a stimulator unit, such as the stimulator unit 142 of the cochlear implant 112 of FIG. ID, to generate electrical stimulation signals for delivery to the cochlea of the recipient, other suitable output sound signals for enabling the recipient to perceive sound, or any other suitable processed signals. By removing the input vibration signal 304 from the input sound signal 302, the implantable adaptive body noise reduction system 300 improves the integrity of the input sound signal 302 to, in turn, improve the sound perceived by the recipient.

[0059] As shown in FIG. 2B, the implantable adaptive body noise reduction system 300 includes a filter sub-system 318 configured to process the input sound signal 302 and / or the input vibration signal 304. In general, the filter sub-system 318 utilizes an algorithm with different parameters, such as coefficient weights of an algorithm (e.g., gain changes, phase changes, filter coefficients), to process the input sound signal 302 and / or the input vibration signal 304. For instance, coefficient weights are applied, such as in a particular frequency range (e.g., audible range), such that the input sound signal 302 and the input vibration signal 304 have substantially equal magnitude and / or phase.

[0060] In the specific example of FIG. 2B, the filter sub-system 318 includes a fixed prefilter 322 and an adaptive filter 324. The fixed prefilter 322 includes fixed parameters used toinitially process the input vibration signal 304 and / or the input sound signal 302 (e.g., during a pre-processing stage) to provide a preliminarily processed signal 326. The adaptive filter 324 includes adjustable parameters used for further processing of the preliminarily processed signal 326 (e.g., during a main processing stage) to provide the processed signal 306. That is, the fixed prefilter 322 and the adaptive filter 324 sequentially process the input vibration signal 304 and / or the input sound signal 302 to provide the processed signal 306.

[0061] The implantable adaptive body noise reduction system 300 can operate in a calibration mode, for example, during fitting of the implantable device system 202 in the recipient to establish the fixed parameters of the fixed prefilter 322. After identification of a convergence point (e.g., after multiple iterations or loops in which the parameters of the adaptive filter 324 are adjusted and a resulting processed signal is compared to a reference vibration signal), the parameters of the adaptive filter 324 at the convergence point (e.g., providing the desirable processed signal) are then established for the fixed prefilter 322 to use during the run-time mode. As such, in the calibration mode, the adjustable parameters of the adaptive filter 324 are used to process a reference sound signal and / or a reference vibration signal to establish the fixed parameters of the fixed prefilter 322 based on the desirable processed signal, and in the run-time mode, the established fixed parameters of the fixed prefilter 322 and the adjustable parameters of the adaptive filter 324 are used to process the input sound signal 302 and / or the input vibration signal 304 to output the processed signal 306 for enabling the recipient to perceive sound.

[0062] As noted, the fixed parameters of the fixed prefilter 322 are established during the calibration mode, and the fixed parameters are maintained during the run-time mode. In other words, the fixed parameters are unchanged during the run-time mode after being set as a result of the calibration mode. However, the implantable adaptive body noise reduction system 300 in the specific example of FIG. 2B is adaptive (e.g., in the frequency domain, the time domain) in that the adjustable parameters of the adaptive filter 324 can be changed during the run-time mode to improve processing of the input vibration signal 304 and / or of the input sound signal 302. The adjustable parameters can be iteratively adjusted to improve the processed signals 306 provided via processing of the input vibration signals 304 and / or of the input sound signals 302.

[0063] For instance, during a first iteration of the run-time mode (e.g., performed immediately after completion of the calibration mode), a first input sound signal 302 and a first input vibration signal 304 are received. The fixed prefilter 322 uses the fixed parameters to processthe first input vibration signal 304 and / or the first input sound signal 302 to provide a first preliminarily processed signal 326 to the adaptive filter 324. In some embodiments, the adaptive filter 324 uses predetermined, preset, or default parameters during the first iteration to process the first preliminarily processed signal 326. As an example, the adaptive filter 324 functions as a pass-through filter that does not further process the first preliminarily processed signal 326 (e.g., each coefficient weight of the adaptive filter 324 is one). In other words, the adaptive filter 324 outputs the first preliminarily processed signal 326 as received from the fixed prefilter 322. The first preliminarily processed signal 326 is then removed from the first input sound signal 302 to provide a first processed signal 306. The first processed signal 306 is then output by the implantable adaptive body noise reduction system 300 to enable the recipient to perceive sound (e.g., the external sound of interest in the input sound signal 302), such as via electrical stimulation signals or other output sound signals.

[0064] The first processed signal 306 is also compared to the first input vibration signal 304 at an adaptation algorithm 320 to determine a difference (e.g., an absolute value of a difference) between the first processed signal 306 and the first input vibration signal 304. In particular, because the input sound signals 302 captured by the first sensor 265 A potentially include some noise captured by the second sensor 265B, the first input sound signal 302 can include at least some similarities as the first input vibration signal 304. Therefore, the difference between the first processed signal 306 and the first input vibration signal 304 indicates an amount of the first input vibration signal 304 removed from the first input sound signal 302 to provide a desirable sound signal. Based on the difference between the first processed signal 306 and the first input vibration signal 304, the adaptation algorithm 320 adjusts the adjustable parameters (e.g., from the predetermined parameters used during the first iteration) of the adaptive filter 324 so that a subsequent processed signal 306 includes less of a corresponding input vibration signal 304. The adaptive filter 324 subsequently uses the adjustable parameters adjusted by the adaptation algorithm 320 to process a subsequent input sound signal 302 and / or a subsequent input vibration signal 304 to remove more of the subsequent input vibration signal 304 from the subsequent input sound signal 302.

[0065] For instance, during a second iteration of the run-time mode occurring immediately after the first iteration, a second input sound signal 302 and a second input vibration signal 304 are received. The fixed prefilter 322 uses the fixed parameters (e.g., the same fixed parameters used to process the first input sound signal 302 and / or the first input vibration signal 304) to process the second input sound signal 302 and / or the second input vibration signal 304 toprovide a second preliminarily processed signal 326 to the adaptive filter 324. The adaptive filter 324 then uses the adjustable parameters established by the adaptation algorithm 320 to further process the second preliminarily processed signal 326. The further processed signal is then removed from the second input sound signal 302 to provide a second processed signal 306. The changing of the adjustable parameters of the adaptive fdter 324 causes more of the second input vibration signal 304 to be removed from the second input sound signal 302 as compared to removal of the first input vibration signal 304 from the first input sound signal 302. That is, a difference between the second processed signal 306 and the input vibration signal 304 can be greater than a difference between the first processed signal 306 and the first input vibration signal 304. As such, the second processed signal 306 can be improved (e.g., include more of, or better integrity of, a desirable sound signal) as compared to the first processed signal 306.

[0066] The second processed signal 306 can also be compared to the input vibration signal 304 at the adaptation algorithm 320, and the adaptation algorithm 320 further changes the adjustable parameters of the adaptive filter 324 in response for the adaptive filter 324 to process a subsequent input sound signal 302 and / or a subsequent input vibration signal 304. In this manner, the adjustable parameters of the adaptive filter 324 are iteratively adjusted for each received input sound signal 302 and / or input vibration signal 304 to improve the processed signal 306 being output. In some examples, the adjustable parameters of the adaptive filter 324 are changed continuously during operation of the implantable device system 202 in the runtime mode. However, in some other examples, the adjustable parameters of the adaptive filter 324 are maintained at a certain point during operation of the implantable device system 202 in the run-time mode. For example, the adjustable parameters of the adaptive filter 324 remain unchanged after a threshold quantity of iterations of changing the adjustable parameters of the adaptive filter 324 has been reached, after a change in the adjustable parameters of the adaptive filter 324 is below a threshold change, and / or after a duration of time of operation of the implantable device system 202 in the run-time mode.

[0067] In certain embodiments, the adaptation algorithm 320 can also make use of the input sound signal 302 (together with 304) to increase the robustness of the adaptation. That is, in another example, the adaptation algorithm 320 uses both the received input sound signal 302 and / or input vibration signal 304 to adapt the filter only when body noise is detected. In one such embodiment, the filter coefficients may not be changed when the adaptation algorithm determines that there is not enough body noise.

[0068] The fixed parameters of the fixed prefilter 322 can help improve operation of the implantable device system 202 in the run-time mode. For example, because the fixed parameters of the fixed prefilter 322 help perform some initial processing during the run-time mode to remove at least some of the input vibration signal 304 from the input sound signal 302, the run-time mode can immediately operate (e.g., after completion of the calibration mode) to provide a processed signal 306 with improved integrity, such as in comparison with an embodiment that does not include the fixed prefilter 322 and therefore may not immediately remove a significant amount of an input vibration signal from an input sound signal. Additionally or alternatively, a more desirable processed signal 306 can be quickly provided during the run-time mode, such as with fewer iterations of changing the adjustable parameters of the adaptive filter 324. Thus, the fixed prefilter 322 improves operation of the implantable adaptive body noise reduction system 300 to provide the processed signal 306.

[0069] As noted, the present disclosure provides several different signal techniques / methods to effectively reduce the addition of any unwanted distortions that can otherwise result from conventional adaptive filtering schemes, such as in a noise cancellation system. A first example technique is described below with reference to FIGs. 3A, 3B, 4A, and 4B, while a second example technique is described below with reference to FIGs. 5 and 6. Finally, a third example solution is described below with reference to FIGs. 7 and 8. It is noted that these example solutions are not mutually exclusive, and one or more of these example solutions can be combined in different ways (one non-limiting illustrative example of which is described below with reference to FIG. 9).

[0070] As used in the following description of example embodiments, the term “noise” can refer various different types of noise that can be present in various signals, including but not limited to body noise, environment noise, feedback, echo, and / or distortion that can be present in one or more input signals (e.g., “noisy” microphone signals, etc.). In certain embodiments, the term “noise” can also refer to different types of distortion that can be present in noise cancellation output signals (i.e., amplification distortions or “hiss” introduced into otherwise “clean” output signals by noise cancellation filter systems).

[0071] In one example embodiment of the techniques presented herein, an adaptive noise cancellation system is configured to adjust a variable filtering strength parameter to control (e.g., limit or disable) noise cancellation filtering when a noise cancellation filtering is expected to add distortions. In another example embodiment of the techniques presented herein, a noise reduction system is configured to apply noise cancellation gains to attenuate noise (e.g., bodynoise, environmental noise, feedback, echo, distortion, etc.) present in one or more input signals, when a noise cancellation system would otherwise introduce distortions. In some other example embodiments, a noise reduction system is configured to apply noise cancellation gains to attenuate noise (e.g., amplification distortions, hiss, increased noise floor, etc.) present in one or more noise cancellation output signals, when a noise cancellation system introduces distortions.Example Solution 1 - Variable noise cancellation filtering strength

[0072] A first example solution to avoid or reduce distortions from conventional filtering schemes employs the use of a variable noise cancellation filtering strength parameter to reduce or effectively “turn off’ the noise cancellation filtering (i.e., an adjustable strength of the adaptive filter) when it is expected that the noise cancellation filtering would add distortions.

[0073] FIG. 3 A is a block diagram illustrating an adaptive noise cancellation system 360, according to a first example embodiment. As shown in FIG. 3 A, a signal processing path 350 of the adaptive noise cancellation system 360 includes an input (source) 351, a noise cancellation filter system 353, a filtering strength controller 355, and an output (sink) 359. The input (source) 351 corresponds to one or more sensors, such as microphone(s), accelerometer(s), etc., and provides a noisy input signal 352 to the noise cancellation filter system 353. The output (sink) 359 can correspond to a stimulator, such as the stimulator unit 142 of FIG. ID, for example. It should be appreciated that there can be one or more preprocessing blocks between the input (source) 351 and the noise cancellation filter system 353, and / or one or more post-processing blocks between the noise cancellation filter system 353 and the output (sink) 359.

[0074] In this example embodiment, the filtering strength controller 355 is configured to determine a variable filtering strength parameter, a, based on the input level (magnitude) of the noisy input signal 352, as shown in FIG. 3A. The filtering strength controller 355 provides an intermediate signal 356 to the noise cancellation filter system 353 that indicates the variable filtering strength parameter (a). The noise cancellation filter system 353 processes the noisy input signal 352 (e.g., using adaptive filtering / phase cancelling) to cancel or reduce body noise present in the noisy input signal 352, and as a result, provides a clean output signal 358 at the output (sink) 359. In this example embodiment, the noise cancellation filter system 353 applies the variable filtering strength parameter 357 according to the value of (a) received inthe intermediate signal 356. When the input signal level is in a normal range, a is set to 1, such that the noise cancellation filtering is “on” at full-strength. When the input signal level is approaching a noise floor level or a saturation level, a is decreased (where 0 < a < 1), such that the noise cancellation filtering has reduced strength. When the input signal level is below the noise floor or above the saturation level, a is set to 0, such that the noise cancellation filtering is effectively turned “off.” This aspect of the first example solution is shown and further described below with reference to FIG. 3B.

[0075] The first example solution involves using a variable noise cancellation filtering strength parameter, a, with 0 < a < 1, to effectively “turn off’ the noise cancellation filtering when it is expected that it would add distortions. When a = 1, the system is equivalent to a conventional noise cancellation filtering scheme with the filter always active at full strength. As a is decreased, the strength ofthe noise cancellation filtering is limited more and more (e.g., decreasing values of a down from 1 towards 0, dynamically or in certain increments, etc.), down to a = 0 at which point the noise cancellation filter is effectively bypassed. out = a ■ (mic — noi) + (1 — a) ■ mic = mic — a ■ noi

[0076] Having a transitional region where a rapidly decreases from 1 down to 0 (i.e., where 0 < a < 1) can ensure a smoother transition between the normal range and the noise floor level, as well as between the normal range and the saturation level, as further explained below with reference to FIG. 3B.

[0077] An alternative manner of characterizing the parameter, a, is as a “mixing" parameter. As shown in the above equation, the output of the noise cancellation system (i.e., mic — noi) is mixed with the original noisy input signal (i.e., mic). The parameter a, is the proportion of the output and ( 1 - a) is the proportion of noisy input that are mixed together.

[0078] FIG. 3B is an example illustration of a variable noise cancellation filtering strength or mixing parameter, a, with respect to an input level (magnitude or power) of an unfiltered input signal, mic, according to the first example embodiment. In order to avoid distortions according to the first example solution of FIG. 3A, the value of a can be set based on the input level of the unfiltered input signal, mic, as shown in FIG. 3B.

[0079] When the input level of mic is in a normal range 375 (i.e., between point 374 and point 376), a is set to 1 such that the adaptive filter output noi is propagated to the system output. Here, the noise cancellation filtering is “on” at full strength. As the input level of mic approaches noise floor 370 (i.e., in a lower range 373 from point 374 to point 372), the variablefiltering strength parameter a is decreased rapidly (where 0 < a < 1). Here, the noise cancellation filtering is said to have a reduced filtering strength. This reduced filtering strength can vary depending on proximity to the noise floor 370, as shown in FIG. 3B (e.g., refer to point 372). When the input level of mic is below the noise floor 370 (i.e., at point 371), a is set to 0 such that the adaptive filter output not (and its hiss distortions) are not propagated to the system output. Here, the noise cancellation filtering is effectively turned “off.” Instead, the unfiltered input signal, mic, is directly used as output of the system, without being processed by the adaptive filter.

[0080] It is noted that the parameter a does not need to vary between 0 and 1. In some embodiments, the cancellation strength could vary between e.g. 0.1 and 0.9 and this would substantially have the same desired effect (e.g., reducing distortions). In general, the parameter a is significantly lower when approaching saturation or noise floor compared to when the filter operates in "regular" mode.

[0081] A similar approach of decreasing a can be taken with respect to saturation level 380. As the input level of mic approaches the saturation level 380 (i.e., in an upper range 377 from point 376 to point 378), the variable filtering strength parameter a is decreased rapidly (where 0 < a < 1). Here, the noise cancellation filtering is said to have a reduced filtering strength. This reduced filtering strength can vary depending on proximity to the saturation level 380, as shown in FIG. 3B (e.g., refer to point 378). When the input level of mic is above the saturation level 380 (i.e., at point 379), a is set to 0 such that the adaptive filter output not (and its saturation artefact distortions) are not propagated to the system output. Here, the noise cancellation filtering is effectively turned “off.” Instead, the unfiltered input signal, mic, is directly used as output of the system, without being processed by the adaptive filter.

[0082] This solution can be employed in time-domain filters and frequency-domain filters and can be employed both for acoustic devices and cochlear implants. For frequency-domain implementations, the variable filtering strength parameter, a, can be chosen independently for each frequency band in certain embodiments (e.g., the input signal is filtered to generate a plurality of filtered input signals each associated with one of a plurality of frequency bands and the variable filtering strength parameter is chosen independently for each frequency band). It is be appreciated that solution 1 becomes a frequency-domain approach (as Solution 2 and 3) when alpha is tuned per band, as mentioned above. As such, in certain examples, it is possible to combine Solutions 1, 2, and 3 within a same operable system.

[0083] FIG. 4A is a flowchart illustrating an example method 400 according to an example embodiment. The method 400 can be implemented using the arrangement shown in FIG. 3A, for example. At operation 410, method 400 includes receiving at least one input signal at a noise cancellation system. At operation 420, method 400 includes processing at least one input signal using the noise cancellation system to generate a noise cancellation output signal, wherein the noise cancellation system is controlled by a variable filtering strength parameter that is a function of a level of the at least one input signal. The at least one input signal can be a sound signal, for example.

[0084] At operation 430, method 400 further includes selectively adjusting the variable filtering strength parameter to control (e.g., limit or disable) noise cancellation filtering in response to determining that the noise cancellation system is expected to add distortions to the at least one input signal when generating the noise cancellation output signal.

[0085] In some examples, operation 430 includes decreasing a value of the variable filtering strength parameter to reduce strength of the noise cancellation filtering as the at least one input signal approaches at least one of a noise floor level or a saturation level. In one example, operation 430 can include dynamically decreasing the value of the variable filtering strength parameter to reduce the strength of the noise cancellation filtering as a function of proximity of the level of the at least one input signal to the noise floor level. In another example, operation 430 can include dynamically decreasing the value of the variable filtering strength parameter to reduce the strength of the noise cancellation filtering as a function of proximity of the level of the at least one input signal to the saturation level.

[0086] In some examples, operation 430 includes setting a value of the variable filtering strength parameter to zero to disable the noise cancellation filtering when the at least one input signal reaches or exceeds at least one of a noise floor level or a saturation level.

[0087] FIG. 4B is a flowchart illustrating an example method 450 according to an example embodiment. The method 450 can be implemented using the arrangement shown in FIG. 3 A, for example. At operation 460, method 450 includes receiving at least one input signal at a noise cancellation filter, and processing the at least one input signal to generate a noise cancellation output signal. At operation 470, method 450 includes determining, based on the at least one input signal, whether the noise cancellation filter is expected to add distortions to the at least one input signal when generating the noise cancellation output signal. At operation 480, method 400 includes selectively controlling (e.g., limiting or disabling) the noisecancellation filter in response to determining that the noise cancellation filter is expected to add distortions.

[0088] In certain examples, the noise cancellation filter operates in accordance with a variable filtering strength parameter, and operation 480 can include selectively adjusting the variable filtering strength parameter to control (e.g., limit or disable) the noise cancellation filter in response to determining that the noise cancellation filter is expected to add distortions. The variable filtering strength parameter is a function of a level of the at least one input signal, for example. The at least one input signal can be a sound signal, for example.

[0089] In some examples, operation 470 can include monitoring the level of the at least one input signal in relation to at least one of a noise floor level or a saturation level. In some examples, operation 480 can including selectively adjusting the variable filtering strength parameter when the at least one input signal is approaching, at, or below the noise floor level. In some examples, operation 480 can include selectively adjusting the variable filtering strength parameter when the at least one input signal is approaching, at, or above the saturation level.

[0090] In some examples, operation 480 can include dynamically decreasing a value of the variable filtering strength parameter to reduce strength of the noise cancellation filter as the at least one input signal approaches at least one of the noise floor level or the saturation level. In some examples, operation 480 can include setting a value of the variable filtering strength parameter to zero to disable the noise cancellation filter when the at least one input signal reaches or exceeds at least one of the noise floor level or the saturation level.

[0091] Thus, the techniques described above with reference to FIGs. 3A, 3B, 4A, and 4B can be used to reduce, remove, or avoid distortion from a noise cancellation filtering scheme by dynamically adjusting a variable filtering strength parameter to control (e.g., limit or disable) the noise cancellation filtering based on a level of at least one input signal. In some examples, the noise cancellation output signal can be used as the system output signal, and this system output signal can be used to generate a stimulation signal representing the at least one input signal. In some other examples, the at least one input signal can be used as the system output signal, without performing noise cancellation filtering, to generate a stimulation signal representing the at least one input signal. In some other examples, the noise cancellation filtering can operate at a reduced strength, based on a proximity of the level of the at least one input signal to a noise floor level or a saturation level.Example Solution 2 - Noise reduction instead of noise cancellation

[0092] A second example solution to avoid or reduce additional distortions from conventional fdtering schemes employs a noise reduction system (also referred to herein as a “gain application” block) after the noise cancellation block (the adaptive filter) to perform noise reduction to suppress the environmental noise (or feedback), instead of the noise cancellation filter, when use of the noise cancellation filter would otherwise add distortion. The noise reduction system (gain application) is driven by the noise cancellation filter, but is capable of detecting signal amplification and attenuating the noise present in the noisy input signal, and thus avoiding the distortions that would otherwise be introduced by the noise cancellation filter. In this example, the noise reduction (gain application) operates on the noisy input signal, rather than the clean output signal from the noise cancellation filter. One benefit of this example solution is reduced power consumption and increased battery autonomy.

[0093] FIG. 5 is a block diagram illustrating a noise reduction system 560, according to a second example embodiment. As shown in FIG. 5, a signal processing path 550 of the noise reduction system 560 includes an input (source) 551, a noise cancellation filter system 553, a noise reduction gain controller 555, a gain application block 557, and an output (sink) 559. The input (source) 551 corresponds to one or more sensors, such as microphone(s), accelerometer(s), etc., and provides a noisy input signal 552 to the noise cancellation filter system 553. The output (sink) 559 can correspond to a stimulator, such as the stimulator unit 142 of FIG. ID, for example. It should be appreciated that there can be one or more preprocessing blocks between the input (source) 551 and the noise cancellation filter system 553, and / or one or more post-processing blocks between the noise cancellation filter system 553 and the output (sink) 559.

[0094] In the specific example of FIG. 5, the noise reduction system 560 includes the noise reduction gain controller 555 and the gain application block 557. The noise reduction gain controller 555 also receives the noisy input signal 552, as well as a noise cancellation output signal 554 that is generated by the noise cancellation filter system 753. This this example embodiment, the noise cancellation output signal can be the “clean” output signal, or a signal representing attenuation applied by the noise cancellation filtering. The noise reduction gain controller 555 determines a noise reduction gain value (gl) as a function of the noisy input signal 552 and the noise cancellation output signal 554 (e.g., the “clean output” signal or an“atenuation signal”). In the illustrated example, the noise reduction gain controller 555 outputs an intermediate signal 556 (i.e., an intermediate noise reduction signal), which can include the noisy input signal 552 from the input (source) 751 along with the noise reduction gain value (gl). The gain application block 557 generates a noise reduction output signal 558 (also referred to herein as a “atenuated” output signal) by applying the noise reduction gain value (gl) to the noisy input signal 552, and the noise reduction output signal 558 (“atenuated” output signal) is then provided to the output (sink) 559.

[0095] Thus, the gain application block 757 of the noise reduction algorithm of FIG. 5 operates on the noisy input signal 552 from the input (source) 551, rather than the “clean” output signal from the noise cancellation fdter system 553. That is, the clean output signal from the noise cancellation fdter system 553 is used by the noise reduction gain controller 555 to derive the noise reduction gain value (gl), but not to generate the noise reduction output signal 558 (i.e., the system output signal, or “atenuated” output signal), in the second example solution of FIG. 5. Here, the noise reduction gain value (gl) represents the atenuation that is otherwise given to the noisy input signal 552 by the noise cancellation fdter system 553 when generating the clean output signal.

[0096] As noted above, FIG. 5 illustrates an example noise reduction gain controller 555 outputs an intermediate signal 556. It is to be appreciated that, in alternative embodiment, the gain controller output can be just the gain (gl) used in the gain application block (no need for an intermediate signal). In such examples, the gain application would then apply the gain to the noisy input signal 552.

[0097] As noted, the second example solution makes use of noise reduction to fdter the noisy input signal rather than the noise cancellation fdter directly. This technique has equivalent body noise suppression performance to the other two example solutions described herein, but also has the additional benefit of reduced power consumption, which is essential to keep to a minimum in a totally implantable cochlear implant system due to the limited batery longevity over the years.

[0098] In totally implantable cochlear implants, for example, a body noise reduction (BNR) algorithm can be used rather than a body noise cancellation (BNC) approach to avoid typical distortions from a noise cancellation filtering scheme. To be precise, in this configuration the BNC system (adaptive fdter) is still present and is performing phase cancellation. However, the BNC fdter is not used directly to generate the output signal. Instead, the clean BNC outputsignal is used to inform / drive the BNR gain application to attenuate body noises. The body noise reduction (BNR) algorithm described herein can be used as an alternative method to the body noise cancellation (BNC) approach for performing body noise suppression without introducing distortions like the typical hiss associated with an increased noise floor from a conventional noise cancellation algorithm.

[0099] Contrary to the BNC approach, which subtracts the body noise estimate from the noisy input microphone signal to obtain a “clean” BNC output signal, the BNR algorithm applies a gain (also referred to herein as a BNR gain value (g)) to each frequency band of the noisy microphone signal to attenuate those spectral bands where body noise is present. Using BNR gains in this manner provides additional flexibility and control over the clean BNR output signal, in comparison to the BNC filtering scheme.[ooioo] The BNR gains, g, applied to each frequency bin, k, of the noisy input microphone signal, Mic, are calculated as a function of the BNC output signal, Clean-. gdB= min (k(cleanLevelsdBk— micLevelsdBk), 0 dB)[ooioi] where micL eve IsdBand cleanLevelsdBare the magnitude spectrum (in dB) of the “noisy” input microphone signal (Mic) and the “clean” BNC output signal (Clean), respectively. Here, the BNR gains (g) represent the attenuation given by the BNC filter.

[0102] It is to be appreciated that the gain can be calculated from the magnitude spectrum or the power spectrum (which is the square of the magnitude spectrum). Equivalent gains can be obtained in Solutions 2 and Solution 3 using the power spectra.

[0103] In certain example embodiments, a BNR gain slopes parameter, A, is configurable in each frequency band and controls the amount of noise reduction. The greater the slope (A), the higher the body noise attenuation. Since the slope A can be greater than 1, the BNR algorithm (gain application) can achieve a more aggressive noise reduction compared to the BNC approach (adaptive filter), if desired. Note that this is a secondary advantage of the second example solution over the first and third example solutions described herein. In the simplest case of A = 1, the BNR algorithm provides the same attenuation to the noisy input Mic signal as the BNC filter alone would. For both BNC and BNR, the output signal magnitude is cleanLevels (while the phases can differ).

[0104] However, contrary to the BNC approach, the BNR algorithm does not amplify the noisy input Mic signal since the BNR gain g is “clipped” to, in one example, a maximum of 0 dB. Itis to be appreciated that the maximum gain need not be OdB, but instead just a smaller dB value like +3dB. The desired effect of reducing distortions would still be obtained, albeit a little less optimally than using OdB. This is done since an amplification of the noisy input Mic signal is typically an undesirable distortion introduced by the BNC system (adaptive filter), such as a noise floor increase or other distortions due to nonlinearities of the respective sensors (i.e., the microphone and the accelerometer, respectively).

[0105] The BNR output signal, Out, corresponds to the noisy input microphone signal (Mic), as attenuated by the BNR gains g (expressed below as gain factors instead of dB):

[0106] This implies that, for a BNR gain slopes parameter A = 1, the magnitude of the BNR output signal (Out) when using the BNR algorithm is the same as the magnitude of the clean BNC output signal (Clean) when the BNC filter is attenuating the noisy input Mic signal (i.e., | CleanFFT| < \MicFFF|):

[0107] Thus, the “magnitude” of the BNR output signal, Out, is the same as the “magnitude” of the clean BNC output signal, Clean, in this example. Note that the “phases” of the clean BNC output signal (Clean) and the BNR output signal (Out) might differ.

[0108] Instead, when the BNC filter is adding distortions to the noisy input Mic signal in the clean BNC output signal (i.e., \CleanFFT\ > \MicFFT|), the BNR gain GBNR= 1 and the magnitude of the BNR output signal (Out) is equal to the magnitude of the original noisy input microphone signal Mic)'.|OutFFr| = GBNR■ \MicFFT\ = \MicFFT\

[0109] In this way, the distortions that would otherwise be added by the BNC filter into the clean BNC output signal, Clean, are avoided in the BNR output signal, Out, in this example.[oono] The use of noise cancellation (adaptive filter / phase cancellation) and the use of noise reduction (gain application) can be compared using spectrogram analysis techniques from a totally implantable cochlear implant recipient. For example, spectrograms of an unprocessed input microphone signal (Mic), a clean output signal processed with a conventional body-noise canceller (BNC) approach (Clean), and an output signal processed by the body-noise reduction(BNR) algorithm (Out) described herein can be generated and displayed to allow for comparison. In the case of own voice, the conventional BNC approach adds distortion in some own voice segments of the clean BNC output signal when the input level of Mic is relatively high (near, at, or above the saturation level), due to saturation in the accelerometer signal. In the case of silence, the conventional BNC approach adds hiss when the input level of Mic is relatively low (near, at, or below the noise floor), due to an increased noise floor resulting from the noise cancellation filtering scheme. Compared to the BNC approach, the BNR algorithm manages to attenuate the vibrations of own voice and scratching without adding distortions into the BNR output signal (Out), and / or to avoid adding hiss (i.e., increased noise floor at high frequencies due to BNC) into the BNR output signal (Out) while in silence. The output noise floor with the BNR algorithm is significantly lower than the output noise floor with the BNC approach (i.e., the BNR output signal (Out) has the same or similar noise floor as the unprocessed input microphone signal (Mic), whereas the noise floor of the BNC output signal (Clean) is significantly higher). Thus, when the input level of Mic is loud (e.g., in the case of own voice approaching or exceeding the saturation level) and / or when the input level oiMic is very soft (e.g., in the case of silence), the second example solution can be used to perform noise reduction via gain application techniques, instead of noise cancellation via adaptive filtering / phase cancellation techniques.[ooni] Since the BNR gains (g) are derived from the clean BNC output signal (Clean), the BNR algorithm requires that the BNC filter operates in the background. However, the rate of the BNC filtering with the BNR algorithm enabled does not need to be equivalent to the input Mic signal FFT analysis rate of ~I kHz, and can be significantly lower (e.g., -500 Hz). This can lead to substantial power savings since other computationally power-hungry and / or computationally expensive algorithms (like noise reference FFT, BNC static filter, BNC adaptation and cancellation) can also run slower at 500 Hz rather than -1 kHz.

[0112] FIG. 6 is a flowchart illustrating an example method 600 according to the second example embodiment. The method 600 can be implemented using the arrangement shown in FIG. 5, for example. At operation 610, method 600 includes receiving at least one input signal. At operation 620, method 600 includes processing the at least one input signal with a noise cancellation system configured to apply noise cancellation filtering to the at least one input signal to generate a noise cancellation output signal. At operation 630, method 600 includes processing the at least one input signal with a noise reduction system configured to apply noise reduction gains to the at least one input signal to generate a noise reduction output signal. Thenoise reduction gains are a function of the at least one input signal and the noise cancellation output signal, for example.

[0113] In some examples, the method 600 further includes determining the noise reduction gains based on the at least one input signal and the noise cancellation output signal. In this example embodiment, applying the noise reduction gains to the at least one input signal is operable to attenuate noise present in the at least one input signal.

[0114] In some examples, the at least one input signal is a sound signal, and the method 600 further includes using the noise reduction output signal, instead of the noise cancellation output signal, to generate a stimulation signal representative of the sound signal. In some examples, the noise cancellation system is a body noise cancellation system, and the noise reduction system is a body noise reduction system.

[0115] Thus, the techniques described above with reference to FIGs. 5 and 6 can be used to avoid introducing distortion from a noise cancellation filtering scheme by dynamically adjusting gain values to apply attenuation to at least one input signal to generate a noise reduction output signal, and the noise reduction output signal can be used as a system output signal to generate a stimulation signal representing the at least one input signal.Example Solution 3 - Noise reduction after noise cancellation

[0116] A third example solution to avoid or reduce additional distortions from conventional filtering schemes also employs a noise reduction system (“gain application” block) after the noise cancellation block, similarly to the previous embodiment, but performs noise reduction (gain application) in addition to / after the noise cancellation (adaptive filter) in this embodiment, unlike in the previous embodiment. The noise reduction system can detect amplification and attenuate any distortions present in the clean output signal from the noise cancellation filter. In this example, the noise reduction system (gain application) operates on the clean output signal from the noise cancellation system to reduce or remove any distortions (as introduced by the adaptive filter) that are present in the clean output signal. This embodiment is more advantageous in acoustic devices or hearing aids in particular, since this technique allows “phase” of the "clean signal” (output of the noise cancellation) to be maintained.

[0117] FIG. 7 is a block diagram illustrating a noise reduction system 760, according to a third example embodiment. As shown in FIG. 7, a signal processing path 750 of the noise reduction system 760 includes an input (source) 751, a noise cancellation filter system 753, a noisereduction gain controller 755, a gain application block 757, and an output (sink) 759. The input (source) 751 corresponds to one or more sensors, such as microphone(s), accelerometer(s), etc., and provides a noisy input signal 752 to the noise cancellation filter system 753. The output (sink) 759 can correspond to a stimulator, such as the stimulator unit 142 of FIG. ID, for example . It should be appreciated that there can be one or more pre-processing blocks between the input (source) 751 and the noise cancellation filter system 753, and / or one or more postprocessing blocks between the noise cancellation filter system 753 and the output (sink) 759.

[0118] In the specific example of FIG. 7, the noise reduction system 760 includes the noise reduction gain controller 755 and the gain application block 757. The noise reduction gain controller 755 also receives the noisy input signal 752, as well as a noise cancellation output signal 754 that is generated by the noise cancellation filter system 753. In this example, the noise cancellation output signal 754 is the “clean” output signal generated by the noise cancellation filtering. The noise reduction gain controller 755 determines a noise reduction gain value (g2) as a function of the noisy input signal 752 and the noise cancellation output signal 754 (the “clean” output signal). The noise reduction gain controller 755 outputs an intermediate signal 756 (i.e., an intermediate noise reduction signal), which can include the noise cancellation output signal 754 (the “clean” output signal) from the noise cancellation filter system 753 along with the noise reduction gain value (g2). The gain application block 757 generates a noise reduction output signal 758 (also referred to herein as an “attenuated” output signal) by applying the noise reduction gain value (g2) to the noise cancellation output signal 754 (the “clean” output signal) from the noise cancellation filter system 753, and the noise reduction output signal 758 (“attenuated” output signal) is then provided to the output (sink) 759.

[0119] Thus, the noise reduction algorithm of FIG. 7 operates on the “clean” output signal from the noise cancellation filter system 753, rather than the noisy input signal 752 from the input (source) 551. That is, the “clean” output signal from the noise cancellation filter system 753 is used by the noise reduction gain controller 755 to derive the noise reduction gain value (g2), and to generate the noise reduction output signal 758 (i.e., the system output signal, or “attenuated” output signal), in the third example solution of FIG. 7. Here, the noise reduction gain value (g2) represents the amount of distortion present in the clean output signal that is introduced by the noise cancellation filter system 753 and which is be removed (via the gain application), rather than representing the attenuation that is given to the noisy input signal 752 by the noise cancellation filter system 753 (like in the example of FIG. 5).

[0120] As noted above, FIG. 7 illustrates an example noise reduction gain controller 755 outputs an intermediate signal 756. It is to be appreciated that, in alternative embodiment, the gain controller output can be just the gain (gl) used in the gain application block (no need for an intermediate signal). In such examples, the gain application would then apply the gain to the noisy input signal 752.

[0121] As noted, the third example solution is similar to the second example solution, in that a body noise reduction (BNR) algorithm can be used together with a body noise cancellation (BNC) approach to achieve lower distortion at the system output, and in that the BNR gain is derived from the clean BNC output signal levels and the noisy input microphone signal levels. However, the third example solution differs from the second example solution in that the attenuation is applied to the output of the body noise cancellation fdter system (the clean BNC output signal) rather than the to the noisy microphone input signal, Mic. Stated differently, in Solution 2 the noisy signal phase is used at the output, whereas here the clean signal phase is used.

[0122] Here, the BNR gain, g, is applied only to attenuate the distortion that is already present in the clean BNC output signal, Clean'. gdB= min ((—cleanLevelsdBk+ micLevelsdBk), 0 dB)

[0123] where micLevelsdBand cleanLevelsdBare the magnitude or power spectrum of the “noisy” input microphone signal (Mic) and the “clean” BNC output signal (Clean), respectively. Contrary to the previous embodiment, the BNR gains (g) do not represent the attenuation given by the BNC filter, but rather the amount distortion present in the clean BNC output signal (Clean), which needs to be removed via the gain application. As noted above, the use of OdB is illustrative and other embodiments could use another small gain value (e.g., 3dB).

[0124] The BNR output signal, Out, corresponds to the clean BNC output signal (Clean), as attenuated by the BNR gains g (expressed below as gain factors instead of dB):

[0125] This implies that the “magnitude” of the BNR output signal, Out, when using both the BNC approach and the BNR algorithm is the same as the “magnitude” of the clean BNC output signal, Clean, when the BNC filter is attenuating the noisy input microphone signal, Mic, asintended (GNR= 1 when \CleanFFT\ < |MtcFFr|). However, when the BNC filter has introduced distortions ( | CleanFFT| > \MicFFT|), the magnitude of the clean BNC output signal (Clean) gets attenuated by the gain application (g). such that the magnitude of the BNR output signal (Out) does not exceed the magnitude of the original noisy input microphone signal (Mic).

[0126] This example embodiment is similar to the previous embodiment, in that both will output the same final output signal “magnitude.” This example embodiment is different from the previous embodiment, however, in that the third example solution allows the clean “phase” of the output signal to be maintained. This is an advantage for acoustic devices or hearing aids, where the processed audio needs to be eventually resynthesised, but not necessary for certain cochlear implants.

[0127] FIG. 8 is a flowchart illustrating an example method 800 according to the third example embodiment. The method 800 can be implemented using the arrangement shown in FIG. 7, for example. At operation 810, method 800 includes receiving at least one input signal. At operation 820, method 800 includes processing the at least one input signal with a noise cancellation system configured to apply noise cancellation filtering to the at least one input signal to generate a noise cancellation output signal. At operation 830, method 800 includes processing the noise cancellation output signal with a noise reduction system configured to apply noise reduction gains to the noise cancellation output signal to generate a noise reduction output signal. The noise reduction gains are a function of the at least one input signal and the noise cancellation output signal, for example.

[0128] In some examples, the method 800 further includes determining the noise reduction gains based on the at least one input signal and the noise cancellation output signal. In this example embodiment, applying the noise reduction gains to the at least one input signal at operation 830 is operable to attenuate distortions present in the noise cancellation output signal.

[0129] In some examples, the at least one input signal is a sound signal, and the method 800 further includes using the noise reduction output signal to generate a stimulation signal representative of the sound signal. In some examples, the noise cancellation system is a body noise cancellation system, and the noise reduction system is a distortion noise reduction system.

[0130] Thus, the techniques described above with reference to FIGs. 7 and 8 can be used to remove or reduce distortion introduced by a noise cancellation filtering scheme by dynamically adjusting gain values to apply attenuation to the noise cancellation output signal to generate anoise reduction output signal, and this noise reduction output signal can be used as a system output signal to generate a stimulation signal representing the at least one input signal.

[0131] It is noted that the three example solutions described above with reference to FIGs. 3A- 3B and FIGs. 4A-4B, FIGs. 5 and 6, and FIG.s 7 and 8, respectively, are not mutually exclusive, and thus can be combined in different ways. One example in which the second example solution of FIGs. 5 and 6 and the second example solution of FIGs. 7 and 8 can be combined is described below with reference to FIG. 9.

[0132] FIG. 9 is a flowchart illustrating another method 900 according to another example embodiment. The method 900 can be implemented using the arrangement of FIG. 5 and / or FIG. 7, for example. At operation 910, method 900 includes receiving at least one input signal at a noise cancellation system. At operation 920, method 900 includes processing the at least one input signal by using a noise cancellation filter to generate a noise cancellation output signal. At operation 930, method 900 includes receiving the at least one input signal and the noise cancellation output signal at a noise reduction system. At operation 940, method 900 includes selectively processing one of the at least one input signal or the noise cancellation output signal by applying noise reduction gains to one of the at least one input signal or the noise cancellation output signal to generate a noise reduction output signal.

[0133] It is be appreciated that solution 1 becomes a frequency-domain approach (as Solution 2 and 3) when alpha is tuned per band, as mentioned above. As such, in certain examples, it is possible to combine Solutions 1, 2, and 3 within a same operable system. As such, in one example, the operations to selectively process one of the at least one input signal or the noise cancellation output signal by applying noise reduction gains to one of the at least one input signal or the noise cancellation output signal to generate a noise reduction output signal comprises: processing the at least one input signal to generate a noise cancellation output signal using a variable filtering mixing parameter that is a function of a level of the at least one input signal.

[0134] In certain embodiments, the noise reduction system includes a gain controller configured to determine the noise reduction gains based on the at least one input signal and the noise cancellation output signal. The noise cancellation system is configured to process the at least one input signal using the noise cancellation filter to reduce or remove one or more of body noise, feedback, distortions, echo, etc. from the at least one input signal when generating the noise cancellation output signal, for example.

[0135] In some examples, the noise reduction system is configured to selectively process the at least one input signal by applying the noise reduction gains to the at least one input signal, via the gain controller, to attenuate one or more of body noise, distortion, feedback, or echo present in the at least one input signal when generating the noise reduction output signal. For example, the noise reduction system is configured to apply the noise reduction gains to the at least one input signal, via the gain controller, to generate the noise reduction output signal when the noise cancellation filter introduces distortions in the noise cancellation output signal. In such examples, the noise reduction gains determined by the gain controller represent attenuation applied to the at least one input signal by the noise cancellation filter to reduce or remove noise present in the at least one input signal when generating the noise cancellation output signal.

[0136] In some other examples, the noise reduction system is configured to selectively process the noise cancellation output signal by applying the noise reduction gains to the noise cancellation output signal, via the gain controller, to attenuate one or more of body noise, feedback, distortions, echo, etc. present in the noise cancellation output signal when generating the noise reduction output signal. For example, the noise reduction gains determined by the gain controller represent an amount of distortion present in the noise cancellation output signal that is introduced by the noise cancellation filter and is to be reduced or removed when generating the noise cancellation output signal.

[0137] In some examples, the at least one input signal is a sound signal, and the method 900 can further include generating at least one stimulation signal representative of the sound signal using the noise reduction output signal, instead of the noise cancellation output signal, via a stimulator unit.

[0138] Thus, the techniques presented herein and described above with reference to several example solutions can either: (1) make adjustments to a variable noise cancellation filtering strength parameter with respect to the noise cancellation filter system, (2) perform noise reduction via gain application, instead of noise cancellation via adaptive filtering / phase cancellation, and / or (3) perform noise cancellation followed by noise reduction (gain application after adaptive filtering / phase cancellation). As noted, the three example solutions described above are not mutually exclusive, and thus can be combined in various different ways. There exist specific advantages and disadvantages of employing each one of the three specific solutions as detailed above. For example, the second example solution is may better suited or cochlear implants, since it allows for improved battery consumption and longevity,whereas the first example solution and the third example solution may be better suited for acoustic devices and hearing aids, since these solutions maintain all the benefits of phase cancellation of conventional algorithms. In some instances, the noise reduction (gain application) techniques presented herein have demonstrated a reduction in the output noise floor of up 10 dB compared to a conventional noise cancellation filter system.

[0139] The techniques described herein allow the same noise cancellation performance of conventional systems to be maintained, while reducing or avoiding unwanted distortions, such as the typical noise floor increase introduced by the adaptive filtering of a noise cancellation filter system when the noise is not present (silence) or when the noise estimate is inaccurate. These example solutions translate to improved sound quality and potential improvements in speech intelligibility at soft levels, especially for devices with implantable microphones where the noise floor is already high compared to with external microphones and where the noise reference signal can contain nonlinearities. Another notable distinction from conventional noise cancellation techniques is that the noise reduction system and techniques described herein aim at removing or avoiding noise cancellation distortions altogether, and calculate the gain to be applied directly from the noisy input signal from the microphone and the clean output signal from the noise cancellation filter, without the need to estimate a signal-to-noise ratio (i.e., without using the SNR value between speech and noise references for the gain mask calculation).

[0140] As previously described, the technology disclosed herein can be applied in any of a variety of circumstances and with a variety of different devices. Example devices that can benefit from technology disclosed herein are described in more detail in FIG. 10. The techniques of the present disclosure can be applied to other devices, such as neurostimulators, cardiac pacemakers, cardiac defibrillators, sleep apnea management stimulators, seizure therapy stimulators, tinnitus management stimulators, and vestibular stimulation devices, as well as other medical devices that deliver stimulation to tissue. Further, technology described herein can also be applied to consumer devices. These different systems and devices can benefit from the technology described herein.

[0141] FIG. 10 illustrates an example vestibular stimulator system 1002, with which embodiments presented herein can be implemented. As shown, the vestibular stimulator system 1002 comprises an implantable component (vestibular stimulator) 1012 and an external device 1004 (e.g., external processing device, external component, battery charger, remote control, etc.). The external device 1004 comprises a transceiver unit 1060. As such, theexternal device 1004 is configured to transfer data (and potentially power) to the vestibular stimulator 1012.

[0142] The vestibular stimulator 1012 comprises an implant body (main module) 1034, a lead region 1036, and a stimulating assembly 1016, all configured to be implanted under the skin / tissue (tissue) 1015 of the recipient. The implant body 1034 generally comprises a hermetically-sealed housing 1038 in which RF interface circuitry, one or more rechargeable batteries, one or more processors, and a stimulator unit are disposed. The implant body 1034 also includes an intemal / implantable coil 1014 that is generally external to the housing 1038, but which is connected to the transceiver via a hermetic feedthrough (not shown).

[0143] The stimulating assembly 1016 comprises a plurality of electrodes 1044( l)-(3) disposed in a carrier member (e.g., a flexible silicone body). In this specific example, the stimulating assembly 1016 comprises three (3) stimulation electrodes, referred to as stimulation electrodes 1044(1), 1044(2), and 1044(3). The stimulation electrodes 1044(1), 1044(2), and 1044(3) function as an electrical interface for delivery of electrical stimulation signals to the recipient’s vestibular system.

[0144] The stimulating assembly 1016 is configured such that a surgeon can implant the stimulating assembly adjacent the recipient’s otolith organs via, for example, the recipient’s oval window. It is to be appreciated that this specific embodiment with three stimulation electrodes is merely illustrative and that the techniques presented herein can be used with stimulating assemblies having different numbers of stimulation electrodes, stimulating assemblies having different lengths, etc.

[0145] In operation, the vestibular stimulator 1012, the external device 1004, and / or another external device, can be configured to implement the techniques presented herein. That is, the vestibular stimulator 1012, possibly in combination with the external device 1004 and / or another external device, can include an evoked biological response analysis system, as described elsewhere herein.

[0146] As should be appreciated, while particular uses of the technology have been illustrated and discussed above, the disclosed technology can be used with a variety of devices in accordance with many examples of the technology. The above discussion is not meant to suggest that the disclosed technology is only suitable for implementation within systems akin to that illustrated in the figures. In general, additional configurations can be used to practicethe processes and systems herein and / or some aspects described can be excluded without departing from the processes and systems disclosed herein.

[0147] This disclosure described some aspects of the present technology with reference to the accompanying drawings, in which only some of the possible aspects were shown. Other aspects can, however, be embodied in many different forms and should not be construed as limited to the aspects set forth herein. Rather, these aspects were provided so that this disclosure was thorough and complete and fully conveyed the scope of the possible aspects to those skilled in the art.

[0148] As should be appreciated, the various aspects (e.g., portions, components, etc.) described with respect to the figures herein are not intended to limit the systems and processes to the particular aspects described. Accordingly, additional configurations can be used to practice the methods and systems herein and / or some aspects described can be excluded without departing from the methods and systems disclosed herein.

[0149] According to certain aspects, systems and non-transitory computer readable storage media are provided. The systems are configured with hardware configured to execute operations analogous to the methods of the present disclosure. The one or more non-transitory computer readable storage media comprise instructions that, when executed by one or more processors, cause the one or more processors to execute operations analogous to the methods of the present disclosure.

[0150] Similarly, where steps of a process are disclosed, those steps are described for purposes of illustrating the present methods and systems and are not intended to limit the disclosure to a particular sequence of steps. For example, the steps can be performed in differing order, two or more steps can be performed concurrently, additional steps can be performed, and disclosed steps can be excluded without departing from the present disclosure. Further, the disclosed processes can be repeated.

[0151] Although specific aspects were described herein, the scope of the technology is not limited to those specific aspects. One skilled in the art will recognize other aspects or improvements that are within the scope of the present technology. Therefore, the specific structure, acts, or media are disclosed only as illustrative aspects. The scope of the technology is defined by the following claims and any equivalents therein.

[0152] It is also to be appreciated that the embodiments presented herein are not mutually exclusive and that the various embodiments can be combined with another in any of a number of different manners.

Claims

CLAIMSWhat is claimed is:

1. A method, comprising: receiving at least one input signal at a noise cancellation system; and processing the at least one input signal using the noise cancellation system to generate a noise cancellation output signal, wherein the noise cancellation system is controlled by a variable filtering strength parameter that is a function of a level of the at least one input signal.

2. The method of claim 1, wherein processing the at least one input signal using the noise cancellation system comprises: selectively adjusting the variable filtering strength parameter to at least one of limit or disable noise cancellation filtering in response to determining that the noise cancellation system is expected to add distortions to the at least one input signal when generating the noise cancellation output signal.

3. The method of claim 2, wherein selectively adjusting the variable filtering strength parameter comprises: decreasing a value of the variable filtering strength parameter to reduce strength of the noise cancellation filtering as the at least one input signal approaches at least one of a noise floor level or a saturation level.

4. The method of claim 3, wherein decreasing the value of the variable filtering strength parameter comprises: dynamically decreasing the value of the variable filtering strength parameter to reduce the strength of the noise cancellation filtering as a function of proximity of the level of the at least one input signal to the noise floor level.

5. The method of claim 3, wherein decreasing the value of the variable filtering strength parameter comprises:dynamically decreasing the value of the variable filtering strength parameter to reduce the strength of the noise cancellation fdtering as a function of proximity of the level of the at least one input signal to the saturation level.

6. The method of claim 2, wherein selectively adjusting the variable fdtering strength parameter comprises: setting a value of the variable fdtering strength parameter to zero to disable the noise cancellation fdtering when the at least one input signal reaches or exceeds at least one of a noise floor level or a saturation level.

7. The method of claim 1, 2, 3, 4, 5, or 6, wherein the at least one input signal is a sound signal.

8. The method of claim 1, 2, 3, 4, 5, or 6, further comprising: fdtering the at least one input signal to generate a plurality of fdtered input signals each associated with one of a plurality of frequency bands, wherein the variable fdtering strength parameter is chosen independently for each frequency band.

9. An apparatus comprising: a noise cancellation fdter configured to receive at least one input signal, and to process the at least one input signal to generate a noise cancellation output signal; and a controller configured to: determine, based on the at least one input signal, whether the noise cancellation fdter is expected to add distortions to the at least one input signal when generating the noise cancellation output signal; and selectively control the noise cancellation fdter in response to determining that the noise cancellation fdter is expected to add distortions.

10. The apparatus of claim 9, wherein the noise cancellation fdter operates in accordance with a variable fdtering strength parameter, and wherein the controller is configured to: selectively adjust the variable fdtering strength parameter to control the noise cancellation fdter in response to determining that the noise cancellation fdter is expected to add distortions.

11. The apparatus of claim 9 or 10, wherein the variable filtering strength parameter is a function of a level of the at least one input signal.

12. The apparatus of claim 11, wherein, to determine whether the noise cancellation filter is expected to add distortions, the controller is configured to: monitor the level of the at least one input signal in relation to at least one of a noise floor level or a saturation level.

13. The apparatus of claim 12, wherein the controller is configured to: selectively adjust the variable filtering strength parameter when the at least one input signal is approaching, at, or below the noise floor level; and selectively adjust the variable filtering strength parameter when the at least one input signal is approaching, at, or above the saturation level.

14. The apparatus of claim 13, wherein, to selectively adjust the variable filtering strength parameter to control the noise cancellation filter, the controller is configured to: dynamically decrease a value of the variable filtering strength parameter to reduce strength of the noise cancellation filter as the at least one input signal approaches at least one of the noise floor level or the saturation level.

15. The apparatus of claim 13, wherein, to selectively adjust the variable filtering strength parameter to control the noise cancellation filter, the controller is configured to: set a value of the variable filtering strength parameter to zero to disable the noise cancellation filter when the at least one input signal reaches or exceeds at least one of the noise floor level or the saturation level.

16. The apparatus of claim 9 or 10, wherein the at least one input signal is a sound signal.

17. A method, comprising: receiving at least one input signal; processing the at least one input signal with a noise cancellation system configured to apply noise cancellation filtering to the at least one input signal to generate a noise cancellation output signal; andprocessing the at least one input signal with a noise reduction system, wherein the noise reduction system is configured to apply noise reduction gains to the at least one input signal to generate a noise reduction output signal.

18. The method of claim 17, wherein the noise reduction gains are a function of the at least one input signal and the noise cancellation output signal.

19. The method of claim 17, further comprising: determining the noise reduction gains based on the at least one input signal and the noise cancellation output signal.

20. The method of claim 17, wherein applying the noise reduction gains to the at least one input signal is operable to attenuate noise and distortion present in the at least one input signal.

21. The method of claim 17, wherein the at least one input signal is a sound signal, the method further comprising: using the noise reduction output signal, instead of the noise cancellation output signal, to generate a stimulation signal representative of the sound signal.

22. The method of claim 17, 18, 19, 20, or 21, wherein the noise cancellation system is a body noise cancellation system, and the noise reduction system is a body noise reduction system.

23. A method, comprising: receiving at least one input signal; processing the at least one input signal with a noise cancellation system configured to apply noise cancellation filtering to the at least one input signal to generate a noise cancellation output signal; andprocessing the noise cancellation output signal with a noise reduction system, wherein the noise reduction system is configured to apply noise reduction gains to the noise cancellation output signal to generate a noise reduction output signal.

24. The method of claim 23, wherein the noise reduction gains are a function of the at least one input signal and the noise cancellation output signal.

25. The method of claim 23, further comprising: determining the noise reduction gains based on the at least one input signal and the noise cancellation output signal.

26. The method of claim 23, wherein applying the noise reduction gains to the noise cancellation output signal is operable to attenuate distortions present in the noise cancellation output signal.

27. The method of claim 23, wherein the at least one input signal is a sound signal, the method further comprising: using the noise reduction output signal to generate a stimulation signal representative of the sound signal.

28. The method of claim 23, 24, 25, 26, or 27, wherein the noise cancellation system is a body noise cancellation system, and the noise reduction system is a distortion noise reduction system.

29. A system, comprising: a noise cancellation system configured to: receive at least one input signal; and process the at least one input signal by using a noise cancellation filter to generate a noise cancellation output signal; and a noise reduction system configured to: receive the at least one input signal and the noise cancellation output signal;selectively process one of the at least one input signal or the noise cancellation output signal by applying noise reduction gains to one of the at least one input signal or the noise cancellation output signal to generate a noise reduction output signal.

30. The system of claim 29, wherein to selectively process one of the at least one input signal or the noise cancellation output signal by applying noise reduction gains to one of the at least one input signal or the noise cancellation output signal to generate a noise reduction output signal comprises: processing the at least one input signal to generate a noise cancellation output signal using a variable filtering mixing parameter that is a function of a level of the at least one input signal.

31. The system of claim 29 or 30, wherein the noise reduction system includes a gain controller configured to determine the noise reduction gains based on the at least one input signal and the noise cancellation output signal.

32. The system of claim 31, wherein the noise cancellation system is configured to process the at least one input signal using the noise cancellation filter to reduce or remove one or more of body noise, feedback, or echo from the at least one input signal when generating the noise cancellation output signal.

33. The system of claim 32, wherein the noise reduction system is configured to selectively process the at least one input signal by applying the noise reduction gains to the at least one input signal, via the gain controller, to attenuate one or more of body noise, feedback, or echo present in the at least one input signal when generating the noise reduction output signal.

34. The system of claim 33, wherein the noise reduction system is configured to apply the noise reduction gains to the at least one input signal, via the gain controller, to generate the noise reduction output signal when the noise cancellation filter introduces distortions in the noise cancellation output signal.

35. The system of claim 33, wherein the noise reduction gains determined by the gain controller represent attenuation applied to the at least one input signal by the noisecancellation filter to reduce or remove noise present in the at least one input signal when generating the noise cancellation output signal.

36. The system of claim 32, wherein the noise reduction system is configured to selectively process the noise cancellation output signal by applying the noise reduction gains to the noise cancellation output signal, via the gain controller, to attenuate distortions present in the noise cancellation output signal when generating the noise reduction output signal.

37. The system of claim 36, wherein the noise reduction gains determined by the gain controller represent an amount of distortions present in the noise cancellation output signal that are introduced by the noise cancellation filter and are to be removed when generating the noise cancellation output signal.

38. The system of claim 30, wherein the at least one input signal is a sound signal, the system further comprising: a stimulator unit configured to generate at least one stimulation signal representative of the sound signal using the noise reduction output signal, instead of the noise cancellation output signal.

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