Abstract: Newly implanted cochlear implant recipients have highly individual and variable patterns of increasing tolerance and recognition of stimulus. Disclosed techniques include a series of self-administered fittings. During an initial clinical fitting, the recipient is given a basic map. Working at their own pace, the recipient can perform self-administered percept exercises that test the recipient's growing capacity to perceive stimulus quality. The results of the exercises are analyzed and compared with reference data. A clinical alert is generated when the recipients data pattern conforms to a predetermined criteria that indicates the recipient can benefit from a clinical visit because their performance is of a sufficiently stable nature. Optionally, the results of the exercises can be combined with trained clinical data, to make incremental map adjustments over time as the recipient is adapting to cochlear stimulation at their own pace.

Abstract: Presented herein are techniques to control the spread of current beyond, in an apical direction, a predetermined location/point in the cochlea. As a result, the techniques presented herein create a protected apical zone at an apical side of the predetermined location for undisturbed acoustic temporal coding (i.e., an apical region of the cochlea in which the voltage fields from delivered current signals are nulled, minimized, or otherwise controlled in order to eliminate, reduce, or otherwise limit electro-acoustic interactions that could negatively affect remaining low-frequency hair cells).

Abstract: Techniques for automatically analyzing neural activity within a target neural region. In one example, electrical stimulation is applied to the target neural region at an initial current level that approximates a typical threshold-Neural Response Telemetry (NRT) level. An NRT measurement of neural activity within the target neural region in response to the stimulation is recorded. A machine-learned expert system, which is configured with a decision tree that includes at least two levels of nodes which consider parameters relating to the NRT measurement, respectively, is utilized to predict, based on one or more features of the neural activity, whether the NRT measurement includes a neural response or does not include a neural response.

Abstract: A hearing prosthesis, including an implantable microphone, and a sound management system, wherein the hearing prosthesis is configured to set an operational parameter of the sound management system based on input from a microphone external to the recipient of the implantable microphone.

Abstract: Presented herein are techniques for providing tinnitus relief to recipients of a hearing prosthesis. In accordance with embodiments presented herein, a hearing prosthesis comprises a tinnitus relief system that is configured to generate a tinnitus masker signal that comprises a plurality of discrete (separate) components. The tinnitus relief system is configured to inject the components of the tinnitus masker signal directly into a sound processing path so that the masker components are combined with different processed portions of a channelized sound signal. The channelized sound signal and the components of the tinnitus masker signal are used to generate one or more output signals for use in compensation of a hearing loss of a recipient of the hearing prosthesis.

Abstract: A hearing prosthesis, including an implantable microphone, and a sound management system, wherein the hearing prosthesis is configured to set an operational parameter of the sound management system based on input from a microphone external to the recipient of the implantable microphone.

Abstract: Presented herein are excitation modeling and matching sound coding techniques that are configured to account for a recipient's estimated or predetermined neural response so as to improve a recipient's ability to perceive sound. More specifically, the techniques presented herein correlate a modeled excitation pattern with a target excitation pattern to generate a pattern of stimulation current configured to evoke an excitation pattern within the recipient's auditory system that approximates the target excitation pattern.

Abstract: Presented herein are techniques for providing tinnitus relief to recipients of a hearing prosthesis. In accordance with embodiments presented herein, a hearing prosthesis comprises a tinnitus relief system that is configured to generate a tinnitus masker signal that comprises a plurality of discrete (separate) components. The tinnitus relief system is configured to inject the components of the tinnitus masker signal directly into a sound processing path so that the masker components are combined with different processed portions of a channelized sound signal. The channelized sound signal and the components of the tinnitus masker signal are used to generate one or more output signals for use in compensation of a hearing loss of a recipient of the hearing prosthesis.

Abstract: Techniques for automatically analyzing neural activity within a target neural region. In one example, electrical stimulation is applied to the target neural region at an initial current level that approximates a typical threshold-Neural Response Telemetry (NRT) level. An NRT measurement of neural activity within the target neural region in response to the stimulation is recorded. A machine-learned expert system, which is configured with a decision tree that includes at least two levels of nodes which consider parameters relating to the NRT measurement, respectively, is utilized to predict, based on one or more features of the neural activity, whether the NRT measurement includes a neural response or does not include a neural response.

Abstract: Techniques for automatically analyzing neural activity within a target neural region. In one example, electrical stimulation is applied to the target neural region at an initial current level that approximates a typical threshold-Neural Response Telemetry (NRT) level. An NRT measurement of neural activity within the target neural region in response to the stimulation is recorded. A machine-learned expert system, which is configured with a decision tree that includes at least two levels of nodes which consider parameters relating to the NRT measurement, respectively, is utilized to predict, based on one or more features of the neural activity, whether the NRT measurement includes a neural response or does not include a neural response.

Abstract: A hearing prosthesis, including an implantable microphone, and a sound management system, wherein the hearing prosthesis is configured to set an operational parameter of the sound management system based on input from a microphone external to the recipient of the implantable microphone.

Abstract: The present application discloses systems and methods for detecting non-auditory nerve stimulation with an implant having a plurality of electrodes configured to electrically stimulate a target nerve of the implant recipient. One embodiment includes generating an electrical stimulation signal with a first set of electrodes of the implant, measuring a response to the electrical stimulation signal with a second set of electrodes of the implant, and determining whether the electrical stimulation signal stimulated at least one non-target nerve of the implant recipient based on the measured response.

Abstract: The present application discloses systems and methods for displaying and operating a user interface having one or more channel group controllers corresponding to one or more groups of hearing prosthesis channels. The hearing prosthesis may be configured to generate a plurality of signals via a plurality of channels based on a channel profile. The channel profile may define at least one intensity level for each channel. In operation, the user interface may be configured to instruct the hearing prosthesis to change the channel profile of the plurality of channels in response to receiving an input via one of the channel group controllers. The user interface may be used to fit a hearing prosthesis to a recipient. In one embodiment, an initial channel profile may be automatically determined, and the prosthesis channel profile may be adjusted by changing a representative intensity level corresponding to the channel profile.

Abstract: Presented herein are excitation modeling and matching sound coding techniques that are configured to account for a recipient's estimated or predetermined neural response so as to improve a recipient's ability to perceive sound. More specifically, the techniques presented herein correlate a modeled excitation pattern with a target excitation pattern to generate a pattern of stimulation current configured to evoke an excitation pattern within the recipient's auditory system that approximates the target excitation pattern.

Abstract: Techniques for automatically analyzing neural activity within a target neural region. In one example, electrical stimulation is applied to the target neural region at an initial current level that approximates a typical threshold-Neural Response Telemetry (NRT) level. An NRT measurement of neural activity within the target neural region in response to the stimulation is recorded. A machine-learned expert system, which is configured with a decision tree that includes at least two levels of nodes which consider parameters relating to the NRT measurement, respectively, is utilized to predict, based on one or more features of the neural activity, whether the NRT measurement includes a neural response or does not include a neural response.

Abstract: A tissue-stimulating prosthesis receives an input signal and determines a set of stimulation signals for use in generating electrical stimulation that will cause the recipient to perceive the input signal. The prosthesis determines a set of stimulation signals based on the perceptual power of at least one of the frequency components of the input signal or the perceptual power of one or more stimulation signals within the set.

Abstract: Automatically analyzing neural activity. The method comprises: applying electrical stimulation to a target neural region at an initial current level that approximates a typical threshold-Neural Response Telemetry (NRT) level; recording an NRT measurement of neural activity within the target neural region in response to the stimulation; and utilizing a machine-learned expert system to predict, based on one or more features of the neural activity, whether the NRT measurement contains a neural response.

Abstract: Controlling the interaction between an external device and an implanted device, including a method of controlling interaction between an external device and an implanted device, the method including at least the steps of: establishing communications between the implanted device and the external device; the external device determining an identification of the implant and comparing the identification with identifications in a stored list; if the device matches one of said identifications, then using a corresponding set of operating parameters to interact with said implant; and otherwise, not interacting with said device.

Abstract: Controlling the interaction between an external device and an implanted device, including a method of controlling interaction between an external device and an implanted device, the method including at least the steps of: establishing communications between the implanted device and the external device; the external device determining an identification of the implant and comparing the identification with identifications in a stored list; if the device matches one of said identifications, then using a corresponding set of operating parameters to interact with said implant; and otherwise, not interacting with said device.

Abstract: Controlling the interaction between an external device and an implanted device, including a method of controlling interaction between an external device and an implanted device, the method including at least the steps of: establishing communications between the implanted device and the external device; the external device determining an identification of the implant and comparing the identification with identifications in a stored list; if the device matches one of said identifications, then using a corresponding set of operating parameters to interact with said implant; and otherwise, not interacting with said device.