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: The present application discloses systems and methods for distributed processing of electrophysiological signals. The system may include a processor, a remote device, and an implant comprising an array of electrodes. The method may comprise the processor receiving an electrophysiological signal request from the remote device that specifies at least one electrode at the implant from which to receive an electrophysiological signal, transmitting to the implant instructions to apply a plurality of stimuli via the specified at least one electrode and, for individual stimuli in the plurality of stimuli, recording an electrophysiological signal component resulting from the stimulus. The method may also comprise the processor combining the recorded individual electrophysiological signal components to produce the electrophysiological signal and transmitting the electrophysiological signal to the remote device for further processing.

Abstract: The present application discloses systems and methods for distributed processing of electrophysiological signals. The system may include a processor, a remote device, and an implant comprising an array of electrodes. The method may comprise the processor receiving an electrophysiological signal request from the remote device that specifies at least one electrode at the implant from which to receive an electrophysiological signal, transmitting to the implant instructions to apply a plurality of stimuli via the specified at least one electrode and, for individual stimuli in the plurality of stimuli, recording an electrophysiological signal component resulting from the stimulus. The method may also comprise the processor combining the recorded individual electrophysiological signal components to produce the electrophysiological signal and transmitting the electrophysiological signal to the remote device for further processing.

Abstract: The present application discloses systems and methods for distributed processing of electrophysiological signals. The system may include a processor, a remote device, and an implant comprising an array of electrodes. The method may comprise the processor receiving an electrophysiological signal request from the remote device that specifies at least one electrode at the implant from which to receive an electrophysiological signal, transmitting to the implant instructions to apply a plurality of stimuli via the specified at least one electrode and, for individual stimuli in the plurality of stimuli, recording an electrophysiological signal component resulting from the stimulus. The method may also comprise the processor combining the recorded individual electrophysiological signal components to produce the electrophysiological signal and transmitting the electrophysiological signal to the remote device for further processing.

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: 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: 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: 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: A computer-implemented method for fitting a medical implant to a recipient, the medical implant being operative to stimulate a physiological system of the recipient over a plurality of stimulation channels. The method includes: determining, based on measurements, an initial stimulation profile for the plurality of stimulation channels; determining a representative stimulus level of the initial stimulation profile; determining a fitting stimulation profile by modifying the shape a shape of the initial stimulation based on the representative stimulus level profile; and configuring the medical implant according to the fitting stimulation profile.

Abstract: A method for determining a first set of one or more parameters for configuring a system, the method including evaluating a behavior of the system over a predetermined selection of parameter values for a second set of parameters, and deriving a first set of one or more parameters to configure the system based on the evaluated behavior of the system, wherein the number of parameters in the first set is less than the number of parameters in the second set.

Abstract: A method for determining a first set of one or more parameters for configuring a system, the method including evaluating a behavior of the system over a predetermined selection of parameter values for a second set of parameters, and deriving a first set of one or more parameters to configure the system based on the evaluated behavior of the system, wherein the number of parameters in the first set is less than the number of parameters in the second set.

Abstract: The present application discloses systems and methods for distributed processing of electrophysiological signals. The system may include a processor, a remote device, and an implant comprising an array of electrodes. The method may comprise the processor receiving an electrophysiological signal request from the remote device that specifies at least one electrode at the implant from which to receive an electrophysiological signal, transmitting to the implant instructions to apply a plurality of stimuli via the specified at least one electrode and, for individual stimuli in the plurality of stimuli, recording an electrophysiological signal component resulting from the stimulus. The method may also comprise the processor combining the recorded individual electrophysiological signal components to produce the electrophysiological signal and transmitting the electrophysiological signal to the remote device for further processing.

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: A method of fitting to a recipient a cochlear implant including a plurality of stimulation channels. The method comprises applying to at least one stimulation channel of the cochlear implant a first stimulus signal comprising a neural response component and a psychophysics signal component, automatically measuring a strength of an evoked compound action potential (ECAP) of the recipient evoked in response to the application of the neural response component of the first stimulus signal, and simultaneously providing to a user an indication of the automatically measured strength of the ECAP and a value of the applied psychophysics signal component.

Abstract: A method of fitting to a recipient a cochlear implant including a plurality of stimulation channels. The method comprises applying to at least one stimulation channel of the cochlear implant a first stimulus signal comprising a neural response component and a psychophysics signal component, automatically measuring a strength of an evoked compound action potential (ECAP) of the recipient evoked in response to the application of the neural response component of the first stimulus signal, and simultaneously providing to a user an indication of the automatically measured strength of the ECAP and a value of the applied psychophysics signal component.

Abstract: A method and system for fitting a medical implant to a recipient is disclosed. The medical implant is operative to stimulate a physiological system of the recipient over a plurality of stimulation channels. The method includes the steps of determining an initial stimulation profile for the plurality of stimulation channels and then determining a fitting stimulation profile by modifying the form or shape of the initial stimulation profile.

Abstract: A method for configuring a medical implant that stimulates a physiological system of a recipient of the medical implant is described where the medical implant includes at least one input configuration variable corresponding to a subjective characteristic of the physiological system. The configuration method includes measuring at least one physical characteristic of the physiological system to provide at least one objective physical measurement value and then determining the at least one input configuration variable to configure the medical implant by a predictive configuration model having as an input the at least one objective physical measurement value.

Abstract: Automatically analysing an evoked neural response. The method comprises: applying electrical stimulation to a target neural region at incrementally greater current levels beginning with an initial current level that is as close as possible to a typical threshold-NRT level; recording an NRT measurement of an auditory signal which generated by the target neural region in response to the stimulation; and utilizing a machine-learned expert system to predict whether the NRT measurement contains a neural response based on a plurality of features extracted from the auditory signal.

Abstract: The automatic measurement of evoked compound action potential (ECAP) thresholds of the auditory nerve; that is, a neural response, concurrently with the performance of psychophysics measurements of a prosthetic hearing implant recipient. During the fitting process, a stimulus signal comprising two components is applied to each stimulation channel. One signal component is configured to elicit an ECAP neural response, referred to herein as a neural response signal component. The other component is configured to elicit a response to a psychophysics stimulation, referred to herein as a psychophysics signal component. Indications of the psychophysics measurement and the concurrently obtained neural response measurements are provided to the user. For the psychophysics measurement, this includes the selected characteristics of the psychophysics signal component since the results of the applied stimulation is a recipient behavioral or auditory response.