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: 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: 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: Implantable medical devices and instruments (tools) including one or more implantable sensors. In certain embodiments, a hearing prosthesis comprises an implantable stimulating assembly configured to be implanted in a recipient's cochlea. At least one implantable sensor is disposed in the implantable stimulating assembly and is configured to monitor an insertion attribute.

Abstract: A cochlear prosthesis comprising an electrical signal analyser configured to process a first frequency sub-range of a detected sound signal for electric stimulation of the cochlea, and a delay circuit configured to impose a delay on at least one of an electrical signal delivery path and an acoustic signal delivery path, to provide for delivery of the electrical stimulation to the cochlea at a desired time relative to a time of arrival of acoustic stimuli at the cochlea, wherein the acoustic stimuli arriving at the cochlea and the electrical stimulation delivered to the cochlea at the desired time substantially simultaneously stimulate the cochlea.

Abstract: An embodiment of the present invention takes masking effects into consideration when determining stimulation signals for neural stimulation. These masking effects may be modeled using user-specific models determined by taking measurements for an implant system of an implant recipient. Or, the model may correspond to a group of individuals sharing a common characteristic or the population as a whole. These models may be, for example, psycho-physical models.

Abstract: A bimodal hearing prosthesis configured to deliver electrical and acoustic stimulation to a recipient such that a frequency range of a received sound that is represented by the electrical stimulation is perceived simultaneously with the frequency range of the received sound that is represented by the acoustic stimulation.

Abstract: An embodiment of the present invention takes masking effects into consideration when determining stimulations signals for neural stimulation. These masking effects may be modeled using user-specific models determined by taking measurements for an implant system of an implant recipient. Or, the model may correspond to a group of individuals sharing a common characteristic or the population as a whole. These models may be, for example, psycho-physical or electrophysiological models.

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: A method for stimulating nerve or tissue fibers and a prosthetic hearing device implanting same. The method comprises: generating a stimulation signal comprising a plurality of pulse bursts each comprising a plurality of pulses; and distributing said plurality of pulse bursts across one or more electrodes each operatively coupled to nerve or tissue fibers such that each of said plurality of pulse bursts delivers a charge to said nerve or tissue fibers to cause dispersed firing in said nerve or tissue fibers.

Abstract: A method for stimulating nerve or tissue fibers and a prosthetic hearing device implanting same. The method comprises: generating a stimulation signal comprising a plurality of pulse bursts each comprising a plurality of pulses; and distributing said plurality of pulse bursts across one or more electrodes each operatively coupled to nerve or tissue fibers such that each of said plurality of pulse bursts delivers a charge to said nerve or tissue fibers to cause dispersed firing in said nerve or tissue fibers.

Abstract: A bimodal hearing prosthesis configured to deliver electrical and acoustic stimulation to a recipient such that a frequency range of a received sound that is represented by the electrical stimulation is perceived simultaneously with the frequency range of the received sound that is represented by the acoustic stimulation.

Abstract: An embodiment of the present invention takes masking effects into consideration when determining stimulation signals for neural stimulation. These masking effects may be modeled using user-specific models determined by taking measurements for an implant system of an implant recipient. Or, the model may correspond to a group of individuals sharing a common characteristic or the population as a whole. These models may be, for example, psycho-physical models.

Abstract: A method for stimulating nerve or tissue fibers and a prosthetic hearing device implanting same. The method comprises: generating a stimulation signal comprising a plurality of pulse bursts each comprising a plurality of pulses; and distributing said plurality of pulse bursts across one or more electrodes each operatively coupled to nerve or tissue fibers such that each of said plurality of pulse bursts delivers a charge to said nerve or tissue fibers to cause dispersed firing in said nerve or tissue fibers.

Abstract: An embodiment of the present invention takes masking effects into consideration when determining stimulations signals for neural stimulation. These masking effects may be modeled using user-specific models determined by taking measurements for an implant system of an implant recipient. Or, the model may correspond to a group of individuals sharing a common characteristic or the population as a whole. These models may be, for example, psycho-physical or electrophysiological models.