Abstract: The invention is a method of automatically adjusting a visual prosthesis electrode array to the neural characteristics of an individual patient. By recording electrically evoked responses to a predetermined input stimulus, one can alter that input stimulus to the needs of an individual patient. A minimum input stimulus is applied to a patient, followed by recording an electrically evoked response to the input stimulus. By gradually increasing stimulus levels, one can determine the minimum input that creates a neural response, thereby identifying the threshold stimulation level. One can further determine a maximum level by increasing stimulus until a predetermined maximum neural response is obtained.

Abstract: The present disclosure provides a computer-implemented method for representing intensity levels indicative of a first type of sense of a subject (150) by parameter values for a different second type of sense of the subject (150). The method comprises determining (210) a first parameter value for the second type of sense representing a first intensity level indicative of the first type of sense; and determining (220) a second parameter value for the second type of sense representing a second intensity level indicative of the first type of sense with reference to the first parameter value, wherein the first parameter value differs from the second parameter value by at least one Just-Noticeable-Difference (JND) of the second type of sense of the subject (150).

Abstract: The invention is a method of automatically adjusting a retinal electrode array to the neural characteristics of an individual patient. By recording electrically evoked electroretinograms (eERG) to a predetermined input stimulus, one can alter that input stimulus to the needs of an individual patient. A minimum input stimulus is applied to a patient, followed by recording the eERG response to the input stimulus. By gradually increasing stimulus levels, one can determine the minimum input that creates a neural response, thereby identifying the threshold stimulation level. One can further determine a maximum level by increasing stimulus until a predetermined maximum neural response is obtained. However, eERG signals include a significant amount of noise. Applicants have developed novel techniques for artifact reduction and noise filtering to provide an accurate measure of neural activity.

Abstract: The present disclosure provides a computer-implemented method for representing intensity levels indicative of a first type of sense of a subject (150) by parameter values for a different second type of sense of the subject (150). The method comprises determining (210) a first parameter value for the second type of sense representing a first intensity level indicative of the first type of sense; and determining (220) a second parameter value for the second type of sense representing a second intensity level indicative of the first type of sense with reference to the first parameter value, wherein the first parameter value differs from the second parameter value by at least one Just-Noticeable-Difference (JND) of the second type of sense of the subject (150).