An automated EP analysis apparatus for monitoring, detecting and identifying changes (adverse or recovering) to a physiological system generating the analyzed EPs, wherein the apparatus is adapted to characterize and classify EPs and create alerts of changes (adverse or recovering) to the physiological systems generating the EPs if the acquired EP waveforms change significantly in latency, amplitude or morphology.

A method of surgically positioning an electrode array at a desired implantation location relative to a nerve. A temporary probe electrode is temporarily positioned adjacent to the nerve and at a location which is caudorostrally separate to the desired implantation location of the electrode array. The implanted position of the probe electrode is temporarily fixed relative to the nerve. During implantation of the electrode array, electrical stimuli are applied from one of the temporarily fixed probe electrode and the electrode array, to evoke compound action potentials on the nerve. Compound action potentials evoked by the stimuli are sensed from at least one electrode of the other of the temporarily fixed probe electrode and the electrode array. From the sensed compound action potentials a position of the electrode array relative to the nerve is determined.

A method of surgically positioning an electrode array at a desired implantation location relative to a nerve. A temporary probe electrode is temporarily positioned adjacent to the nerve and at a location which is caudorostrally separate to the desired implantation location of the electrode array. The implanted position of the probe electrode is temporarily fixed relative to the nerve. During implantation of the electrode array, electrical stimuli are applied from one of the temporarily fixed probe electrode and the electrode array, to evoke compound action potentials on the nerve. Compound action potentials evoked by the stimuli are sensed from at least one electrode of the other of the temporarily fixed probe electrode and the electrode array. From the sensed compound action potentials a position of the electrode array relative to the nerve is determined.

The present invention discloses a real-time ultrasonic stimulation electric signal recording chip and a preparation method thereof, where the preparation method includes the following steps: S1 manufacturing an interdigital electrode on a piezoelectric substrate to obtain a surface acoustic wave chip, and manufacturing a recording electrode and an electrode lead; S2, manufacturing an insulation protection layer on the chip obtained in the S1, and processing the insulation protection layer to form the recording electrode, so as to obtain a chip combining the interdigital electrode and the recording electrode; S3, preparing a PDMS cavity; and S4, bonding the PDMS cavity prepared in the S3 and the chip obtained in the S2. In the present invention, combining the interdigital electrode generating a surface acoustic wave ultrasound with a multi-channel recording electrode, such that real-time recording of a multi-channel electric signal under ultrasonic stimulation is achieved.

Disclosed is a neurostimulation system comprising an implantable device for controllably delivering a neural stimulus, and a processor. Signals evoked by a stimulus are sensed at each pair of sense electrodes, each sensed signal including a differential evoked compound action potential (ECAP) evoked by the delivered neural stimulus. The differential ECAP is decomposed in each sensed signal into a first single-ended ECAP corresponding to one sense electrode of the pair of sense electrodes and a second single-ended ECAP corresponding to the other sense electrode of the pair of sense electrodes. ECAP propagation model parameters are determined from the first single-ended ECAP model and the second single-ended ECAP model and from distances of the respective sense electrodes from the stimulus electrode configuration. An indication may be given to a user if one of the one or more ECAP propagation model parameters departs from a predetermined range. Or, originating ECAP model parameters may be determined from the first single-ended ECAP model and from the distance of the corresponding sense electrode from the stimulus electrode configuration. Parameters of a model of a differential ECAP at a second pair of sense electrodes may be computed: and an optimal combination of parameters for a parametric ECAP detector at the second pair of sense electrodes may be computed from the parameters of the model of the differential ECAP.

Disclosed is a neurostimulation system comprising an implantable device for controllably delivering a neural stimulus, and a processor. Signals evoked by a stimulus are sensed at each pair of sense electrodes, each sensed signal including a differential evoked compound action potential (ECAP) evoked by the delivered neural stimulus. The differential ECAP is decomposed in each sensed signal into a first single-ended ECAP corresponding to one sense electrode of the pair of sense electrodes and a second single-ended ECAP corresponding to the other sense electrode of the pair of sense electrodes. ECAP propagation model parameters are determined from the first single-ended ECAP model and the second single-ended ECAP model and from distances of the respective sense electrodes from the stimulus electrode configuration. An indication may be given to a user if one of the one or more ECAP propagation model parameters departs from a predetermined range. Or, originating ECAP model parameters may be determined from the first single-ended ECAP model and from the distance of the corresponding sense electrode from the stimulus electrode configuration. Parameters of a model of a differential ECAP at a second pair of sense electrodes may be computed: and an optimal combination of parameters for a parametric ECAP detector at the second pair of sense electrodes may be computed from the parameters of the model of the differential ECAP.

Systems and methods for enhancing diagnostic evoked potential recordings of a nerve or nerve pathway of interest. A grid array of stimulating electrodes are placed on, over, or through skin in a location beneath which a nerve or nerve pathway is suspected to lie. A stimulator controls the grid array, where each electrode is independently controllable as active or inactive, as a cathode or anode, etc. A plurality of recording electrodes may record Somato-Sensory Evoked Potentials (SSEPs) and/or Transcranial Electrical Motor Evoked Potentials (TCeMEP) in response to activation of the stimulating electrodes. A processor controls stimulating the stimulating electrodes, and receives responses from the recording electrodes, in a general search mode and a focused search mode in order to use a minimum stimulation intensity at which a maximum response amplitude is detected to continually stimulate the nerve or the nerve pathway.

Methods and systems for providing closed loop control of stimulation provided by an implantable stimulator device are disclosed herein. The disclosed methods and systems use a neural feature prediction model to predict a neural feature, which is used as a feedback control variable for adjusting stimulation. The predicted neural feature is determined based on one or more signals from an accelerometer configured in contact with the patient. The disclosed methods and systems can be used to provide closed loop feedback in situations, such as sub-perception therapy, when neural features cannot be readily directly measured.

Methods and systems for providing closed loop control of stimulation provided by an implantable stimulator device are disclosed herein. The disclosed methods and systems use a neural feature prediction model to predict a neural feature, which is used as a feedback control variable for adjusting stimulation. The predicted neural feature is determined based on one or more signals from an accelerometer configured in contact with the patient. The disclosed methods and systems can be used to provide closed loop feedback in situations, such as sub-perception therapy, when neural features cannot be readily directly measured.

Techniques for non-invasively controlling targeted neural activity of a subject are provided herein. The techniques include applying a stimulus input to the subject, the stimulus input being formed by a deep artificial neural network (ANN) model and being configured to elicit targeted neural activity within a brain of the subject. The stimulus input may be a pattern of luminous power generated by the deep ANN model and applied to retinae of the subject. The stimulus input may be generated by the deep ANN model based on a mapping of the subject's neural responses to neurons of the deep ANN model.