The disclosure relates to a computer-implemented method for monitoring diaphragmatic response to phrenic nerve stimulation. The method comprises receiving in real-time a diaphragmatic CMAP signal. The method comprises computing a baseline value of a characteristic of the CMAP signal. The characteristic represents a diaphragmatic response intensity to a phrenic nerve stimulation. The method comprises determining a threshold value of the characteristic, representing a boundary of values of the characteristic indicative of upcoming diaphragmatic palsy. The determining of the threshold value includes shifting the baseline value. The method comprises receiving in real-time a ECG signal. The method comprises repeating in real-time: detecting a QRS complex in the ECG signal, monitoring the CMAP signal, computing a real-time value of the characteristic, comparing the real-time value to the threshold value, and outputting an alert when the threshold is passed. The real-time value of the characteristic is asynchronous to the QRS complex.

The embodiments include an apparatus used in combination with a computer for sensing biopotentials and electrode contact impedance. The apparatus includes a catheter in which there is a plurality of sensing electrodes, a corresponding plurality of local amplifiers, each coupled to one of the plurality of sensing electrodes, a data, control and power circuit coupled to the plurality of local amplifiers, and a photonic device bi-directionally communicating an electrical signal with the data, control and power circuit. An optical fiber optically communicated with the photonic device. The photonic device bi-directionally communicates an optical signal with the optical fiber. An optical interface device provides optical power to the optical fiber and thence to the photonic device and receives optical signals through the optical fiber from the photonic device. The optical interface device bi-directionally communicates electrical data, control, and power signal to the computer.

A method of manufacturing an optical fiber bundle cannula and a multi-channel fiber photometry system based on the optical fiber bundle cannula are provided. The method includes: manufacturing an optical fiber positioning mold and forming positioning holes on the mold; inserting first ends of optical fibers into the positioning holes respectively; fixing exposed portions of the optical fibers close to the mold to the mold using a curing material so that a relative position of ends of the optical fibers inserted into the mold remains unchanged; inserting second ends of the optical fibers into a tubular portion so that the optical fibers located between the tubular portion and the mold form an umbrella-shaped portion; fixing the umbrella-shaped portion and part of the tubular portion using a curing material, so as to form a fixing portion; and extracting the optical fibers from the mold.

A system and method for modeling patient-specific spinal cord stimulation (SCS) is disclosed. The system and method acquire impedance and evoked compound action potential (ECAP) signals from a lead positioned proximate to a spinal cord (SC). The lead includes at least one electrode. The system and method determine a patient-specific anatomical model based on the impedance and ECAP signals, and transform a dorsal column (DC) map template based on a DC boundary of the patient-specific anatomical model. Further, the system and method map the transformed DC map template to the patient-specific anatomical model. The system and method may also include the algorithms to solve extracellular and intracellular domain electrical fields and propagation along neurons. The system and method may also include the user interfaces to collect patient responses and compare with the patient-specific anatomical model as well as using the patient-specific anatomical model for guiding SCS programming.

A system and method for modeling patient-specific spinal cord stimulation (SCS) is disclosed. The system and method acquire impedance and evoked compound action potential (ECAP) signals from a lead positioned proximate to a spinal cord (SC). The lead includes at least one electrode. The system and method determine a patient-specific anatomical model based on the impedance and ECAP signals, and transform a dorsal column (DC) map template based on a DC boundary of the patient-specific anatomical model. Further, the system and method map the transformed DC map template to the patient-specific anatomical model. The system and method may also include the algorithms to solve extracellular and intracellular domain electrical fields and propagation along neurons. The system and method may also include the user interfaces to collect patient responses and compare with the patient-specific anatomical model as well as using the patient-specific anatomical model for guiding SCS programming.

A method for refining a nerve health assessment model used during surgical procedures, includes accessing a database storing historical patient data; analyzing the historical patient data to generate or update a predictive model configured to estimate at least one of: a predicted post-operative outcome, an individualized target range for an intraoperative nerve function parameter, or a statistical risk profile for surgical complications; obtaining current intraoperative nerve function measurements; receiving actual post-operative outcome data for the current patient; updating the database to include new patient data associated with the current patient; and refining the predictive model based at least in part on the new patient data added to the database.

A method for refining a nerve health assessment model used during surgical procedures, includes accessing a database storing historical patient data; analyzing the historical patient data to generate or update a predictive model configured to estimate at least one of: a predicted post-operative outcome, an individualized target range for an intraoperative nerve function parameter, or a statistical risk profile for surgical complications; obtaining current intraoperative nerve function measurements; receiving actual post-operative outcome data for the current patient; updating the database to include new patient data associated with the current patient; and refining the predictive model based at least in part on the new patient data added to the database.

Disclosed herein are a neural signal feedback system and method. The neural signal feedback system includes: a microelectrode array unit configured such that a plurality of microelectrodes is disposed on a substrate and such that one microelectrode, which is a reference electrode, and corresponding electrode groups including other microelectrodes located at different same distances from the reference electrode are set; and an analysis and determination unit configured to compare neural signal values, measured in the microelectrode array unit, with a preset reference value, and to determine whether to apply the electrical stimulation of the microelectrode array unit. The analysis and determination unit performs re-measurement after the application of electrical stimulation, and repeats the application of electrical stimulation and measurement until the measured values reach the reference value.

Disclosed herein are a neural signal feedback system and method. The neural signal feedback system includes: a microelectrode array unit configured such that a plurality of microelectrodes is disposed on a substrate and such that one microelectrode, which is a reference electrode, and corresponding electrode groups including other microelectrodes located at different same distances from the reference electrode are set; and an analysis and determination unit configured to compare neural signal values, measured in the microelectrode array unit, with a preset reference value, and to determine whether to apply the electrical stimulation of the microelectrode array unit. The analysis and determination unit performs re-measurement after the application of electrical stimulation, and repeats the application of electrical stimulation and measurement until the measured values reach the reference value.

A hybrid-type neural electrode is disclosed. The hybrid-type neural electrode comprises: a first layer including a bottom surface on which a planar electrode is arranged and a plurality of holes formed to penetrate vertically; and a second layer including a bottom surface on which a measurement device for measuring a neural signal is arranged while facing the top surface of the first layer.