A computer brain interface (CBI) device of an individual is self-calibrated. A neurostimulation test signal is generated based on a selected set of test signal parameters. The neurostimulation signal is applied to the afferent sensory nerve fibers to elicit a bioelectric response via a neurostimulation interface operably connected to or integrated with the CBI device. The neurostimulation interface senses the bioelectric responses of the stimulated afferent sensory nerve fibers. The CBI devices determines, based on the sensed bioelectric responses, whether an excitation behavior of the stimulated afferent sensory nerve fibers with respect to the neurostimulation interface has changed. When the excitation behavior has changed, a set of recalibrated neurostimulation signal parameters is determined based on the sensed bioelectric responses. The CBI device is operated using the recalibrated neurostimulation signal parameters to communicate information to the individual via neurostimulation of the afferent sensory nerve fibers.

A computer brain interface (CBI) device of an individual applies a burst sequence of stimulation pulses to afferent sensory nerve fibers to elicit a bioelectric response via a neurostimulation interface operably connected to or integrated with the CBI device. The neurostimulation interface senses the bioelectric responses of the stimulated afferent sensory nerve fibers. The CBI device derives, based on the sensed bioelectric responses, a neural excitability profile characterizing a non-linear, dynamic excitation behavior of the afferent sensory neurons corresponding to the applied sequence of stimulation pulses. At least one stimulation parameter of the current set of stimulation parameters is adjusted based on the derived excitability profile to obtain an updated set of stimulation parameters.

A spinal cord stimulator (SCS) system and method for placing SCS electrodes in a patient for spinal cord stimulation therapy. The SCS system includes a stimulator and a base unit. In conjunction with a machine learning (ML) block, the base unit includes an algorithm module to store and process algorithms for processing data received from recording electrodes placed in a patient's body. The recording electrodes send electromyography (EMG) data to the algorithm module. The algorithm module processes and sends the EMG data to a display device. The displayed data is used, by a surgeon, for lateralization of the SCS electrode. The SCS system further includes algorithms to adjust stimulation parameters related to SCS electrodes based upon the surgeon's workflow. Further, the SCS system allows manual modification of stimulation parameters based upon muscle responses and the EMG data from the recording electrodes.

Computer-implemented systems and methods for determining epidural spinal stimulation parameters that promote muscle activation use spectral analysis and machine learning techniques to characterize electromyography data.

Systems, devices, methods, and computer-readable media may use broad-range spectrophotometric analysis and/or other sensors to generate data from bodily fluids accessed via a fluid drain. These data may be utilized to analyze therapeutic efficacy, to enable early detection of complications, and to guide the clinical management of patients being treated with a fluid drain. Advantageously, these systems, devices, methods, and computer-readable media enable clinical patient care decisions to be performed in a manner that is data-driven or quantitative in nature as opposed to qualitative—e.g., via well-defined, algorithmic-based processes and/or reliable methods. As a result, these systems, devices, methods, and computer-readable media enable improved clinical outcomes, more efficiently optimized medical care, and cost savings.

A system may include a neuromodulator and a processing system. The neuromodulator may be configured to be programmed with a set of more than one program to deliver neuromodulation. The processing system may be configured to: receive sensed data indicative of activity, motion and/or posture of a patient; analyze the activity, motion and/or posture of the patient; and perform a process, based on the analyzed activity, motion and/or posture, for switching from one program in the set of more than one program to another program from the set of more than one program. The process may include automatically implementing the other program from the set of more than one program or suggesting to switch to the other program from the set of more than one program.

In a method of neurological assessment, multichannel electromyography (EMG) data are acquired for an anatomical region. A pairwise EMG channel-EMG channel similarity matrix is generated from the acquired multichannel EMG data. Network analysis is performed on the similarity matrix to generate a network representing the similarity matrix. One or more metrics of the network are computed. One or more biomarkers are determined for the anatomical region based on the one or more metrics. In another method, EMG data are acquired using an electrode array contacting skin of a target anatomy, the EMG data are processed to produce reduced-dimensionality data; and time-invariant muscle synergies and corresponding time-varying activation functions are determined in the reduced-dimensionality data.

An access device for accessing an intervertebral disc having an outer shield comprising an access shield with a larger diameter (˜16-30 mm) that reaches from the skin down to the facet line, with an inner shield having a second smaller diameter (˜5-12 mm) extending past the access shield and reaches down to the disc level. This combines the benefits of the direct visual microsurgical/mini open approaches and the percutaneous, “ultra-MIS” techniques.

A neurostimulation system comprises at least one stimulation electrode configured to deliver an electrical stimulus to neural tissue and at least one measurement electrode configured to record a neural recording of a response of the neural tissue to the stimulus. A processor is configured to assess the neural recording to produce a measure of postsynaptic activation.

Methods and systems for programming stimulation parameters for an implantable medical device for neuromodulation, such as spinal cord stimulation (SCS) are disclosed. The stimulation parameters define user-configured waveforms having at least a first phase having a first polarity and a second phase having a second polarity, wherein the first and second phases are separated by an interphase interval (IPI). By delivering user-configured waveforms with different IPIs, stimulation geometry, and other waveform settings, therapeutic asynchronous activation of dorsal column fibers can be obtained.