The disclosed apparatus, systems and methods relate to devices, systems and methods for intra-operative imaging.

A method includes receiving physiological data associated with a user during a sleep session. The method also includes determining a sleep-wake signal for the user during the sleep session based at least in part on the received physiological data. The method also includes determining one or more sleep-related parameters for the user during the sleep session based at least in part on the sleep-wake signal. The method also includes determining that the user experienced insomnia during the sleep session based at least in part on at least one of the one or more sleep-related parameters. The method also includes identifying a type for the insomnia experienced by the user based at least in part on the one or more sleep-related parameters.

A blood treatment machine includes a patient comfort feedback mechanism configured to be adjusted by a patient to indicate comfort levels of the patient. The machine is configured to adjust one or more treatment parameters based on the patient feedback.

A method for machine learning based artifact rejection is provided. The method may include applying a machine learning model to identify artefactual independent components in transcranial magnetic stimulation electroencephalogram data collected during a transcranial magnetic stimulation procedure. Clean transcranial magnetic stimulation electroencephalogram data is generated by removing, from the transcranial magnetic stimulation electroencephalogram data, the artefactual independent components. Real-time adjustments to parameters of the transcranial magnetic stimulation procedure may be performed based on the clean transcranial magnetic stimulation electroencephalogram data. Related systems and articles of manufacture, including computer program products, are also provided.

A method for uterine activity monitoring may include: acquiring a plurality of signals from a plurality of sensors during uterine activity; processing the plurality of signals to extract a plurality of uterine electrical activity characteristics; analyzing the plurality of uterine electrical activity characteristics; and classifying the uterine activity as one of: a preterm labor contraction, a labor contraction, a Braxton-Hicks contraction, and a state of no contraction. A method of assessing over time a pre-term birth risk of a pregnant female may include: calculating a baseline pre-term birth risk score based on a user input; acquiring, over time, a signal from a sensor; analyzing the signal to extract a parameter of interest, such that the parameter of interest comprises a physiological parameter; and calculating an instant pre-term birth risk score based, at least in part, on the parameter of interest and the user input.

An implantable medical device (IMD) and method are provided. The IMD includes a sensing channel configured to obtain biological signals indicative of biological behavior of an anatomy of interest over a period of time. The biological behavior has a feature of interest that repeats over time. The biological signals have clinically relevant (CR) segments that include information related to the feature of interest. The biological signals have non-clinically relevant (NCR) segments that do not include information related to the feature of interest. At least one of circuitry or a processor are configured to compare the biological signals to an amplitude window to distinguish the CR segments from the NCR segments, save to memory the CR segments and delete the NCR segments, save to memory time information indicative of a duration of the NCR segments that were deleted and to form a lossy compressed data set for the biological signals.

An active implantable stimulating device (10) includes: (a) a tissue coupling unit (40) for being implanted directly onto a vagus nerve (Vn) of a patient, (b) an EEG-unit (70) for measuring an electroencephalogram of the patient, (c) an encapsulation unit (50) configured for being subcutaneously implanted, (d) an energy transfer lead (30) for transferring pulses of electrical and/or optical energy, (e) a signal transfer lead (60) for transferring signals between the EEG unit and the encapsulation unit. EEG electrodes (70a-70d) monitor the electric activity of the brain of a patient. The EEG signal is conveyed to the electronic circuit (53) in the form of EEG conditioned data. The electronic circuit analyses the EEG conditioned data to yield analysis results. The electronic circuit takes a decision to trigger energy pulses to stimulate the vagus nerve (VN).

Systems and methods for electronically creating and modifying a fitness plan are disclosed. The method may include receiving electronic user data, collecting electronic fitness data, and displaying a suggestion for a fitness activity based on the electronic user data and the electronic fitness data.

An implantable vagus nerve stimulation (VNS) system includes a sensor configured to measure ECG data for a patient, a stimulation subsystem configured to deliver VNS to the patient, and a control system configured to perform a heart rate variability analysis with the ECG data. In some aspects, performing the heart rate variability analysis includes measuring R-R intervals between successive R-waves for the ECG data measured during a stimulation period and a baseline period, plotting each R-R interval against an immediately preceding R-R interval for each of the stimulation period and the baseline period, and determining at least one of a standard deviation from an axis of a line perpendicular to an identity line for each of the stimulation period plot and the baseline period plot or a centroid of each of the stimulation period plot and the baseline period plot.

Disclosed herein are systems and methods for electrically modulating tissue. Systems can include a current generator; at least one implantable working electrode, the at least one implantable working electrode configured to be in electrical communication with the current generator; at least one indifferent electrode; and a controller configured to signal the current generator to: generate a set of currents with a set of initial polarities to be delivered to the working electrodes; and wherein the at least one indifferent electrode absorbs a bias current which is equal in magnitude and opposite in polarity to a summation of the set of currents.