A medical imaging decision support system is provided that can conduct, and help medical professionals conduct multi-factor brain analysis. Data for disparate processing modes (for example, EEG, MRI, etc.) can be input to the system, processed in parallel in a cloud environment, and the results can be rendered in a thin client (for example, browser) for a user's rapid multi-modal evaluation of a brain.

An initial set of parameters for operating one or more detection tools is automatically derived and subsequently adjusted so that each detection tool is more or less sensitive to signal characteristics in a region of interest. Detection tool(s) may be applied to physiological signals sensed from a patient (such as EEG signals) and may be configured to run in an implanted medical device that is programmable with the parameters to look for rhythmic activity, spiking, and power changes in the sensed signals, etc. A detection tool may be selected and parameter values derived in a logical sequence and/or in pairs based on a graphical representation of an activity type which may be selected by a user, for example, by clicking and dragging on the graphic via a GUI. Displayed simulations allow a user to assess what will be detected with a derived parameter set and then to adjust the sensitivity of the set or start over as desired.

A medical lead with at least a distal portion thereof implantable in the brain of a patient is described, together with methods and systems for using the lead. The lead is provided with at least two sensing modalities (e.g., two or more sensing modalities for measurements of field potential measurements, neuronal single unit activity, neuronal multi unit activity, optical blood volume, optical blood oxygenation, voltammetry and rheoencephalography). Acquisition of measurements and the lead components and other components for accomplishing a measurement in each modality are also described as are various applications for the multimodal brain sensing lead.

A neurostimulation device includes a plurality of electrodes adapted to be electrically connected to a subject to receive multichannel electrical signals from the subject's brain, a multichannel seizure detection unit electrically connected to the plurality of electrical leads to receive the multichannel electrical signals, and a neurostimulation unit in communication with the multichannel seizure detection unit. The plurality of electrodes are at least three electrodes such that the multichannel electrical signals are at least three channels of electrical signals, and the multichannel seizure detection unit detects a presence of a seizure based on multichannel statistics from the multichannel electrical signals including higher order combinations than two-channel combinations.

Provided are methods and system for assessing a human subject's neurological and/or psychological status. The methods entail displaying visual tests to a human subject, wherein each of the visual tests includes a visual target signal, optionally with visual cue signals, for eliciting visual and, optionally, body part, movements by the subject. Following the display, the movements are then detected. The latency and/or correctness of such movements can then be used to assess the subject's neurological and/or psychological status. Also provided are methods and systems for assessing performance validity.

A method of estimating the probability of a seizure in a subject, the method comprising: receiving historical data associated with epileptic events experienced by the subject over a first time period, the historical data comprising physiological data associated with each epileptic event and a time at which each epileptic event occurred; generating a temporal probability model of future epileptic events based on the time of each of the epileptic events, the temporal probability model representing a probability of a future seizure occurrence in each of a plurality of time windows; generating a probabilistic model based on the physiological data associated with each epileptic event; weighting the probabilistic model based on the temporal probability model to generate a weighted probabilistic model of future seizure activity; and outputting an estimate of seizure probability in the subject using the weighted probabilistic model.

Disclosed are methods and systems for treating epilepsy by stimulating a main trunk of a vagus nerve, or a left vagus nerve, when the patient has had no seizure or a seizure that is not characterized by cardiac changes such as an increase in heart rate, and stimulating a cardiac branch of a vagus nerve, or a right vagus nerve, when the patient has had a seizure characterized by cardiac changes such as a heart rate increase.

Systems and methods of the present invention provide for storing an annotated set of confirmed epileptiform discharges (ED) waveforms in a database; receiving, by a computing device, a signal encoding electroencephalograph (EEG) data from a plurality of electrodes each attached to a subject and detecting EEG data; generating a user interface displaying a plurality of waveforms based upon at least a portion of the EEG data; receiving an initial selection of a portion of one of the plurality of waveforms comprising an ED; identifying a list of candidate waveforms including potential EDs by determining an alignment of the initial selection with a portion of one of the plurality of waveforms in the EEG data; displaying the list of candidate waveforms on the user interface; receiving, from the user and via the user interface, an identification of a subset of the list of candidate waveforms; and storing the subset of the list of candidate waveforms as an annotated list of confirmed EDs in the database.

The invention relates to an electrode for detecting a bioelectrical signal, for example EEG, on a skin surface. The electrode comprises a coating comprising iridium oxide, where the coating has a nanostructured surface pattern providing for a capillary and hydrophilic effect when in use.

The present invention describes methods and systems to enable a concerned party to continuously monitor the progression of a medical condition in one or more patients. The progression of the medical condition is determined by processing sensor data obtained from one or more physiological and/or motion sensors and survey data obtained from the patients. Further, environmental data such as air quality, temperature and humidity may also be used along with the sensor data and the survey data to monitor/track the progression of the medical condition.