A method and system for monitoring therapeutic interventions for treating a patient with PTSD comprises using a scanner to obtain pre-treatment neural spectroscopic data of at least one neuromarker chemical in the brain of the patient before treatment, treating the patient with at least one treatment protocol, after treatment, obtaining post-treatment neural spectroscopic data of the at least one neuromarker chemical in the brain of the patient, and comparing the results of the pre-treatment and post-treatment data to enable a determination of the effectiveness of the treatment.

The present invention concerns an apparatus for treating neurological disorders comprising (i) at least one electrode implantable in the brain of a patient and (ii) a processing and stimulation device connected to the at least one electrode, wherein the processing and stimulation device comprises (a) at least one stimulation module adapted to generate a stimulation signal to be sent to the at least one electrode, the stimulation signal being characterised by a plurality of parameters, (b) at least one acquisition module of a signal characteristic of cerebral activity coming from the brain of the patient adapted to determine its power in at least one frequency band, and (c) at least one control module of at least one parameter of the stimulation signal as a function of the power of the signal characteristic of cerebral activity acquired, based on a transfer function having a saturating trend, wherein the transfer function is such as to set the at least one parameter (Va, Vd, Vf) of the stimulation signal (Vstim) differently dependent on a plurality of power ranges, by keeping the at least one parameter within a predetermined stimulation range ([Vi_HighThreshold; Vi_LowThreshold]) with i=a,d,f.

Methods, systems, and apparatus for determining probabilistic measures of seizure activity (PMSA) values based on a plurality of seizure detection algorithms and/or body signals used as inputs by the seizure detection algorithms. Use of the PMSA values to detect seizure activity based on a consensus of the algorithms and/or body signals, and/or warn, log, administer a therapy, or assess the efficacy of a therapy.

The present disclosure relates to a sensor for monitoring the depth of consciousness of a patient. The sensor includes a plurality of light sources, light detectors, and in some embodiments, electrodes. In an embodiment, the sensor includes reusable and disposable portions.

An electroencephalogram decision system determines, when finding electroencephalogram information representing an electroencephalogram obtained by an electrode unit placed on a region of interest that forms part of a subject's head satisfying a predetermined condition, that a target electroencephalogram, which is an electroencephalogram with a characteristic variation, should have been produced. The predetermined condition is selected from of detection conditions including a first type of condition and a second type of condition. The first type of condition specifies that a decision should be made, based on a component falling within a single frequency band included in the electroencephalogram represented by the electroencephalogram information, whether or not the target electroencephalogram has been produced. The second type of condition specifies that a decision should be made, based on components falling within multiple different frequency bands included in the electroencephalogram represented by the electroencephalogram information, whether or not the target electroencephalogram has been produced.

Systems and methods for monitoring a subject under, or suspected to be under, the influence of one or more drugs are provided. In one aspect, a method comprises controlling one or more sensors of a monitoring device to acquire physiological signals from a subject suspected to be under the influence of one or more drugs, and assembling a set of physiological data using the acquired physiological signals. The method also includes generating, using a processor of the monitoring device, physiological markers characteristic of the influence of the one or more drugs by analyzing the set of physiological data, and correlating the physiological markers with a drug profile characterizing the one or more drugs affecting the subject. The method further includes proving to a user a report indicating the drug profile characterizing the one or more drugs affecting the subject.

A signal processing device and a signal processing method. The signal processing device includes a receiver, a memristor array and a classifier. The receiver is configured to receive a first signal. The memristor array includes a plurality of memristor units, each of the plurality of memristor units includes a memristor, and the memristor array is configured to apply the first signal that has been received to at least one memristor unit of the plurality of memristor units and output a second signal based on a memristor resistance value distribution of the memristor array. The classifier is configured to classify the second signal outputted from the memristor array to obtain a type of the first signal.

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, spike activity, 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 system and method for detection and analysis of learner's/performers cognitive flow have been provided. The system is configured to measure the cognitive state of the performer, while they are performing tasks of various complexity levels, using physiological responses like brain activation, heart rate variability and galvanic skin response. The system uses a Bayesian network based framework to probabilistically evaluate the cognitive state of the learner from the difficulty levels of the tasks, IQ level of the learner and observations made using the physiological sensing. The system also measures the actual cognitive state using a questionnaire. The predicted cognitive state and the actual cognitive state is compared and based on the outcome of comparison a relevant step is taken.

A device is provided for the stimulation of neurons that includes a non-invasive stimulation unit to generate stimuli in multiple stimulation channels, where the stimulation unit stimulates a neuron population in the brain and/or spinal cord of a patient in different locations for each of the stimulation channels. Moreover, the device includes a control unit that controls the stimulation unit to generate repetitive bursts in each of the stimulation channels, where each of the bursts includes multiple stimuli and is designed so that they do not reset the phase of the neuronal activity of the respective stimulated neurons.