A medical device and associated method for detecting and treating tachyarrhythmias acquires a cardiac signal using electrodes coupled to a sensing module. During an initial detection process, a shockable cardiac rhythm is detected by a processing module configured to compare the cardiac signal to a first set of detection criteria. By analyzing the cardiac signal, the processing module establishes at least one patient-specific detection threshold during the initial detection process. Upon establishing the at least one patient-specific detection threshold, the initial detection process is stopped, and a next detection process is started which includes comparing the cardiac signal to a second set of detection criteria including the at least one patient-specific detection threshold. In some embodiments, user programming of tachyarrhythmia detection parameters is not required.

An apparatus for monitoring a nerve includes a Foley type catheter having an exterior surface, and first and second pairs of ring electrodes formed on the exterior surface of the Foley catheter. Each of the first and second pairs of ring electrodes is configured to perform at least one of stimulating the nerve and recording nerve activity.

Systems, methods, and graphical user interfaces are described herein for non-invasively detecting phrenic nerve stimulation during cardiac pacing therapy. Phrenic nerve stimulation information may be generated for one or more electrical pacing vectors at one or more power configurations. The phrenic nerve stimulation information may be displayed to a user for use in configuring and/or evaluating cardiac pacing therapy.

A method and apparatus for the quantitative determination of an individual's risk for sudden cardiac death (SCD) is described. Risk stratification is accomplished (and may have a sensitivity and specificity of greater than about 90%) by determining the presence in any individual being tested for SCD risk of sequences identified herein to correlate quantitatively with SCD risk. Both the number of such sequences present and their alignment scores (similarity) with the SCD risk sequence ensemble are used to calculate quantitative SCD risk.

There is described a technique using apparatus for recording and analyzing a surface electrocardiogram (ECG) for distinguishing a physiological signal from noise. The technique involves aligning and averaging multiple surface electrogram records taken for repeated pacing sequence with the same interval between pacing stimuli.

A method for processing EEG signals includes reading the EEG signals from two frontal electrodes of an electroencephalograph (301); converting the EEG signals to a frequency domain (305); determining values of a BIS/BAS response on the basis of an asymmetry between the EEG signals (208). The method includes calculating the asymmetry between the EEG signals in the frequency domain in a frequency range from 26 to 29 Hz.

Systems and methods for discovery and characterization of neuroactive drugs are provided. In some aspects, a method for evaluating an effectiveness of a drug administered to a subject includes receiving neurophysiological data acquired from a subject under an administration of a drug, and analyzing the neurophysiological data to generate signatures indicative of brain states induced by the drug. The method also includes correlating the generated signatures with a database comprising information associated with a plurality of drug profiles, and determining, using the information, a molecular activity profile for the drug. The method further includes generating a report indicative of the effectiveness of the drug using the molecular activity profile.

Systems and methods for inducing natural sleep in a subject is provided. In some aspects, the method includes inducing a first sleep state; monitoring a first plurality of characteristics of a brain of the subject to verify the subject is in the first sleep state; inducing a second sleep state after the subject has been in the first sleep state for a predetermined amount of time; and monitoring a second plurality of characteristics of the brain of the subject to verify the subject is in the second sleep state.

Disclosed herein is a framework for facilitating patient signal analysis based on vector analysis. In accordance with one aspect, a set of vectors is generated from a patient signal data waveform. The vectors may be directed from a common center to points of interest on the patient signal data waveform. The framework may further extract one or more vector parameters from the set of vectors, and determine one or more vector ratios based on the vector parameters to monitor changes in the patient signal data waveform.

A system and method for detecting and verifying bradycardia/asystole episodes includes sensing an electrogram (EGM) signal. The EGM signal is compared to a primary threshold to sense events in the EGM signal, and at least one of a bradycardia or an asystole is detected based on the comparison. In response to detecting at least one of a bradycardia or an asystole, the EGM signal is compared to a secondary threshold to sense events under-sensed by the primary threshold. The validity of the bradycardia or the asystole is determined based on the detected under-sensed events.