A seizure prediction algorithm based on deep learning that integrates the feature extraction and classification processes into a single automated architecture is claimed herein. In the method, the computation complexity is reduced because there is no feature engineering. The method uses a novel algorithm for EEG channel selection in which the number of EEG channels is decreased to reduce the required memory for storing the data and parameters. In one or more embodiments, an IoT based framework for accurate epileptic seizure prediction system is disclosed.

Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, a computer-implemented method for operating an autonomous or semi-autonomous vehicle may be provided. With a vehicle owner's permission, a vehicle operator identity may be determined; and operating data regarding the autonomous or semi-autonomous vehicle may be received from one or more vehicle-mounted sensors. Based upon the received operating data, (i) autonomous operation risk levels associated with autonomous vehicle operation; and (ii) operator risk levels associated with autonomous vehicle operation by the vehicle operator may be determined. Based upon a comparison of the autonomous operation versus vehicle operator risk levels, the autonomous features may be engaged if it is safer for the vehicle to travel autonomously. Insurance discounts may be provided to risk averse vehicle owners having this safety functionality.

Technology described herein relates to extended monitoring and analysis of subject neurological factors via blepharometric data collection, for example, including devices and processing systems configured to enable such extended monitoring. This may include hardware and software components deployed at subject locations (for example, in-vehicle monitoring systems, portable device monitoring systems, and so on), and cloud-based hardware and software (for example, cloud-based blepharometric data processing systems. The technology allows for user blepharometric data to be collected across a plurality of monitoring sessions, in some cases via different collection technologies, thereby to analyze changes over time. For example, this can assist in identifying risks of degenerative neurological conditions.

A method for assessment, optimization and logging of the effects of a therapy for a medical condition, including (a) receiving into a signal processor input signals indicative of the subject's brain activity; (b) characterizing the spatio-temporal behavior of the brain activity using the signals; (c) delivering a therapy to a target tissue of the subject; (d) characterizing the spatio-temporal effect of the therapy on the brain activity; (e) in response to the characterizing, optimizing at least one parameter of the therapy if the brain activity has not been satisfactorily modified and/or has been adversely modified by the therapy; (f) characterizing the spatio-temporal effect of the at least one optimized parameter; and (g) logging to memory the at least one optimized parameter. A computer readable program storage unit encoded with instructions that, when executed by a computer, performs the method.

Systems and methods rely on feedback from an active medical device or devices (e.g., neurostimulator coupled to sensing and stimulation elements such as electrodes) to assess the effectiveness of a patient's drug regimen. Such reliance may include analyzing characteristics in physiological data acquired by the medical device(s), for example, in the form of responses evoked from the patient by electrical stimulation waveforms. Systems and methods further involved adjusting one or more parameters according to which a combination therapy consisting of at least a drug regimen and an electrical stimulation therapy are delivered to a patient, in an effort to optimize the therapeutic effect of the combination. The adjustments may be automatically by one or more implanted or external hosts working together or alone, and/or with the input of a physician.

An implanted electrical signal generator delivers a novel exogenous electrical signal to a vagus nerve of a patient. The vagus nerve conducts action potentials originating in the heart and lungs to various structures of the brain, thereby eliciting a vagal evoked potential in those structures. The exogenous electrical signal simulates and/or augments the endogenous afferent activity originating from the heart and/or lungs of the patient, thereby enhancing the vagal evoked potential in the various structures of the brain. The exogenous electrical signal includes a series of electrical pulses organized or patterned into a series of microbursts including 2 to 20 pulses each. No pulses are sent between the microbursts. Each of the microbursts may be synchronized with the QRS wave portion of an ECG. The enhanced vagal evoked potential in the various structures of the brain may be used to treat various medical conditions including epilepsy and depression.

A system and method is provided for modeling brain dynamics in normal and diseased states.

A method of detecting a seizure status of a subject includes collecting first data from a first accelerometer positioned on a first limb of the subject and a second data from a second accelerometer positioned on a torso of the subject, determining that one of the first accelerometer or the second accelerometer provides a better indication (e.g., greater level of sensitivity or a lesser level of a false positive rate) by comparing the first data and the second data, detecting an indication of the seizure status of the subject using at least one of the first data and the second data, and generating an alert in response to the detection of the indication of the seizure status of the subject.

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.

Systems, methods and apparatuses described herein generally provide a millimetre size package-free complementary metal-oxide-semiconductor (“CMOS”) chip (referred to as a “die”) for the in situ (on-site) measurement or imaging of electrochemically detectable analytes.