A system including a medical device is provided. The medical device includes at least one sensor configured to acquire first data descriptive of a patient, first memory storing a plurality of templates, and at least one processor coupled to the at least one sensor and the first memory. The at least one processor is configured to identify a first template of the plurality of templates that is similar to the first data, to determine first difference data based on the first template and the first data, and to store the first difference data in association with the first template. The system may further include the programmable device.

A dental appliance including a dielectric substrate with one or more electric areas having one or more integrated circuits, one or more electric lines, and optionally one or more shielding lines. The dental appliance further includes one or more ground areas including one or more ground pads, one or more sensing areas including one or more sensing pads, and optionally one or more shielding pads. The dental appliance is configured to monitor dental contact, dental forces, and/or for detecting teeth clenching and/or grinding.

It is presented a method performed in a vehicle action determiner for determining an undesired action of a first vehicle and a resulting action. The method comprises: detecting that a first user is focusing on the first vehicle; acquiring brain activity data of the first user; determining a negative reaction of the first user based on the brain activity data; determining when the first vehicle is performing an undesired action based on the first user focusing on the first vehicle and the negative reaction of the first user; determining the resulting action taken by an autonomous vehicle, based on the first vehicle performing the undesired action; and triggering the autonomous vehicle to perform the resulting action.

A system and method for non-invasively generating a report of cardiac electrical activities of a subject includes determining, using cardiac electrical activation information, equivalent current densities (ECDs). The ECDs are assembled into time-course ECD information and a spectrum of the time-course ECD information is analyzed to determine peaks for spectral characteristics of atrial fibrillation (AF). The spectral characteristics of AF are correlated with potential electrical sources of the AF and a report is generated indicating the potential electrical sources of the AF spatially registered with the medical imaging data.

The present invention is directed to a method of continuously monitoring neuronal avalanches in a subject comprising (a) determining a deviation in avalanche exponent () or branching parameter () from a predetermined value at rest, wherein the pre-determined value of is a slope of a size distribution of the synchronized neuronal activity and the predetermined value is 3/2 and the pre-determined value of is a ratio of successively propagated synchronized neuronal activity and the predetermined value is 1; and (b) repeating step (a) one or more times to continuously monitor neuronal avalanches in a subject. The invention also features methods of determining or monitoring the degree of sleep deprivation in a subject, methods of identifying subjects that are susceptible to a sleep disorder and methods of diagnosing a sleep disorder in a subject.

We provide a method of compressing a data stream for transmission, including: generating a data sequence representing a received data stream, generating a plurality of data substreams, each comprising a portion of the data sequence, identifying a formal concept defining a dependency between a first one of the data substreams and one or more further ones of the data substreams that are dependent on the first data substream, removing those dependent data substreams from the plurality of data substreams, and transmitting the remaining data substreams, and a method of reconstructing a data stream at a receiver, including: receiving a received data sequence representing a received data stream, identifying that a substream has been removed from the data stream prior to transmission, identifying a formal concept definition for regenerating the removed substream based on an identified substream of the received data sequence, regenerating a data substream using the formal concept definition and the identified substream of the received data sequence, and adding the regenerated data substream to the received data sequence.

Provided are systems and methods for integrated control and safety systems (ICSSs) that employ intelligent personal protective equipment (PPE). In some embodiments, an industrial plant system includes an industrial safety system (ISS) for monitoring a safety status of an industrial plant and one or more intelligent PPE systems worn by personnel located in the industrial plant. Each of the intelligent PPE systems includes one or more intelligent PPE devices for sensing personal and environmental characteristics of a person wearing the intelligent PPE system, and transmits safety data corresponding to the personal and environmental characteristics sensed. The ISS collects the safety data, determines (based on the safety data) whether a safety incident has occurred and, in response to determining that a safety incident has occurred, executes a response to the safety incident.

Described herein are implantable systems and devices, and methods for use therewith, that distinguish between different signal components of interest in sensed physiologic signals with high sensitivity and specificity. Such a method can include obtaining a sensed signal using an IMD and using a plurality of different filters that are parallel to one another to simultaneously filter the sensed signal, and/or copies thereof, to produce different filtered signals. Where each filter has a respective passband that does not substantially overlap with the passband(s) of the other filter(s), each of the different filtered signals will be indicative of different frequency content of the sensed signal. Additionally, amplitudes of temporally aligned peaks in at least two of the different filtered signals can be detected, and one or more peaks of the sensed signal can be classified based on the detected amplitudes of the temporally aligned peaks in the different filtered signals.

A system and a process are provided for evaluating subliminal pixel patterns and identifying trigger patterns, which are pixel patterns that trigger a response in subjects exposed to the pattern. Each pixel pattern is embedded in a digital video or a digital still image. Pixel patterns that are found to induce reactions in subjects are identified as trigger patterns and are flagged for re-testing. Re-tested trigger patterns that repeatably induce reactions are identified as positive trigger patterns and are studied further. Variations are made to a positive trigger pattern to determine whether small changes can affect how a subject responds when exposed to that positive trigger pattern. A positive trigger pattern is evaluated to determine whether it can induce an emotional, a physical, and/or a behavioral change in the subjects and, if so, the positive trigger pattern is applied to a real-world situation.

Described is a computer system for establishing an electroencephalogram (EEG) model for discriminating between alert and fatigue states. The computer system comprises a receiver module for receiving an alert state segment illustrative of an alert state of at least one subject, and one or more EEG fatigue data segments illustrative of a fatigue state of the at least one subject. The computer system further comprises a segment selector for selecting one of the one or more fatigue data segments and setting it to be an assumed maximum fatigue segment, an EEG classifier trainer for training an EEG classifier by extracting an EEG feature space from the alert state segment and assumed maximum fatigue segment, and a maximum fatigue identifier module for identifying a segment of maximum fatigue by applying the EEG classifier to each of the fatigue data segments. The computer system further comprises a segment comparator for determining if the segment of maximum fatigue is consistent with the assumed maximum fatigue segment, and a limit setter for setting the segment of maximum fatigue as a revised assumed maximum fatigue segment, if the segment of maximum fatigue is inconsistent with the assumed maximum fatigue segment, and supplying the EEG classifier trainer with the revised assumed maximum fatigue segment. The computer system further comprises a model output module for setting the EEG classifier as the EEG model for discriminating between alert and fatigue states in segments of EEG data, if the segment of maximum fatigue is consistent with the assumed maximum fatigue segment.