A system and a method for processing multiple signals generated by sensors processing to identify and/or monitor physiological data of an individual (for example in healthcare system) or general statement of an environment, a predetermined space (for example a room, a machine, a building) or an object (for example in smart home system, environment monitoring system, fire prevention system or the like).

In some aspects, a device wearable by a person includes a transducer configured to apply to the brain of the person acoustic signals.

Example aspects of a collector for a seizure detection device, a seizure detection device, and a method of detecting a seizure are disclosed. The collector for a seizure detection device can comprise a collector material configured to collect volatile organic compounds given off from a patient's skin; a wrapping configured to isolate the collector material from an external environment; a heater comprising a heating element, the heating element configured to emit a thermal pulse to desorb the volatile organic compounds from the collector material; and a mesh layer configured to prevent the collector material from contacting the patient's skin, wherein the collector material is received between the wrapping and the mesh layer.

An apparatus and method for monitoring a driver with epilepsy using a brain wave signal are disclosed. The monitoring method includes collecting a brain wave signal for a driver with epilepsy in a mobility for a predetermined time, determining the driver's state by analyzing the brain wave signal collected for the predetermined time, and controlling an operation of the mobility on the basis of the determined driver's state.

A system and method for finding a Pareto-optimal solution for automated detection, warning, and abatement of a medical condition based on a cost of event intervention in a patient is disclosed. The method includes acquiring at least one biological signal from the patient via at least one sensor of a medical device, detecting an abnormal biological event based on changes in the biological signal, and delivering at least one of a therapy and a warning. The method includes logging a set of parameters including at least one of a detection parameter, a therapy parameter, and a therapy modality. The method includes identifying an optimal set of parameters that yield a Pareto-optimal cost of event intervention by iteratively determining at least one metric over a time window, determining the cost of event intervention, and modifying at least one parameter, until the cost of event intervention meets an acceptability criteria.

A determination apparatus includes circuitry configured to: compare signal separation results obtained by a plurality of signal separation algorithms executed on a mixed signal in which signals emitted from a plurality of signal sources are mixed, each of the plurality of signal separation algorithms being an algorithm separating a signal of interest from the mixed signal; and determine a parameter of each of the plurality of signal separation algorithms based on a comparison result.

A computer-implemented method for detecting pathological brain activity patterns from a scalp electroencephalographic signal, the method including the steps of obtaining (A) an electroencephalographic signal as a function of multiple channels and time; identifying (C), for each channel, the zero-crossings of the electroencephalographic signal over a fixed threshold; generating a zero-crossing representation of at least a segment of the obtained electroencephalographic signal with the identified zero-crossings; obtaining (D) a reference family of real functions of time and channels from a zero-crossing statistical analysis of zero-crossing representation of pre-recorded electroencephalographic signals; calculating (E) a matching score by comparing the zero-crossing representation of a segment of the electroencephalographic signal with at least one reference function from the reference family of functions; and computing the matching score as a function of time by sliding the at least one reference function from the reference family of functions over the electroencephalographic signal.

An electromagnetic tomography system for gathering measurement data pertaining to a human head includes an image chamber unit, a control system, and a housing. The image chamber unit includes an antenna assembly defining a horizontally-oriented imaging chamber and including an array of antennas arranged around the imaging chamber. The antennas include at least some transmitting antennas and some receiving antennas. The control system causes the transmitting antennas to transmit a low power electromagnetic field that is received by the receiving antennas after passing through a patient's head in the imaging chamber. A data tensor is produced that may be inversed to reconstruct a 3D distribution of dielectric properties within the head and to create an image. The housing at least partially contains the antenna assembly and has a front entry opening into the imaging chamber. The head is inserted horizontally through the front entry opening and into the imaging chamber.

A device for monitoring the electro-physiological activity of a subject, particularly for diagnosing or monitoring epilepsy, including: measurement element for measuring electrical brain activity; measurement element for measuring the electrical activity of the muscles of mastication; an acquisition module configured to acquire in synchronously the signals measured by the measurement element for measuring electrical brain activity and by the measurement element for measuring the electrical activity of the muscles of mastication;
a signal processing modules; and a transmission module for transmitting the electrical signals acquired by the acquisition module to the signal processing module.

The signal processing module is configured to detect among the signals measured by the measurement element for measuring electrical brain activity the signals measured by the measurement element for measuring the electrical activity of the muscles of mastication.

An adaptive cognitive prosthetic that learns to replace neural function that was lost due to a brain injury or disease is described herein. In some embodiments, an adaptive cognitive prosthetic comprises a processing unit for converting input data from an input assembly into a cognitive variable and selecting a stimulation pattern for conveying the cognitive variable. The processing unit employs an adaptive algorithm to assemble the stimulation pattern by combination of subset stimulation patterns, the combination of subset stimulation patterns learned by the adaptive algorithm through error analysis.