A method is described for extracting aperiodic components from a time-series wave data set for diagnosis purposes. The method may include collecting time-series wave data within a controlled environment were a plurality of contrasting conditions can be used in collecting the time-series wave data set. Aperiodic components can be extracted from the time-series wave data set and the aperiodic components can then be fitted to the plurality of contrasting conditions of the controlled environment to product regressed aperiodic components from which diagnostic determination can be made.

Means and methods for measuring pain and adapted for calculating the level of nociception during general anesthesia or sedation from data including electroencephalogram (EEG), facial electromyogram (EMG), heart rate variability (HRV) by electrocardiogram (ECG) and plethysmography by impedance cardiography (ICG). In a preferred embodiment of this invention the parameters derived from the EEG, the HRV, the plethysmographic curve and the analgetics concentrations are either combined into one index on a scale from 0 to 100, where a high number is associated with high probability of response to noxious stimuli, while a decreasing index is associated with decreasing probability of response to noxious stimuli. Zero (0) indicates extremely low probability of response to noxious stimuli. In an alternative embodiment, only features from the EEG and ECG will be used or only features from EEG, ECG and ICG, to define the fmal index.

A method for monitoring physical conditions of an operator of a driving apparatus is described. The method includes obtaining an identity of the operator, acquiring signals indicating a physical condition of the operator, and determining whether the physical condition as indicated by the signals has breached a predetermined threshold. Further, when it is determined that the physical condition as indicated by the signals has breached a predetermined threshold, the method includes generating a first status indicating the operator suffers an abnormal physical condition, obtaining a current location of the driving apparatus, generating a first notification based on the first status, the first notification indicating the identity of the operator and the current location of the driving apparatus, the first notification describing the first user suffers the abnormal physical condition, and transmitting the first notification to a data receiver in a healthcare facility.

Techniques and technologies for determining and enhancing productivity are described. In at least some embodiments, a system for includes a processing component operatively coupled to a memory; a productivity analyzer at least partially disposed in the memory, the productivity analyzer including one or more instructions that when executed by the processing component perform operations including: receive productivity data associated with usage of one or more productivity tools by at least one user during a time period; receive biometric data associated with one or more biometric aspects of the at least one user during the time period; analyze one or more aspects of the productivity data and the biometric data; and determine based on the analysis at least one productivity-related operation intended to enhance at least one productivity metric of the at least one user.

An arrangement may include a first system provided for processing physiological data representative of a beating heart. The first system may be adapted to execute a process for using at least one pattern to detect a notable finding in the physiological data and for sending the notable finding to a second system. The second system may be adapted to execute a process for analyzing the notable finding, for determining at least one new pattern to send to the first system, and for sending the at least one new pattern to the first system. The at least one new pattern may also include a rule that includes a set of conditions and an action to perform if the set of conditions is met.

A hearing assistance system comprises an input unit for providing electric input sound signals u.sub.i, each representing sound signals U.sub.i from a multitude n.sub.u of sound sources S.sub.i, an electroencephalography (EEG) system for recording activity of the auditory system of the user's brain and providing a multitude n.sub.y of EEG signals y.sub.j, and a source selection processing unit receiving said electric input sound signals u.sub.i and said EEG signals y.sub.j, and in dependence thereof configured to provide a source selection signal Ŝ.sub.x indicative of the sound source S.sub.x that the user currently pays attention to using a selective algorithm that determines a sparse model to select the most relevant EEG electrodes and time intervals based on minimizing a cost function measuring the correlation between the individual sound sources and the EEG signals, and to determine the source selection signal Ŝ.sub.x based on the cost functions obtained for said multitude of sound sources.

A method and an apparatus include a display, an iris scanning sensor, and a processor functionally coupled with the display, and the iris scanning sensor, wherein the processor activates the iris scanning sensor when receiving a display-on event in a display-off state that is an intended user input.

A rehabilitation system using an artificially intelligent horseback-riding apparatus for hippotherapy, the system comprising: an artificially intelligent horseback-riding apparatus which is ridable; a smartphone which can communicate with a cloud server and has installed an application for controlling the operation state of the artificially intelligent horseback-riding apparatus and operating the horseback-riding apparatus; a diagnostic device which is for diagnosing the state of a patient by means of a brain wave signal of the patient; an operating unit which is for operating the artificially intelligent horseback-riding apparatus; and a cloud server which is for storing, in the smartphone, treatment program and data, necessary for a patient treatment, and for transmitting same.

The present invention relates a novel system and method to diagnose and predict systemic disorders including brain disorders and mental states in early stage and more accurately. More particularly, this invention relates to a novel method of EEG recording and processing through which multiple output data streams are taken together from a system like brain and the structure of their correlation matrix is studied through its eigenvector, eigendirection and eigenspaces and other signal processing techniques including compression sensing, wavelet transform, fast fourier transform etc.

For the purpose of improving sleep satisfaction for different human subjects individually, a sound source control device (20) includes: an acquirer (202) configured to acquire a biorhythm of a human subject; an estimator (204) configured to estimate sleep depths of the human subject from the acquired biorhythm of the human subject; a controller (230) configured to control a sound source (240) to play a sound in accordance with the acquired biorhythm of the human subject, the sound being defined using a prescribed parameter set; and an evaluator (220) configured to evaluate a sleep state of the human subject based on the estimated sleep depths of the human subject, and based on the evaluation, instruct the controller (230) to change at least a part of contents of the parameter set.