A therapeutic support apparatus includes a user support surface extending along a longitudinal axis. The user support surface has a head section and a torso section. Each of the head section and the torso section are operable to angle relative to the longitudinal axis. An elevation unit is operable to position at least one of the head section and torso section at angles relative to the longitudinal axis. A monitor acquires data related to a user while sleeping on the user support surface. An alarm is operable to activate based on the data acquired by the monitor.

Embodiments are directed to identifying and measuring bodily states and feedback systems. A computer system initializes a tracking and measuring device to generate patient data related to a bodily state or feedback system of a patient. The computer system gathers the patient data using the initialized tracking and measuring device, and identifies a baseline parameter used to determine a baseline state relative to the gathered patient data. The computer system further gathers additional patient data using the initialized tracking and measuring device and compares the additional gathered patient data to the identified baseline parameter. Then, if the additional gathered patient data differs from the baseline state by a specified threshold amount, the computer system determines that a change in the patient's bodily state or feedback system has occurred and/or determines the amount of change in the bodily state or feedback systems that has occurred.

Blood pressure signals are reconstructed from PhotoPlethysmoGraphy (PPG) signals by: receiving PPG signals including systolic, diastolic and dicrotic phases; and determining first and second derivatives of the PPG signals and: a first set of values indicative of lengths of the signal paths of the PPG signal, the first derivative and the second derivative thereof in the systolic, diastolic and dicrotic phases; a second set of values indicative of relative durations of the PPG signal and the first and second derivatives thereof in the systolic, diastolic and dicrotic phases; and a third set of values indicative of the time separation of peaks and/or valleys in subsequent waveforms of the PPG signal. Reconstruction also includes applying artificial neural network processing to the first, second and third set of values. The artificial neural network processing includes artificial neural network training as a function of blood pressure signals to produce reconstructed blood pressure signals.

A method of controlling a wearable device, and which includes obtaining, by a camera of the wearable device, an image including at least a partial field of vision of a user; identifying, by a controller of the wearable device, an object appearing in the image obtained by the camera at a first time point; storing information about the identified object in a memory; detecting, via a microphone of the wearable device, a speech of a user using the wearable device at a second time point; identifying, via the controller, a word included in the detected speech of the user corresponds to the object identified in the image; retrieving, via the controller, the information about the object from the memory based on the identified word included in the detected speech; and outputting the retrieved information about the object.

A method of medical imaging including receiving k-space data that is divided into multiple k-space data groups, selecting one of the multiple k-space data groups as a reference k-space data group, and calculating spatial transform data for each of the multiple k-space data groups by inputting the multiple k-space data groups and the reference k-space data group into a transformation estimation module. The spatial transformation estimation module is configured for outputting spatial transform data descriptive of a spatial transform between a reference k-space data group and multiple k-space data groups in response to receiving the reference k-space data group and the multiple k-space data groups as input. The method further comprises reconstructing a corrected magnetic resonance image according to the magnetic resonance imaging protocol using the multiple k-space data groups and the spatial transform data for each of the multiple k-space data groups.

A computer-implemented method for obtaining continuous signals from biopotential signals, including: separating, by a computer, confounding components from the biopotential signals by using a statistical correlation analysis algorithm to obtain denoised neural signals; and decoding, by the computer, the continuous signals from the denoised neural signals.

Systems, apparatus, and methods for treating medication refractory epilepsy are disclosed. In one embodiment, a method of treating epilepsy is disclosed comprising detecting, using a first electrode array coupled to a first endovascular carrier, an electrophysiological signal of a subject. The method further comprises analyzing the electrophysiological signal using a neuromodulation unit electrically coupled to the first electrode array and stimulating an intracorporeal target of the subject using a second electrode array coupled to a second endovascular carrier implanted within a part of a bodily vessel superior to a base of the skull of the subject.

An apparatus and method involve not just comparing a patient's recovery but improving predications by grouping the patient into a phenotype to trend the patient's rate of progress compared to existing phenotype clusters to predict, based on a comparison of rate of progress of decline, and assess in order to benefit in the improvement of allocation and timing of future resource needs, including the economic impact.

Augmented reality systems and methods for user health analysis. Methods for user health analysis may include collecting data for an initial prediction model and continuing to collect additional data based on one or more data criteria. The methods may further include updating the initial prediction model based on the additional data to produce a revised prediction model or causing an intervention to occur based on the additional data. The data may be collected by a display system including one or more sensors configured to collect user-specific data and a display device configured to present virtual content to a user. The display device may be configured to output light with variable wavefront divergence.

The invention provides a device (and method) for masking noise in which a calibration is carried out to determine the sensitivity of a user to a calibration sound. During use of the device, the signal characteristics of the masking sound are adjusted based on the detected noise, the response of the user to the detected noise and also the response of the user to the calibration sound. As a result, a masking sound is generated that is optimally adapted to mask unwanted noise, in particular in a way which avoids the masking noise itself becoming a disturbance to the particular user.