A dynamic neuropsychological assessment tool according to an embodiment utilizes speech recognition, speech synthesis and machine learning to assess whether a patient is at risk for a neurological disorder, such as Alzheimer's disease. The dynamic neuropsychological assessment tool enables self-administration by a patient. The tool performs pre-test validation operations on the test environment, test equipment, and the patient's capability for performing the test at that time. The tool also enables dynamic modification of a questionnaire presented to the patient while the patient completes the questionnaire. Also provides the dynamic modification of which tests to present the patient with. The modification can be rule based or modified by a provider. The dynamic neuropsychological assessment tool enables providers and administrators to modify and improve tests and validate them using machine learning based on previously completed assessments and results.

Transducer-based systems can be configured to display a graphical representation of a transducer-based device, the graphical representation including graphical elements corresponding to transducers of the transducer-based device, and also including between graphical elements respectively associated with a set of the transducers and respectively associated with a region of space between the transducers of the transducer-based device. Selection of graphical elements and/or between graphical elements can cause activation of the set of transducers associated with the selected elements. Selection of a plurality of graphical elements and/or between graphical elements can cause visual display of a corresponding activation path in the graphical representation. Visual characteristics of graphical elements and between graphical elements can change based on an activation-status of the corresponding transducers. Activation requests for a set of transducers can be denied if it is determined that a transducer in the set of transducers is unacceptable for activation.

The present invention relates to a device and a method for detecting a peak of an intracranial pressure (ICP) waveform using a morphological feature of an arterial blood pressure waveform. A peak extracting method of an ICP waveform using a morphological feature of an arterial blood pressure waveform according to an aspect of the present invention includes: extracting a pulse onset from a continuous ICP waveform based on systolic peak from arterial blood pressure waveform; dividing individual ICP waveforms in the continuous ICP waveform based on the pulse onset; deriving a derivative value from each of the ICP waveforms to extract a peak, a trough, and a flat; calculating latencies from the pulse onset extracted in each of the ICP waveforms to the extracted peaks to cluster peaks with a similar time interval and generate a peak cluster; searching a notch from each of the ICP waveforms based on the latency of a dicrotic notch of the arterial blood pressure waveform; and extracting P1, P2, and P3 peaks from each of the ICP waveforms by referring to the searched notch of the ICP.

A method and system are disclosed for outputting augmented reality information to a first user. In an embodiment, the method includes acquiring first information, including image information, depth information, coordinate information and combinations thereof, the first information relating to at least one of a medical device and a medical examination of a patient; creating the augmented reality information, relating to the medical device and/or the medical examination of the patient, based on the first information; and outputting the augmented reality information such that the augmented reality information is perceivable in a field of view of the first user.

A method, including receiving a bipolar signal from a pair of electrodes in proximity to a myocardium of a human subject, and receiving a unipolar signal from a selected one of the pair of electrodes. The method further includes delineating a window of interest (WOI) for the unipolar and bipolar signals, within the WOI computing local unipolar minimum derivatives of the unipolar signal, and times of occurrence of the local unipolar minimum derivatives, and within the WOI computing bipolar derivatives of the bipolar signal at the times of occurrence. The method also includes evaluating ratios of the bipolar derivatives to the local unipolar minimum derivatives, and when the ratios are greater than a preset threshold ratio value, assigning the times of occurrence as times of activation of the myocardium, counting a number of the times of activation; and classifying the unipolar signal according to the number.

Systems and methods for mapping neuronal circuitry in accordance with embodiments of the invention are illustrated. One embodiment includes a method for generating a neuronal shape graph, including obtaining functional brain imaging data from an imaging device, where the functional brain imaging data includes a time-series of voxels describing neuronal activation over time in a patient's brain, lowering the dimensionality of the functional brain imaging data to a set of points, where each point represents the brain state at a particular time in the timeseries, binning the points into a plurality of bins, clustering the binned points, and generating a shape graph from the clustered points, where nodes in the shape graph represent a brain state and edges between the nodes represent transitions between brain states.

Systems and methods for generating a three-dimensional (3D) model of a user's dental arch based on two-dimensional (2D) images of dental impressions include a model training system that provides a machine learning model using training image(s) of a dental impression of a respective dental arch and a 3D training model of the respective dental arch. A model generation system receives first image(s) of a first dental impression of a user's dental arch and second image(s), which may be of the first dental impression or a second dental impression of the dental arch. The model generation system generates a first and second 3D model of the dental arch by applying the first image(s) and second image(s) to the machine learning model.

A health data management system includes a health data measurement apparatus and a health management server communicable therewith. The apparatus includes medical and health equipment that measures health data of a user and first circuitry that collects the health data. The management server includes a first memory that stores the health data from the apparatus and second circuitry. Based on the stored health data, the second circuitry generates health management data representing a health state of the user, and analyzes at least one of an item indicating a worsening health state of the user, an item with insufficient measurement data, or an item lacking measurement data as a required check item. When determined that the health management data includes the required check item, the second circuitry transmits to the apparatus a message prompting the user to take a measurement of the required check item, and requests the health data.

A health monitoring system and corresponding method for monitoring a physiological condition of a user may include collecting, by a monitoring device, measurements representing physiological signals of the body, transmitting the measurements from the monitoring device to a local device, and receiving, at a remote server, the measurements and additional data from the local device. The remote server may include a processing module, a review portal and a clinician portal, such that the remote server may be arranged to automatically classify the measurements representing physiological signals of the body, verify the classifications, and provide the verified measurements at a clinician portal.

A method of extracting and displaying postural measurements from patient data includes retrieving, by a processor of a computing device, the patient data from memory. The patient data includes a geometric mesh representation of a patient, including a plurality of data points corresponding to spatial coordinates of a plurality of vertices in three dimensions. The method also includes determining, by the processor, a reference geometry along the geometric mesh representation in a fixed position with respect to the spatial coordinates; determining, by the processor, a landmark corresponding to one of skeletal or soft tissue anatomy for the patient; and determining, by the processor, a postural deviation of a body portion of the patient by comparing the reference geometry and the landmark. The method further includes displaying, by a display of the computing device, a graphical user interface indicating a characteristic related to the postural deviation.