An apparatus for providing information about a user's brain resources is provided. The apparatus includes at least sensor interface circuitry and processing circuitry coupled to the sensor interface circuitry. In a calibration mode, the sensor interface circuitry is configured to receive first sensor data from an electroencephalography sensor. The first sensor data are indicative of an electroencephalogram of the user. Further, the sensor interface circuitry is configured to receive second sensor data from a physiological sensor in the calibration mode. The second sensor data are indicative of a physiological property of the user. In the calibration mode, the processing circuitry is configured to train a brain-physiological model for the user based on the first sensor data and the second sensor data.

Biometric enabled virtual reality (VR) systems and methods are disclosed for detecting user intention(s) and modulating virtual avatar control based on the user intention(s) for creation of virtual avatar(s) or object(s) in holographic space, two-dimensional (2D) virtual space, or three-dimensional (3D) virtual space. A virtual representation of an intended motion of a user corresponding to an intention of muscle activation of the user is determined based on analysis of a biometric signal data of the user as collected by a biometric detection device. The virtual representation of the intended motion is used to modulate virtual avatar control or output to create at least one of a virtual avatar representing aspect(s) of the user or an object manipulated by the user in a holographic space, virtual 2D space, or virtual 3D space. The avatar or the object is created based on: (1) the biometric signal data of a user, or (2) user-specific specifications as provided by the user.

[Object] To provide an information processing apparatus, a biological data measurement system, an information processing method, and a program that can improve the accuracy of acquired biological data. [Solving Means] An information processing apparatus according to the present technology includes a body motion noise prediction unit and a control unit. The body motion noise prediction unit predicts, on the basis of a reference signal that is body motion information of a person to be measured detected by a reference signal sensor, that body motion noise caused by body motion of the person to be measured is added to a detection biological signal detected by a biological sensor from the person to be measured. The control unit controls signal processing of the detection biological signal on the basis of a prediction result of the body motion noise prediction unit.

The present invention relates to body position detection. In order to improve body position detection, a computer-implemented method is provided that comprises the steps of: a) receiving (210) accelerometer data from an accelerometer mounted on a user,

wherein the received accelerometer data comprises three acceleration components including a first acceleration component in a first axis direction, a second acceleration component in a second axis direction substantially perpendicular to the first axis direction, and a third acceleration component in a third axis direction substantially perpendicular to a plane formed by the first and second axes; and

wherein the first axis direction is parallel to a frontal axis of the user, the second axis direction is parallel to a longitudinal axis of the user, and the third axis direction is parallel to a sagittal axis of the user; b) determining (220), based on the received accelerometer data, at least one body position based on a comparison between an absolute value of a projection of a gravity vector on a plane formed by two of the first, second, and third axes and an absolute value of an acceleration component in a remaining axis direction.

Motion tracking systems and methods for determining how trackers are positioned on body members of a person, the methods including: wirelessly receiving, by a computing device, one or more first data packets of each tracker; digitally determining a first direction in which the computing device is relative to the respective tracker by computing an angle of departure of the one or more first data packets; digitally determining based on the first directions, a second direction in which each tracker is relative to one or more other trackers; and digitally determining on which body member is each tracker positioned on the person at least based on both the second directions and the body members requiring to have a tracker positioned thereon. Also, systems and methods in which angles of arrival are computed for determining the first directions.

A system and a method are described for monitoring a medical care environment. In one or more implementations, a method includes identifying a first subset of pixels within a field of view of a camera as representing a bed. The method also includes identifying a second subset of pixels within the field of view of the camera as representing an object (e.g., a subject, such as a patient, medical personnel; bed; chair; patient tray; medical equipment; etc.) proximal to the bed. The method also includes determining an orientation of the object within the bed.

In some examples, a device for detecting seizure events can include a non-transitory machine readable medium storing instructions executable by a processing resource to generate a point cloud of an object, monitor a movement of the generated point cloud based on data received from a sensor, and detect a seizure event based on the monitored movement

Methods of measuring biometric characteristics using a sensor positioned in an ear canal of a user are provided. The sensor is positioned on or connected to an ear tip, a contact hearing device, or one or more components thereof. One or more biometric signals may be sensed from the sensor. The biometric characteristic of the user is measured or derived from these sensed signals, and include but are not limited to the temperature of the user, acoustic signal(s) from the user, movement(s) of the user, a ballistocardiogram, an electrocardiogram, oxygen saturation, and blood pressure.

An apparatus for predicting an outcome of a patient includes a processor, and a memory storing computer executable instructions, which when executed by the processor cause the processor to perform operations comprising obtaining patient kinematic data of the patient; deriving one or more patient kinematic features from the patient kinematic data; and determining the outcome based on the one or more patient kinematic features and at least one additional data element of the patient using an outcome model trained on a training set of kinematic features of the same type as the patient kinematic features and the at least one additional data element.

An orthopedic system configured for use in a pre-operative, intra-operative, and post-operative assessment. The orthopedic system comprises a first screw, a second screw, a first device, a second device, and a computer. The first device and the second device are respectively coupled to a first bone and a second bone of a musculoskeletal system. The first and second devices each include electronic circuitry, one or more sensors, and an IMU. A bracket, wrap, or sleeve can be used to hold the first and second devices to the musculoskeletal system. The first and second devices are configured to send measurement data to a computer. The first and second devices each have an antenna system. Electronic circuitry in the first or second devices are configured to harvest energy from a received radio frequency signal to recharge a battery to maintain operation.