Abstract: The sleep monitoring system uses a motion vector estimator to determine motion vectors as a function of location in camera images. A signal processing system with an input coupled to the motion vector estimator computes a measure of turning motion, by summing motion vectors from respective locations within an image. Pose changes are detected based on the measure of turning motion. The measure of turning motion may be computed from a sum of components of the motion vectors that are normal to the major axis of a body area in the image, which is determined based on image content changes in a set of images from the camera. To avoid false turning detection due to leg kicking or similar motion the detected turning motion may be reduced to zero if it is not detected in a sufficiently large part of the body area.

Abstract: A baby monitoring system (10) is provided which gives insight in the sleeping behaviour of a child based on the motion of the child in the bed (1). The baby monitoring system (10) comprises a video camera(11), a motion estimator (21) and a processor (22) to classify the observed motions into events. A set of events gives a parent an insight in the sleeping behaviour of the child.

Abstract: A monitoring system (10) includes at least one video camera (14), a motion unit (40), and a segmentation unit (42). The at least one video camera (14) is configured to continuously receive video of a subject in normal and darkened room conditions. The motion unit (40) identifies clusters of motion of the subject based on respiratory and body part motion in the received video of the subject. The segmentation unit (42) segments body parts of the subject based on the identified clusters of subject motion.

Abstract: The invention relates to methods and apparatus for monitoring movement and breathing of two or more subjects occupying common bedding. Particularly, the invention relates to a method for monitoring movement of subjects located in a common bedding, the method comprising the steps of: —imaging the bedding by an optical sensor; —performing a motion estimation by producing motion vectors indicating the local displacement of corresponding image blocks between consecutive images, or images that are several frames apart, received from said optical sensor; —calculating motion clusters by measuring spatial and temporal correlations of the motion vectors; —segmenting the calculated motion clusters by assignment of each motion cluster to a corresponding subject, wherein the assignment of the motion clusters to the corresponding subject is based on the spatial and/or temporal similarity of the motion clusters among each other and on previous segmentation results.

Abstract: The present invention relates to a device, system and method for automated detection of orientation and/or location of a person. To increase the robustness and accuracy, the proposed device comprises an image data interface (20) for obtaining image data of a person (110), said image data comprising a sequence of image frames over time, a motion detector (21) for detecting motion within said image data, a motion intensity detector (22) for identifying motion hotspots representing image areas showing frequently occurring motion, and a person detector (23) for detecting the orientation and/or location of at least part of the person (110) based on the identified motion hotspots.

Abstract: An electronic switch for controlling a device (170) by switching a function of the device at least in dependency on a sleep stage of a human, the switch comprising an EEG data interface configured to receive brain activity data from an EEG sensor (120) configured to monitor electrical activity of the brain of the human during a training phase, an EEG sleep classifier (125) configured to classify sleep stages of the human from the received brain activity data, a body data interface configured to receive body activity data from an alternative sensor (30) configured to monitor a bodily function of the human both during the training phase and during a subsequent usage phase, the alternative sensor being different from the EEG sensor, an alternative sleep classifier (135) and a machine learning system (140), the machine learning system being configured to train the alternative sleep classifier (135) to classify a sleep stage of the human from the received body activity data, the learning system using sleep stages

Abstract: The invention relates to a method and an apparatus for the detection of the body position, especially while sleeping. More particularly, the invention relates to how the main body positions during sleep can be derived from the distribution of the reflection of a projected IR light from a subject's body under a blanket. Additionally, the breathing signals can be analyzed to determine the body posture.

Abstract: The invention relates to methods and apparatus for monitoring movement and breathing of two or more subjects occupying common bedding. Particularly, the invention relates to a method for monitoring movement of subjects located in a common bedding, the method comprising the steps of:—imaging the bedding by an optical sensor;—performing a motion estimation by producing motion vectors indicating the local displacement of corresponding image blocks between consecutive images, or images that are several frames apart, received from said optical sensor;—calculating motion clusters by measuring spatial and temporal correlations of the motion vectors;—segmenting the calculated motion clusters by assignment of each motion cluster to a corresponding subject, wherein the assignment of the motion clusters to the corresponding subject is based on the spatial and/or temporal similarity of the motion clusters among each other and on previous segmentation results.

Abstract: A method is disclosed for determining anatomical properties of a patient, the patient having an oral cavity and a throat, comprising a) projecting at least one structured light pattern into the patient's oral cavity; b) detecting at least one reflected light pattern, each of the reflected light patterns emanating from reflection of a corresponding projected structured light pattern; c) analysing the at least one reflected structured light pattern in view of the at least one structured light pattern, thereby determining anatomical properties of the patient; and an associated imaging device.

Abstract: The present invention relates to a monitoring system (1, 2, 3) and a corresponding monitoring method for monitoring a patient and detecting delirium of the patient in an unobtrusive manner without the need of on-body sensors. The proposed monitoring system comprises a monitoring unit (10) for obtaining image data (30) of the patient over time, an image analysis unit (12) for detecting motion events of the patient from the obtained image data (30), an evaluation unit (14) for classifying the detected motion events into delirium-typical motion events and non-delirium-typical motion events, and a delirium determination unit (16) for determining a delirium score (32) from the duration, intensity, type, location and/or occurrence of delirium-typical motion events, said delirium score (32) indicating the likelihood and/or strength of delirium of the patient.

Abstract: A hair treatment device is provided comprising a light-based detector (10) for detecting a hair (11) near a skin (12) surface. The light-based detector comprises a light source (13) for emitting optical radiation of at least a first wavelength and with an incident polarization towards the skin surface. A light sensor (14a, 14b) is provided for detecting light reflected at the skin surface. The light sensor (14a, 14b) is capable of separately detecting he reflected light with the incident polarization and with a different polarization and for providing a PP value representing the detected light with the incident polarization and a CP value representing the detected light with the different polarization.

Abstract: Provided are systems (100) and methods (200) for providing contact-less sleep disorder diagnosis, including a sound input device (103) and/or a movement detector (105) that receive sound and/or movement data originating from a patient in a sleeping environment, respectively. Also included is a computer-implemented device (109) that receives and stores the sound and/or movement data and determines a sleep disorder diagnosis based on the received data.

Abstract: The present invention relates to a method and a system for unobtrusively measuring a person's respiration, wherein at least two microphones positioned at either side of a person's bed are steered based on the distance of the persons head to said microphones as computed on the basis of images captured by a video camera.

Abstract: A light therapy device (1) comprises: at least one light source (2); a control device (10) for controlling the operation of the light source; a boundary memory (11) containing boundary information defining boundaries for the distance (D) and relative angle (f) of a user's head with respect to the light source; monitoring means (30) for monitoring the actual distance and actual relative angle of the user's head and generating an output signal indicating the measured distance and angle. The control device has an input coupled to the memory for receiving the boundary information, and has an input coupled to the monitoring means for receiving the output signal from the monitoring means. The control device compares the output signal from the monitoring means with the boundary information, and issues a warning signal when the actual position and/or orientation of the user's head and/or eyes is/are outside said boundaries.

Abstract: The invention relates to a respiratory motion detection apparatus (1) for detecting respiratory motion of a person. An illuminator (3) illuminates the person (2) with an illumination pattern (11), and a detector (4) detects the illumination pattern (11) on the person (2) over time. A temporal respiratory motion signal being indicative of the respiratory motion of the person (2) is determined from the detected illumination pattern by a respiratory motion signal determination unit (5). The illumination pattern deforms significantly with slight movements of the person. Thus, since the respiratory motion signal determination unit (5) is adapted to determine the temporal respiratory motion signal from the detected illumination pattern, even slight respiratory movements of the person can be determined. The sensitivity of detecting respiratory movements of a person can therefore be improved.