Abstract: In one embodiment, an apparatus is presented that receives a driving style of a driver, senses a parameter or parameters of a driver and/or at least one passenger within a vehicle, correlates the parameter(s) to the driving style, and triggers feedback to the driver of the correlated parameter(s) of the at least one passenger or to the passenger of the correlated parameters parameter(s) of the driver. The invention provides, among other features, a mechanism to increase positive interactions between the driver and the passenger(s) and to decrease or avoid negative interactions, which leads to a safer use of the vehicle based on the correlations between measured health/well-being data and driving style or behavior.

Abstract: The present disclosure pertains to a system and method for delivering sensory stimulation to a user during a sleep session. The system comprises one or more sensors, one or more sensory stimulators, and one or more hardware processors. The processor(s) are configured to: determine one or more brain activity parameters indicative of sleep depth in the user based on output signals from the sensors; cause a neural network to indicate sleep stages predicted to occur at future times for the user during the sleep session; cause the sensory stimulator(s) to provide the sensory stimulation to the user based on the predicted sleep stages over time during the sleep session, and cause the sensory stimulator(s) to modulate a timing and/or intensity of the sensory stimulation based on the one or more brain activity parameters and values output from one or more intermediate layers of the neural network.

Abstract: The present disclosure pertains to a system configured to facilitate prediction of a sleep stage and intervention preparation in advance of the sleep stage's occurrence. The system comprises sensors configured to be placed on a subject and to generate output signals conveying information related to brain activity of the subject; and processors configured to: determine a sample representing the output signals with respect to a first time period of a sleep session; provide the sample to a prediction model at a first time of the sleep session to predict a sleep stage of the subject occurring around a second time; determine intervention information based on the prediction of the sleep stage, the intervention information indicating one or more stimulator parameters related to periheral stimulation; and cause one or more stimulators to provide the intervention to the subject around the second time of the sleep session.

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 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: 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: A device, system and method automatically detects orientation and/or location of a person. To increase the robustness and accuracy, the device includes an image data interface (20) for obtaining image data of a person (110), which image data includes 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: 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: 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: In one embodiment, a wearable device comprising one or more sensors is presented that receives one or more physiological parameters of a user sensed by the one or more sensors and causes adjustment of one or more vehicle parameters based on the one or more physiological parameters.

Abstract: 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 head are utilized based on a distance of the persons head to the microphones and an identification of which microphone is in a line of sight and which is out of the line of site of the person's breathing as computed on the basis of images captured by a video camera.

Abstract: There is provided a restraint management apparatus. The restraint management apparatus comprises a processing unit arranged to: receive one or more types of sensor data; determine a status of a subject based on the received sensor data; determine, based on the determined subject status, a restraint parameter for a restraint device configured to restrain a body part of the subject; and output a signal based on the determined restraint parameter.

Abstract: There is provided a context detection apparatus for use with a medical monitoring device arranged to measure a physiological characteristic of a subject. The context detection apparatus comprises at least one context sensor comprising a camera; and a processing unit. The processing unit is arranged to receive image data acquired by the camera from the at least one context sensor; analyze the received image data to generate a plurality of different types of context information; wherein each type of context information comprises information which relates to a factor capable of influencing measured values of the physiological characteristic and which is not measurable by the medical monitoring device; and output a signal to the medical monitoring device based on the generated context information.

Abstract: A sleep monitor for monitoring baby sleep uses sleep state classification based on heartbeat feature respiration features. The sleep monitor automatically retrains the classification during use of the sleep monitor. Training examples for use in this training process are generated automatically by detecting time instants whereat the baby in the bed is in a wake state, based on signals from the at least one of a sound feature detector a movement feature detector (112) and an open eye detector (114). The retraining may comprise using time sequence from the end of detection of wake states to assign a class to heartbeat feature and/or respiration feature values during that time sequence for the training process. In an embodiment, the retraining comprises clustering detected heartbeat feature and/or respiration feature values detected outside the detected wake states.

Abstract: An electronic switch for controlling a device 170 by switching a function of the device at least in dependence on a sleep stage of a human. The switch includes 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, and a body data interface configured to receive body activity data from an alternative sensor 130 configured to monitor a bodily function of the human both during the training phase and during a subsequent usage phase.

Abstract: The invention provides a patient monitoring system for monitoring a patient in a bed. A video camera is used for capturing video images of the patient. Video analysis is used to determine and track the position of body parts of the patient including the hands. This analysis is enhanced by using sensors which detect interaction by the patient with pieces of equipment in the vicinity of the bed.

Abstract: The present invention relates to a device for detecting a health condition of a subject (15), comprising a data interface (12) for receiving sensor data (14) of said subject (15) and one or more disease classification parameters (16) for characterizing one or more diseases, a user interface (18) for receiving a user input (20) related to a disease activity, an analysis unit (26) for extracting one or more physiological and/or behavioral features from said received sensor data (14), an optimizer unit (28) for optimizing said one or more disease classification parameters (16) based on a correlation analysis between said one or more physiological and/or behavioral features and said user input (20), and a detection unit (30) for detecting a health condition of said subject (15) by applying said one or more disease classification parameters (16) to said one or more physiological and/or behavioral features.

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: 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: A delirium detection system for automatic, unobtrusive and reliable detection of delirium of a person comprises a processor and a computer-readable storage medium, wherein the computer-readable storage medium contains instructions for execution by the processor. The instructions cause the processor to perform the steps of controlling a stimulus unit to output a stimulus for stimulating the person, receiving and evaluating one or more reaction signals captured by a reaction unit and reflecting the person's reaction to a stimulus, and determining a delirium score from said evaluation of one or more reaction signals.