Abstract: The present invention relates to a device for detecting motion of a person. The present invention further relates to a system incorporating the aforementioned device and a corresponding method. The proposed device comprises a projection sweep unit configured to obtain image data comprising depth information corresponding to an image showing the patient and to generate one or more projection images of the patient for different viewpoints, a motion detection unit configured to detect motion of the patient in the one or more projection images and to generate one or more motion detection signals indicating if motion is detected or not in a respective projection image, and an analysis unit configured to detect and localize body movements of one or more body parts of the patient based on one or more combinations of motion detection signals.

Abstract: The present invention relates to a device, system and method for object recognition. To improve reliability and robustness of the recognition, the device comprises an input unit (21) configured to obtain a depth image (40) of a scene, a computation unit (22) that computes, from the depth image, a noise variance map (42) by computing pixel noise variances at object boundaries of one or more objects in the depth image, a depth confidence map (43) by filtering depth values based on their distance to the depth camera, and a motion confidence map (44) by filtering out variances caused by motion of a person in the scene. Further, from the noise variance map, the depth confidence map and the motion confidence map, one or more candidate regions (45) and their confidence in the depth image are computed, and the one or more candidate regions having the highest confidence are selected as final region of interest (41) representing the object to be recognized.

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: 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: The present invention relates to a device for detecting motion of a person. The present invention further relates to a system incorporating the aforementioned device and a corresponding method. The proposed device comprises a projection sweep unit configured to obtain image data comprising depth information corresponding to an image showing the patient and to generate one or more projection images of the patient for different viewpoints, a motion detection unit configured to detect motion of the patient in the one or more projection images and to generate one or more motion detection signals indicating if motion is detected or not in a respective projection image, and an analysis unit configured to detect and localize body movements of one or more body parts of the patient based on one or more combinations of motion detection signals.

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: There is provided a method and apparatus for determining a baseline for one or more physiological characteristics of a subject. One or more physiological characteristics of a subject and contextual information associated with the subject is acquired. A time period in which the subject is in a baseline state is detected based on the acquired one or more physiological characteristics of the subject and the acquired contextual information associated with the subject. The baseline for the one or more physiological characteristics of the subject is determined from a value of at least one of the acquired one or more physiological characteristics in the detected time period.

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: 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: 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: 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.

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: 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.