A patient monitoring system to help manage a patient that is at risk of falling is disclosed. The system includes a patient-worn wireless sensor that senses the patient's motion and wirelessly transmits information indicative of the sensed motion to a patient monitor. The patient monitor receives, stores, and processes the transmitted information to determine whether the patient has fallen or is about to fall. Upon such detection, the system can notify the patient's caretakers that the patient has fallen or is about to fall and therefore, is in need of immediate attention.

A patient monitoring system to help manage a patient that is at risk of falling is disclosed. The system includes a patient-worn wireless sensor that senses the patient's motion and wirelessly transmits information indicative of the sensed motion to a patient monitor. The patient monitor receives, stores, and processes the transmitted information to determine whether the patient has fallen or is about to fall. Upon such detection, the system can notify the patient's caretakers that the patient has fallen or is about to fall and therefore, is in need of immediate attention.

A medical system according to embodiments of the present invention includes at least one sensor configured to monitor physiological status of a patient and to generate sensor data based on the physiological status, a user interface device, a processor communicably coupled to the user interface device, the processor configured to: present via the user interface device an array of two or more possible input elements, the input elements each comprising a class of patients or a diagnosis and treatment pathway; receive a selected input element based on a user selection among the two or more possible input elements; acquire the sensor data and process the sensor data to generate physiological data; and present via the user interface screen the physiological data according to a template that is customized for the selected input element.

A method of non-invasively monitoring the respiration of a patient comprises: transmitting ultrasound into the body toward an internal structure of the patient's body, the internal structure being one of the liver, the spleen or a kidney; selecting a depth range; measuring the phase of ultrasound echo signals from the internal structure at multiple points along the depth range for at least a first and a second echo signal, the first and second echo signals being received at different times; detecting the motion of the internal structure within the patient's abdomen by reference to differences in the measured phase between the first and the second echo signals; and thereby monitoring the respiration of the patient by associating movement of the internal structure with movement caused by respiration.

A method of non-invasively monitoring the respiration of a patient comprises: transmitting ultrasound into the body toward an internal structure of the patient's body, the internal structure being one of the liver, the spleen or a kidney; selecting a depth range; measuring the phase of ultrasound echo signals from the internal structure at multiple points along the depth range for at least a first and a second echo signal, the first and second echo signals being received at different times; detecting the motion of the internal structure within the patient's abdomen by reference to differences in the measured phase between the first and the second echo signals; and thereby monitoring the respiration of the patient by associating movement of the internal structure with movement caused by respiration.

Sleep systems having embedded sensors are described. In one aspect, a sleep system includes a mattress and one or more force sensors embedded within the mattress. The force sensors are positioned within the mattress to sense movement of an occupant of the mattress. The sleep system also includes one or more processors coupled with the one or more force sensors. At least one of the processors is configured to determine sleep state information for the occupant based on data obtained from one or more of the force sensors.

Sleep systems having embedded sensors are described. In one aspect, a sleep system includes a mattress and one or more force sensors embedded within the mattress. The force sensors are positioned within the mattress to sense movement of an occupant of the mattress. The sleep system also includes one or more processors coupled with the one or more force sensors. At least one of the processors is configured to determine sleep state information for the occupant based on data obtained from one or more of the force sensors.

A medical image registration method and apparatus are described. By performance of a medical image registration method, a highly accurate registered image, in which breathing deformation information is considered, may be obtained by generation of non-real-time medical images in which the breathing deformation information is reflected before a medical procedure is conducted and by rigid registration of a real-time medical image and the generated non-real-time medical images during the medical procedure.

A medical image registration method and apparatus are described. By performance of a medical image registration method, a highly accurate registered image, in which breathing deformation information is considered, may be obtained by generation of non-real-time medical images in which the breathing deformation information is reflected before a medical procedure is conducted and by rigid registration of a real-time medical image and the generated non-real-time medical images during the medical procedure.

The present invention relates to a device (10, 10a, 10b), system (1, 2, 3) and method for detection of an asthma attack or asthma of a subject. For this purpose, the device comprises a light sensor input (11), e.g. a 2D camera, for obtaining light sensor data of the scene and a thermal sensor input (12), e.g. a thermal camera, for obtaining thermal sensor data of a scene including a subject while breathing. An analysis unit (13) obtains these data and derives respiratory effort information indicating respiratory efforts of the subject from the obtained light sensor data and/or the obtained thermal sensor data and derives airflow information indicating airflow during respiration of the subject from the obtained thermal sensor data. Further, the analysis unit (13) predicts or detects an asthma attack or asthma based on analysis of the respiratory effort information and the airflow information, said analysis evaluating deviations from predetermined or healthy correlations between respiratory efforts and airflow.