An apparatus comprises an activity monitor for measuring physical activity of a subject. The activity monitor is configured to obtain a first set of physical activity data over a first time period, for example during the day, and a second set of physical activity data over a second time period, for example during the night. A processor processes the data obtained by the activity monitor to calculate a physical activity ratio which is the ratio of the physical activity measured during the first time period to the physical activity measured in the second time period. The processor also calculates a first overall value which represents an activity level of the subject during the first time period. The physical activity ratio together with the first overall value may be used to assess the severity of symptoms of COPD displayed by a subject or to identify respiratory disease comorbidity information for example psychological issues such as low motivation, or sleep quality issues displayed by the subject.

An apparatus comprises an activity monitor for measuring physical activity of a subject. The activity monitor is configured to obtain a first set of physical activity data over a first time period, for example during the day, and a second set of physical activity data over a second time period, for example during the night. A processor processes the data obtained by the activity monitor to calculate a physical activity ratio which is the ratio of the physical activity measured during the first time period to the physical activity measured in the second time period. The processor also calculates a first overall value which represents an activity level of the subject during the first time period. The physical activity ratio together with the first overall value may be used to assess the severity of symptoms of COPD displayed by a subject or to identify respiratory disease comorbidity information for example psychological issues such as low motivation, or sleep quality issues displayed by the subject.

A method and apparatus for extracting a breathing rate estimate from video images of a respiring subject. Signals corresponding to the spatial coordinates of feature points tracked through the video sequence are filtered and excessively large changes are attenuated to reduce movement artefacts. The signals are differentiated and signals which correlate most strongly with other signals are selected. The selected signals are subject to principal component analysis and the best quality of the top five principal components is selected and its frequency is used to calculate and output a breathing rate estimate. The method is particularly suitable for detecting respiration in subject in secure rooms where the video image is of substantially the whole room and the subject is only a small part of the image, and maybe covered or uncovered.

A method and apparatus for extracting a breathing rate estimate from video images of a respiring subject. Signals corresponding to the spatial coordinates of feature points tracked through the video sequence are filtered and excessively large changes are attenuated to reduce movement artefacts. The signals are differentiated and signals which correlate most strongly with other signals are selected. The selected signals are subject to principal component analysis and the best quality of the top five principal components is selected and its frequency is used to calculate and output a breathing rate estimate. The method is particularly suitable for detecting respiration in subject in secure rooms where the video image is of substantially the whole room and the subject is only a small part of the image, and maybe covered or uncovered.

The present invention is in the field of screening techniques for pulmonary conditions. In particular, the present invention provides systems and methods for screening a subject for the presence of pulmonary conditions. A system comprises a sensor unit configured for registering an expansion of a thorax of a subject, the system being configured for determining from data outputted by the sensor unit a local expansion of the thorax and an internal airflow distribution of the lungs of the subject.

Disclosed are systems, devices and methods for providing proximity awareness to an anatomical feature while navigating inside a patient's chest, an exemplary method including receiving image data of the patient's chest, generating a three-dimensional (3D) model of the patient's chest based on the received image data, determining a location of the anatomical feature based on the received image data and the generated 3D model, tracking a position of an electromagnetic sensor included in a tool, iteratively determining a position of the tool inside the patient's chest based on the tracked position of the electromagnetic sensor, and indicating a proximity of the tool relative to the anatomical feature, based on the determined position of the tool inside the patient's chest.

Magnetic resonance imaging utilizing a continuous spoiled gradient echo sequence with 3D radial trajectory and 1D self-gating for respiratory motion detection can be used to characterize respirator motion in the abdomen. The resulting image data is acquired and is retrospectively sorted into different respiratory phases based on their temporal locations within a respiratory cycle, and each phase is reconstructed via a self-calibrating conjugate gradient sensitivity encoding (CG-SENSE) program.

Magnetic resonance imaging utilizing a continuous spoiled gradient echo sequence with 3D radial trajectory and 1D self-gating for respiratory motion detection can be used to characterize respirator motion in the abdomen. The resulting image data is acquired and is retrospectively sorted into different respiratory phases based on their temporal locations within a respiratory cycle, and each phase is reconstructed via a self-calibrating conjugate gradient sensitivity encoding (CG-SENSE) program.

A biological signal of a subject is acquired so as to calculate biological information from the acquired biological signal. When the biological information has been determined to be anomaly, whether the biological information is one that was calculated under a high-accuracy condition is determined. When the biological information is determined to be one that was calculated under the high-accuracy condition, a notice is given based on a first criterion. In the other cases, a notice is given based on a second criterion. Thereby, it is possible to provide an abnormality notification system that can give a necessary notification appropriately while suppressing unnecessary notification, by changing the criteria for notification in accordance with the accuracy of the determined biological information when the biological information of the subject was determined to be anomaly.

The present application describes a computerized reward system based on decentralized ledger block-chain technology for rewarding user behaviour beneficial to health. The system is comprised by a monitoring unit (2) that includes sensor means adapted to collect physical parameters (6) from a user (1), in order to create a physical activity record (3), a validation unit (4) with processor means programmed to correlate the parameters of the physical activity record (3) in order to detect the execution of a physical activity by the user (1) and a reward dispensing system (5) comprising a peer-to-peer network configured to manage a decentralized ledger blockchain distributed computing platform for inter-node communication. Said reward dispensing system (5) is programmed to generate and distribute peer-to-peer digital asset rewards (8) in case of detection of a valid physical activity (7) executed by the user (1).