A spirometry system includes an imaging device configured to capture upper body movement images of a subject during inhalation and exhalation of the subject. The system further includes at least one controller configured to receive the captured images from the imaging device and, based upon the received images, determine at least one of an image-based spirometry flow-volume curve for the subject or an image-based spirometry parameter for the subject.

Disclosed are biofeedback methods and devices suitable for providing biofeedback useful for helping a user control an own breathing, for example, to help in inducing deep breathing, and such biofeedback devices further comprising a dispenser for dispensing an inhalable substance.

To provide a mask capable of reducing a load of a patient while suppressing lowering of accuracy at which a subject's exhaled air is measured. A mask to be put on a subject's face includes a mask body portion demarcating an internal space in a state of covering part of the subject's face and a cup-shaped nasal cup covering a subject's nose in a state of being arranged inside the internal space, in which the nasal cup includes a first wall portion covering the subject's nose, a second wall portion arranged under the subject's nostrils, and an exhaled air discharge portion guiding an exhaled air from the subject's nose to an exhaled air sensor, and at least part of the exhaled air from the subject's nose is guided toward the exhaled air discharge portion by the second guide portion in a state where the nasal cup covers the subject's nose.

Various embodiments of the disclosed technology present a structural foundation for volumetric flow reconstructions for expiratory modeling enabled through multi-modal imaging for pulmonology. In some embodiments, this integrated multi-modal system includes infrared (IR) imaging, thermal imaging of carbon dioxide (CO.sub.2), depth imaging (D), and visible spectrum imaging. These multiple image modalities can be integrated into flow models of exhale behaviors enable the creation of three-dimensional volume reconstructions based on visualized CO.sub.2 distributions over time, formulating a four-dimensional exhale model which can be used to estimate various pulmonological traits (e.g., breathing rate, flow rate, exhale velocity, nose/mouth distribution, tidal volume estimation, and CO.sub.2 density distributions). Various embodiments also enable the accurate acquisition of numerous pulmonary metrics that are then stored within distributed systems for respiratory data analytics and feature extraction through deep learning embodiments.

An Internet-based disease monitoring system may include a network-based disease sensor device, which is coupled to a sensor, such as a spirometer. A remote server may be coupled to the network-based disease sensor device to provide analysis of input signals from the sensor. The remote server may be able to provide various services for grouping or handling functions relating to such input signals. A service may provide the ability to aggregate input signals from multiple sensors coupled to sensor devices and provide predictive modeling or statistical analysis, which may then be used to adjust future input signals. A service may also contain instructions how to handle billing based on usage of the network-based disease sensor device.

Devices and methods for predicting, identifying and/or managing pneumonia are disclosed and may generally comprise a housing, a mouthpiece in communication with the housing and configured for insertion within a mouth, a temperature sensor positioned within or along the housing, a pulse oximeter sensor positioned along the housing for sensing a heart rate or blood oxygen level, a microphone positioned within or along the housing for obtaining sounds associated with respiration, and a controller configured to receive physiologic parameters including the temperature, heart rate, blood oxygen level, and sounds associated with respiration. The controller can determine a likelihood of contracting pneumonia, a presence of pneumonia, or a status of pneumonia within the user based on deviations from a threshold value which are present in at least two of the physiologic parameters.

An obstructive sleep apnea detection device including an optical engagement surface adapted to engage a user's skin; a light source adapted to emit light from the optical engagement surface; a photodetector adapted to detect light at the optical engagement surface and to generate a detected light signal; a position sensor adapted to determine patient sleeping position; a controller adapted to determine and record in memory blood oxygen saturation values computed from the detected light signal and user position information from the position sensor; and a housing supporting the optical engagement surface, the photodetector, the light source, the position sensor, and the controller.

Provided are concepts for generating an indicator of chronic obstructive pulmonary disease (COPD) in a subject. In particular, an elasticated bag suitable for inflation is utilised, such that a change in a measurable characteristic of the elasticated during exhalation of the subject is detected. The change in the measurable characteristic may be analyzed so as to generate an indicator of COPD. Thus, this indicator may be used by a skilled professional in deciding whether to further investigate the possible presence of COPD.

An Internet-based disease monitoring system may include a miniaturized disease sensor device, which is coupled to a sensor, such as a spirometer, and a transmitter configured to transmit raw input signals from the sensor to a mobile device as cellular voice or text data for forwarding to a remote server. A remote server may be coupled to the network-based disease sensor device to provide analysis of raw input signals from the sensor. The remote server may be able to provide various services for grouping or handling functions relating to such input signals. A service may provide the ability to aggregate input signals from multiple sensors coupled to sensor devices and provide predictive modeling or statistical analysis, which may then be used to adjust future input signals. A service may also contain instructions how to handle billing based on usage of the network-based disease sensor device.

A patient support apparatus, such as a bed, cot, stretcher, or the like, includes a frame, a support surface, an emitter, a detector, and a controller. The emitter and detector are coupled to the patient support apparatus at first and second locations, respectively. The emitter is adapted to emit electromagnetic waves in a direction aimed toward the detector. The detector is adapted to detect the electromagnetic waves emitted from the emitter. The controller is adapted to perform a spectral analysis of the detected electromagnetic waves to determine a parameter associated with the gas exhaled by a patient positioned on the patient support apparatus. The parameter may refer to a carbon dioxide level of gas exhaled by the patient, the patient's respiration rate, the patient's metabolic rate, or the like. The emitter, detector, and controller may alternatively be separate from, but attachable to, and in communication with, the patient support apparatus.