A pulmonary neuromuscular metrics device that allows the measurement of pulmonary neuromuscular metrics, that is, breathing power, force, and work (that is, energy expended), in patients with neuromuscular conditions. The device may be used in the medical office or remotely at a patient's house, thereby allowing the patient to be followed medically without the need for more frequent and repeated office visits.

The present disclosure describes a sleep staging system. The system comprises: one or more sensors configured to generate output signals conveying information related to breathing parameters of subject during a respiratory therapy session; and one or more physical computer processors configured by computer readable instructions to: determine, based on the output signals, one or more breathing features of individual breaths of the subject; determine a distribution of the one or more breathing features over a plurality of time windows, at least one of the time windows having a length of at least 60 seconds; determine sleep states of the subject by mapping the distribution of the breathing features to one or more sleep states using a sleep stage classifier model, the sleep stage classifier model configured to determine the sleep states; and provide feedback indicating the sleep states during the respiratory sleep session.

The present disclosure describes a sleep staging system. The system comprises: one or more sensors configured to generate output signals conveying information related to breathing parameters of subject during a respiratory therapy session; and one or more physical computer processors configured by computer readable instructions to: determine, based on the output signals, one or more breathing features of individual breaths of the subject; determine a distribution of the one or more breathing features over a plurality of time windows, at least one of the time windows having a length of at least 60 seconds; determine sleep states of the subject by mapping the distribution of the breathing features to one or more sleep states using a sleep stage classifier model, the sleep stage classifier model configured to determine the sleep states; and provide feedback indicating the sleep states during the respiratory sleep session.

The present invention relates to an integrated sleep diagnosis and treatment device, and more particularly to an integrated apnea diagnosis and treatment device. The present invention additionally relates to method of sleep diagnosis and treatment.

The present invention relates to an integrated sleep diagnosis and treatment device, and more particularly to an integrated apnea diagnosis and treatment device. The present invention additionally relates to method of sleep diagnosis and treatment.

A non-invasive method and system is provided for determining an internal component of respiratory effort of a subject in a respiratory study. Both a thoracic signal (T) and an abdomen signal (A) are obtained, which are indicators of a thoracic component and an abdominal component of the respiratory effort, respectively. A first parameter of a respiratory model is determined from the obtained thoracic signal (T) and the abdomen signal (A). The first parameter is an estimated parameter of the respiratory model that is not directly measured during the study. The internal component of the respiratory effort is determined based at least on the determined first parameter of the respiratory model. The first model parameter is determined based on the thorax signal (T) and the obtained abdomen signal (A) without an invasive measurement.

A non-invasive method and system is provided for determining an internal component of respiratory effort of a subject in a respiratory study. Both a thoracic signal (T) and an abdomen signal (A) are obtained, which are indicators of a thoracic component and an abdominal component of the respiratory effort, respectively. A first parameter of a respiratory model is determined from the obtained thoracic signal (T) and the abdomen signal (A). The first parameter is an estimated parameter of the respiratory model that is not directly measured during the study. The internal component of the respiratory effort is determined based at least on the determined first parameter of the respiratory model. The first model parameter is determined based on the thorax signal (T) and the obtained abdomen signal (A) without an invasive measurement.

The present invention provides a method of conducting a sleep analysis by collecting physiologic and kinetic data from a subject, preferably via a wireless in-home data acquisition system, while the subject attempts to sleep at home. The sleep analysis, including clinical and research sleep studies and cardiorespiratory studies, can be used in the diagnosis of sleeping disorders and other diseases or conditions with sleep signatures, such as Parkinson's, epilepsy, chronic heart failure, chronic obstructive pulmonary disorder, or other neurological, cardiac, pulmonary, or muscular disorders. The method of the present invention can also be used to determine if environmental factors at the subject's home are preventing restorative sleep.

A breath analyzer for detecting breathing events of a person ventilated with a respiratory gas, comprising an electronic computing and storage unit configured to receive a signal corresponding to a ventilation pressure and/or a respiratory flow and/or a tidal volume of the respiratory gas delivered to the person and, during a predetermined analysis duration, to detect a curve of the signal by a curve analyzer. A ventilator for ventilating a person with a respiratory gas, which ventilator comprises the breath analyzer and a method for detecting breathing events of a person ventilated with a respiratory gas is also described.

Systems for evaluating the respiratory function of an individual using forced oscillation technique (FOT) oscillometry include a blower controlled so as to apply FOT pressure oscillations on top of a low amplitude offset pressure. A controller continually adjusts the rotational speed of the blower to maintain a targeted time-varying pressure profile in the breathing air provided to the patient.