A wearable device is provided. The wearable device includes a memory configured to store instructions, at least one display having a display area, a frame configured to support the at least one display, the frame including a nose pad in contact with a part of a user's body wearing the wearable device, a photoplethysmography (PPG) sensor exposed through at least a portion of the frame in contact with other part of the user's body, at least one microphone disposed in the nose pad, and a processor. The processor, when executing the instructions, is configured to identify a breathing state of the user, based at least in part on first data acquired through the PPG sensor and second data acquired through the at least one microphone.

A system for noninvasive extraction, identification, and marking of the heart valve signals to evaluate and monitor elevated left ventricular end-diastolic pressure (LVEDP) or pulmonary capillary wedge pressure (PCWP) using at rest assessment of hemodynamic performance, based on quantitative measurements of heart and lung related parameters and cardiac events for diagnostic and therapeutic purposes includes one or more signals from one or more noninvasive sensors or transducers that measure one or more physiological effects that are correlated with cardiopulmonary functions, transmission of the data to a computing device and analysis software where a trained algorithm processes the data to determine the state or condition of elevated LVEDP or PCWP and provides an output indicative of the state or condition of the analysis. The described noninvasive cardiopulmonary health assessment and monitoring systems and methods can provide effective at-home self-assessment or an integrated telehealth remote patient monitoring (RPM) system.

A method of distinguishing sleep period states that a person experiences during a sleep period, the method comprising: using a non-contact microphone to acquire a sleep sound signal representing sounds made by a person during sleep; segmenting the sleep sound signals into epochs; generating a sleep sound feature vector for each epoch; providing a first model that gives a probability that a given sleep period state experienced by the person in a given epoch exhibits a given sleep sound feature vector; providing a second model that gives a probability that a first sleep period state associated with a first epoch transitions to a second sleep period state associated with a subsequent second epoch; and processing the feature vectors using the first and second models to determine a sleep period state of the person from a plurality of possible sleep period states for each of the epochs.

A filtering method includes the following steps: receiving an sound signal; decomposing the sound signal into a primary lung sound signal and a reference heart sound signal; adjusting the reference heart sound signal according to a weighted value to generate an adjusted heart sound signal; and subtracting the adjusted heart sound signal from the primary lung sound signal to generate a filtered lung sound signal.

An infant sleep device may include a platform for supporting an infant, a base upon which the platform is supported, and one or more weight sensors positioned to measure weight of an infant positioned on the platform.

An acoustic sensor is configured to provide accurate and robust measurement of bodily sounds under a variety of conditions, such as in noisy environments or in situations in which stress, strain, or movement may be imparted onto a sensor with respect to a patient. Embodiments of the sensor provide a conformable electrical shielding, as well as improved acoustic and mechanical coupling between the sensor and the measurement site.

A physiological monitor is provided for determining a physiological parameter of a medical patient with a multi-stage sensor assembly. The monitor includes a signal processor configured to receive a signal indicative of a physiological parameter of a medical patient from a multi-stage sensor assembly. The multi-stage sensor assembly is configured to be attached to the physiological monitor and the medical patient. The monitor of certain embodiments also includes an information element query module configured to obtain calibration information from an information element provided in a plurality of stages of the multi-stage sensor assembly. In some embodiments, the signal processor is configured to determine the physiological parameter of the medical patient based upon said signal and said calibration information.

A method and apparatus for monitoring vital signs, such as cardiopulmonary activity, using a ballistograph are provided. The method and apparatus may be used to monitor an infant sleeping in a crib, a patient in a hospital, a person with a chronic disease at home or in professional care, or a person in an elder-care setting.

A method for monitoring feeding maturation in premature babies, the method including measuring an acoustic response from a baby during a selected time period to provide acoustic information; comparing the measured acoustic response against a train data set to determine an indication of a swallow event; and measuring a respiration pattern of the baby during a swallow cycle using a peak and valley model to provide respiration data, where a feeding maturity of the baby is determinable in dependence on the swallow indication and respiration data.

A method of monitoring physiological conditions including an acoustic measurement device and a remote controller. The remove controller configured to measure physiological conditions; calculate absolute tidal volume, a direction of tidal volume, and a rate of change of tidal volume; correlate absolute tidal volume, a direction of tidal volume, and a rate of change of tidal volume to a risk score; calculate a direction trend and rate of change for each physiological condition; correlate the direction trend and rate of change for each physiological condition; detect predefined patterns in the direction trend and rate of change of the measured physiological condition at the predetermined interval; and generating at least one from the group consisting of an alert, an alarm, and a medical treatment if the risk score defined on the predefined scale exceeds a first predetermined risk score threshold and at least one predefined pattern is detected.