A monitoring system includes a wearable patch device configured to be secured to a body of a patient, the wearable patch device comprising a patch body, a first discrete transducer associated with a first position of the patch body, a second discrete transducer associated with a second portion of the patch body, and a wireless transmitter, and electronics including one or more processors and one or more memory devices and configured to receive signals based on transducer readings of the first and second discrete transducers and determine an amount of blood flow through one or more valves of a heart of the patient based on the signals.

A method and system for extracting cardiac cycle parameters from a respiration signal is disclosed. The technique comprises an array of piezoelectric sensors planted on the chest. The chest membrane exhibits the characteristics of bulky attenuator with certain time delay. Contractions and expansions of the heart and lungs muscles model a mechanical load and produce a relative induced strain on the piezoelectric sheet which in turn causes the piezoelectric material to generate a corresponding conformal voltage signal that is mapped with the heart actions. The resultant voltage signal is therefore used to extract and model the corresponding heart parameters utilizing piezoelectric as well as signal processing theories. a direct relationship is established between the output voltage produced by the piezoelectric transducer under hold breathing and the respiration signal collected by the same transducer with respiration.

A method and system for extracting cardiac cycle parameters from a respiration signal is disclosed. The technique comprises an array of piezoelectric sensors planted on the chest. The chest membrane exhibits the characteristics of bulky attenuator with certain time delay. Contractions and expansions of the heart and lungs muscles model a mechanical load and produce a relative induced strain on the piezoelectric sheet which in turn causes the piezoelectric material to generate a corresponding conformal voltage signal that is mapped with the heart actions. The resultant voltage signal is therefore used to extract and model the corresponding heart parameters utilizing piezoelectric as well as signal processing theories. a direct relationship is established between the output voltage produced by the piezoelectric transducer under hold breathing and the respiration signal collected by the same transducer with respiration.

An adhesive layer applicator for a body-mountable device is disclosed. The applicator includes a housing defining a first opening through which a chamber is accessible, and a plurality of adhesive layers and a plurality of adhesive liners alternately stacked on a floor that is movable within the chamber. The size and shape of the opening corresponds to the size and shape of the body-mountable device. The housing is configured to receive at least a portion of the body-mountable device through the opening. A second opening is formed in each adhesive layer in the plurality of adhesive layers and a gel is accommodated within the second openings.

A monitoring system for determining a user's respiration rate includes a wearable monitoring device for attachment to the user's chest wall. The wearable monitoring device includes a plurality of biometric sensors for generating a plurality of separate biometric data types such as motion data, sound data, and EKG data. A controller is included within the wearable monitoring device and/or is communicatively coupled to the device. The controller is configured to receive the biometric data from the biometric sensors, associate the biometric data of each of the separate biometric data types with one another according to a common sampling timeline to generate a set of multiplexed biometric data, and use the multiplexed biometric data to determine the user's respiration rate.

A monitoring system for determining a user's respiration rate includes a wearable monitoring device for attachment to the user's chest wall. The wearable monitoring device includes a plurality of biometric sensors for generating a plurality of separate biometric data types such as motion data, sound data, and EKG data. A controller is included within the wearable monitoring device and/or is communicatively coupled to the device. The controller is configured to receive the biometric data from the biometric sensors, associate the biometric data of each of the separate biometric data types with one another according to a common sampling timeline to generate a set of multiplexed biometric data, and use the multiplexed biometric data to determine the user's respiration rate.

Disclosed herein are systems, devices, and methods for providing continuous, non-invasive blood pressure monitoring. A wearable monitoring device includes first and second transducer arrays separated by a fixed distance. Each of the transducer arrays includes a plurality of independent transducer elements for transmitting and receiving ultrasound energy. When a user wears the device, the transducers are positioned near the brachial artery. The device operates to measure the transit time of a cardiac pulse through the brachial artery and across the fixed distance between transducer arrays. The measured pulse transit time may then be used for determining pulse wave velocity and/or blood pressure.

Systems and methods for detecting the quality of signals captured by a sensor device monitoring a biological function. Sensor data associated with the sensor device is received, the sensor data representing time-series measurement samples of one or more parameters associated with the biological function, the sensor data including usable and unusable samples of the time-series measurements. Data representing two or more features of samples of the time-series measurements is extracted and filtered to reduce outliers in the extracted data based on an expected outlier ratio. A machine learning algorithm is then trained to identify events based on the filtered extracted data.

Systems and methods for detecting the quality of signals captured by a sensor device monitoring a biological function. Sensor data associated with the sensor device is received, the sensor data representing time-series measurement samples of one or more parameters associated with the biological function, the sensor data including usable and unusable samples of the time-series measurements. Data representing two or more features of samples of the time-series measurements is extracted and filtered to reduce outliers in the extracted data based on an expected outlier ratio. A machine learning algorithm is then trained to identify events based on the filtered extracted data.

A respiratory therapy device that is adapted to matingly connect with two standardized respiratory devices simultaneously to allow for combination, enhanced, single device, respiratory treatments. It monitors the number of PEP treatment events utilizing a motion sensor, and presents a resettable, visual stimulus for each event as well as providing a record of the events in each therapy cycle.