The present invention is a respiratory monitoring device which uses 2+ sensors to map respiratory motion in patients to interpret into a respiratory effort and severity score. The core components of the invention are contact-based sensors that measure relative motion of the chest, abdomen, and/or other key anatomical features, a processing unit which takes in the data from all sensors, an algorithm that analyzes and compares the data from each sensor to understand relative motion and interpret it into clinically-relevant information, and a display screen that shares this information with clinicians. The sensors are connected to each other and the information processing unit which shares data with the screen for display of a respiratory severity score based on analysis of Thoraco-Abdominal Asynchrony (TAA) or similar indicators of respiratory effort as measured by the sensor network and analyzed by the algorithm.

Method and systems provide for reliable, convenient, and cost-effective personalized assessment of hemodynamic status in the ambulatory heart failure patient. The method and apparatus use pulse contour analysis of data obtained through observation of the patient for determination of hemodynamic status, and for determination of day-to-day changes in hemodynamic status. Observational assessment of the patient includes monitoring during activities of daily living including sleeping, sitting and standing. These activities create changes in venous return that are used to evaluate cardiac function or changes in cardiac function. The method and system infer body position by using position and motion information obtained by the system. Changes in cardiac function over time or due to changes in body pose are evaluated for the assessment of hemodynamic status, with a focus on changes resulting from fluid overload.

Method and systems provide for reliable, convenient, and cost-effective personalized assessment of hemodynamic status in the ambulatory heart failure patient. The method and apparatus use pulse contour analysis of data obtained through observation of the patient for determination of hemodynamic status, and for determination of day-to-day changes in hemodynamic status. Observational assessment of the patient includes monitoring during activities of daily living including sleeping, sitting and standing. These activities create changes in venous return that are used to evaluate cardiac function or changes in cardiac function. The method and system infer body position by using position and motion information obtained by the system. Changes in cardiac function over time or due to changes in body pose are evaluated for the assessment of hemodynamic status, with a focus on changes resulting from fluid overload.

An imaging device for acquiring a time series of in vivo images of a region of a subject's body is provided. The imaging device includes a energy source, a detector for detecting energy from the energy source passing through the region of the subject's body located between the energy source and detector, a controller configured to operate the energy source and the detector to acquire a time series of in vivo images of the region of the subject's body, a sensor for monitoring a physiological parameter associated with the region of the subject's body to be imaged and a processor configured to determine timing of the image acquisition based at least on the monitored physiological parameter. A method for acquiring a time series of in vivo images of a region of a subject's body using the imaging device is also provided.

A sleep monitoring system has a movement sensing arrangement and a controller for identifying from the movement sensing arrangement output signals sleep-disordered breathing events. Seismocardiography signals are recorded and analyzed to determine repetitive patterns, from which an inter-beat interval time series is derived without identifying specific elements of the repetitive patterns. The sleep-disordered breath events are derived from the inter-beat interval time series. In this way, SCG signals can be used for sleep monitoring in a robust and reliable way.

A sleep monitoring system has a movement sensing arrangement and a controller for identifying from the movement sensing arrangement output signals sleep-disordered breathing events. Seismocardiography signals are recorded and analyzed to determine repetitive patterns, from which an inter-beat interval time series is derived without identifying specific elements of the repetitive patterns. The sleep-disordered breath events are derived from the inter-beat interval time series. In this way, SCG signals can be used for sleep monitoring in a robust and reliable way.

A non-invasive system and method for measuring blood pressure variability includes a cuff (20) pneumatically connected to a pump (14) to inflate the cuff to be wrapped around a limb (21) of a subject. A pressure sensor (18) is associated with the cuff for measuring cuff pressure (52). A photoplethysmogram sensor (26) attached to a fingertip in the same limb (21) of the subject and placed distal to the cuff for monitoring blood flow and recording a pulse plethysmograph signal. A control unit (12) connected to the pressure sensor (18) and the photoplethysmogram sensor (26) for simultaneously recording the cuff pressure and the plethysmograph signal such that an empirical relationship is derived between the cuff pressure and an amplitude measure of the plethysmograph signal (54) to measure short-term variation in systolic and diastolic blood pressures at a frequency corresponding to respiratory cycle.

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 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.

Example embodiments include devices and systems that detect apnea events of a user. The device includes a first sensor configured beside the head of the user for capturing snoring sounds of the user, a second sensor configured on one finger of the user for capturing cardiovascular parameters of the user, a third sensor configured under the trunk of the user for capturing e breathing movements of the user, a data recorder that is connected with the first sensor, the second sensor and the third sensor for receiving recordings therefrom, and a clock for synchronizing the recordings in real time. The recordings include one or more breathing events including snoring events, heart rate and SPO.sub.2 conjunction spikes, and breathing movement cessations. The time periods that apnea events are impossible can be excluded according to a combination of the breathing events, and the apnea events can be detected thereafter.