Described herein are multifunctional smart beds and methods of operating thereof. Specifically, a multifunctional smart bed comprises a controller, configured to receive input from various sensors (e.g., load cells positioned in bed legs, thermometers, and/or microphones) and/or user. These inputs are analyzed and used to control various bed components to improve the sleep quality, to monitor users' health, score couple's relationship, and the like. For example, these inputs may be used to control the firmness of different mattress portions, change orientations of the head, torso, and/or leg sections, adjust the light, and the like. In some examples, the smart bed generates a report indicating one or more sleep duration, sleep depth profile, sleep scope, heart rate, breath rate, environment conditions, couple's relationship, and the like. Furthermore, in some examples, a multifunctional smart bed is also configured to control external devices in the same environment, e.g., smart switches, smart thermostats.

A system and method using a microphone to collect sound data produced by a potential patient's respiration and speech. The system preferably uses a microphone on a portable electronic device—such as a smart phone. The analysis of the collected data is preferably performed locally—such as by a software application running on the smartphone. The software is used to analyze the data and therefore determine and track useful parameters such as respiration rate and respiratory tidal volume. The software also analyzes phonation patterns. Using the parameters, the inventive system can detect the onset of respiratory distress.

A method of estimating a number of lung function indices of an individual. The method includes: transmitting an ultrasound signal toward a chest of the individual from a speaker of a smartphone while the individual is holding the smartphone in a hand of the individual; receiving in a microphone of the smartphone a reflected signal reflected from the chest of the individual in response to the ultrasound signal; extracting a number of features from the reflected signal; and providing the number of features to a neural network regression model, wherein the neural network regression model estimates the number of lung function indices based on the number of features and based on a non-linear correlation between chest wall motion and human lung function.

The disclosure is directed to a sensing device, configured to be installed in a bedding, for monitoring a user's sleep, the device comprising: a sensing part, for acquiring/determining a value representative of an a force or pressure and/or a value representative of a variation of a force or pressure, a housing comprising at least a pressure transducer and an electronic processing unit, a microphone connected to the electronic processing unit, wherein the electronic processing unit is configured to process first and second electrical signals delivered respectively by the microphone and the pressure converter, wherein the electronic processing unit is either configured to deduce locally at least a breathing disturbance therefrom or configured to send data representative of the first and second electrical signals to a remote device.

A system for monitoring sepsis comprises one or more sensors that noninvasively monitor a patient to produce sensor data and processing circuitry to: derive, from the sensor data, one or more physiological parameters of the patient that are indicative of a sepsis state of the patient; apply a set of rules to the one or more physiological parameters; determine a sepsis state for the patient based on the set of rules applied to the one or more physiological parameters; and output at least one signal indicative of the sepsis state of the patient. The system includes an output device that outputs a notification based on the at least one signal.

Apparatus for medical screening includes a plurality of acoustic transducers, which are configured to sense acoustic waves emitted from a body of a subject and to output signals in response thereto. A frame is configured to position the acoustic transducers in proximity to a thorax of the subject, so that the acoustic transducers receive the acoustic waves emitted from different, respective locations on the thorax. Processing circuitry is configured to collect and process the signals so as to assess a respiratory condition of the subject and to issue an alarm upon detecting a pathological respiratory condition, such as a suspicion of COVID-19.

A method and apparatus for detecting a respiratory function are provided. The method includes training a plurality of classification models, receiving a breathing sound by a sound receiver to generate a breathing signal, and classifying the breathing signal by each of the trained classification models to obtain a classification result corresponding to each of the classification models.

A system comprising a remotely programmable micromonitor with a wireless sensing system-on-module (SOM), one or more sensors to detect one or more conditions in a subject by monitoring one or more parameters associated with the conditions by comparing any monitored parameter to a baseline measurement of the monitored parameter from the subject, a plurality of sensors corresponding to a monitored parameter and connected to the micromonitor to convey measurements of all monitored parameters, the sensors including at least one of a non-optical pulse wave sensor or an electrocardiogram (ECG) sensor, a communications module capable of communicating with a wireless technology, wherein the module can send an alert signal to the subject or an attending physician or a remote service center or any other subject, and one or more algorithms for monitoring conditions and/or for predicting conditions, including at least one of a fall detection or fall prediction algorithm.

This document discusses, among other things, systems and methods to determine an indication of contractility of a heart of a patient using received physiologic information, and to determine blood pressure information of the patient using the heart sound information and the determined indication of contractility of the heart. The system can include an assessment circuit configured to determine an indication of contractility of a heart of the patient using first heart sound (S1) information of the patient, and to determine blood pressure information of the patient using second heart sound (S2) information of the patient and the determined indication of contractility of the heart.

Embodiments of the present disclosure provide systems and methods directed to contactless motion tracking. In operation, a speaker may provide an acoustic signal to, for example, a subject. A microphone array may receive a reflected acoustic signal, where the received reflected signal is responsive to the acoustic signal reflecting off the subject. A computing device may extraction motion data of the subject based on the received reflected acoustic signal. Various motion data extraction methods are described herein. The motion data may include respiration motion, coarse movement motion, respiration rate, and the like. Using the extracted motion data, the processor may identify at least one health condition and/or sleep anomaly corresponding to the subject. In some examples, beamforming is implemented to aid in contactless motion tracking.