An intelligent and real-time cardio-pulmonary screening device (100) is disclosed. The device comprises a housing that encloses a body, said body comprising: a display unit (101); a plurality of light emitting diode (LED) indicators (102, 103); a first toggle switch (104); a second toggle switch (105); a plurality of volume controls (106, 107); a third toggle switch; an output port (109); a switch (110); a charging port (111); a temperature sensor; a transducer unit (112); and an artificial intelligence module. The artificial intelligence module analyses the sounds received in real-time and presents the results in the display unit (101), as well as in the plurality of the LED indicators (102, 103); it comprises an artificial intelligence processor that is configured to run machine learning algorithms on the device (100), with said artificial intelligence module syncing from and to the cloud when connected to internet. The disclosed device (100) is an easy to use, affordable, point of care screening device that classifies underlying cardio-pulmonary diseases within a minute.

A system and method for continuous readout is provided. The object of the invention is achieved by a contact surface for attaching to a surface of an organism, a sensor system in thermal, mechanical and electrical contact with the contact surface, a radio chip operatively connected to the sensor, wherein the radio chip will respond to an induced signal from a reader by reading data from the sensor and transmit said data, and method for operating the sensor wherein the data from the sensor system is compensated for environmental effects using comprising a second sensor for detecting at least one property from the group comprising ambient temperature, pressure, flow, level, proximity, displacement, bio, image, gas, chemical, acceleration, orientation, humidity, moisture, impedance, capacitance, force, electric, magnetic and mass, thus forming compensated data.

In one aspect, a multi modal body sensor monitoring and recording system includes a personal status monitor (PSM) that communicates user bio-sensor data to an SCP. The PSM includes a controller comprising a sensing face, an intermediary circuit, and a mounting face. The controller provides a sensor array of specified biosensors. The controller is mountable with an ECG patch. The PSM includes an ECG patch coupled with the controller. The controller is removably mounted via comprising a sensor patch comprising a flat piece of material with an array of sensors arranged on a sensing face of the sensor patch of the sensor patch that is designed with a receptacle to which the controller device is connected into the ECG patch. The ECG patch obtains an ECG data o the user that is passed to the controller. The controller electronically communicates the ECG data and the specified biosensor data to the PHI server. The PHI server queries one or more health provider records systems to obtain a set of electronic health records, of the user. The PHI server electronically communicates the set of electronic health records to a system control program (SCP) server. The SCP server uses the biosensor data collected by the PSM, along with the PHI from electronic health records, to construct a virtual model of an individual's quantifiable biological markers in real time.

In one aspect, a multi modal body sensor monitoring and recording system includes a personal status monitor (PSM) that communicates user bio-sensor data to an SCP. The PSM includes a controller comprising a sensing face, an intermediary circuit, and a mounting face. The controller provides a sensor array of specified biosensors. The controller is mountable with an ECG patch. The PSM includes an ECG patch coupled with the controller. The controller is removably mounted via comprising a sensor patch comprising a flat piece of material with an array of sensors arranged on a sensing face of the sensor patch of the sensor patch that is designed with a receptacle to which the controller device is connected into the ECG patch. The ECG patch obtains an ECG data o the user that is passed to the controller. The controller electronically communicates the ECG data and the specified biosensor data to the PHI server. The PHI server queries one or more health provider records systems to obtain a set of electronic health records, of the user. The PHI server electronically communicates the set of electronic health records to a system control program (SCP) server. The SCP server uses the biosensor data collected by the PSM, along with the PHI from electronic health records, to construct a virtual model of an individual's quantifiable biological markers in real time.

The occurrence of a sudden change in physical condition is detected. In a physical condition determination device 100, a heart rate-relate index calculation unit 110 specifies an appearance time of a sign of a sudden change in heart rate, from a time-series waveform of an index corresponding to a variation in the heart rate (heart rate-related index) and a blood pressure-related index calculation unit 120 specifies an appearance time of a sign of a sudden change in blood pressure, from a time-series waveform of an index corresponding to a variation in the blood pressure (blood pressure-related index). A physical condition sudden change determination unit 130 determines that a sudden change in physical condition (physical condition sudden change) has occurred in a case where these appearance times are both within a predetermined time. This enables the determination in which the sudden change in the heart rate and the sudden change in the blood pressure are taken into consideration, to enable the detection of the physical condition sudden change.

A method of monitoring respiration with an acoustic measurement device, the acoustic measurement device having a sound transducer, the sound transducer configured to measure sound associated with airflow through a mammalian trachea, the method includes correlating the measured sound into a measurement of tidal volume and generating at least one from the group consisting of an alert and an alarm if the measured tidal volume falls outside of a predetermined range.

An analysis device includes a detection unit that detects abnormality in lung sounds for each of auscultation positions on the basis of time-series acoustic signals including lung sounds of each of the auscultation positions; a determination unit that determines severity of heart failure of a patient on the basis of a detection result of abnormality in the lung sounds of each of the auscultation positions detected by the detection unit and condition information representing a condition of the patient; and an output unit that decides whether or not to output predetermined information to an external device on the basis of a result of determination by the determination unit, and performs output corresponding to a result of decision.

The present disclosure includes a medical monitoring hub as the center of monitoring for a monitored patient. The hub includes configurable medical ports and serial ports for communicating with other medical devices in the patient's proximity. Moreover, the hub communicates with a portable patient monitor. The monitor, when docked with the hub provides display graphics different from when undocked, the display graphics including anatomical information. The hub assembles the often vast amount of electronic medical data, associates it with the monitored patient, and in some embodiments, communicates the data to the patient's medical records.

Systems and methods for identification and display of airway collapse due to conditions such as tracheomalacia (TM) or dynamic airway collapse (DAC). In an aspect, the technology relates to a method for identifying airway collapse. The method includes emitting, from an acoustic sensor, a series of acoustic pulses into a tracheal tube positioned in an airway of a patient; detecting, by the acoustic sensor, echoes resulting from the series of acoustic pulses; generating, based on the detected echoes, a time series of passageway sizes of the airway; based on the time series of passageway sizes, detecting an airway collapse has occurred; and based on detecting the airway collapse has occurred, activating an airway collapse alarm.

An artificial intelligence-based system and method for scalable screening of individuals for respiratory infection, such as COVID-19. The system is trained to distinguish distinct latent features of cough sounds produced by a COVID-19 infected person from cough sounds produced by patients suffering from any other respiratory infection or involuntary cough sounds produced by a healthy person. Cough sound samples from individuals can be remotely collected and evaluated by the system for likelihood of the COVID-19 infection. Additionally, images of affected body parts, biomarkers, metadata, and other respiratory sound samples can also be used for screening.