A lung sound analysis system includes an acquisition means for acquiring time-series acoustic signals including lung sounds of a subject who is a heart failure patient, a determination means for determining a pause phase of breathing of the subject, a dividing means for dividing the time-series acoustic signals into those in a period of the pause phase of breathing of the subject and those in a period other than the pause phase, according to a result of the determination, and a detection means for detecting abnormality in the lung sounds from the time-series acoustic signals in the period other than the pause phase after the division.

A swallowing evaluation system (1) includes an ultrasound probe (2), an image acquisition unit that acquires an ultrasound image in a pharynx of a subject by transmitting and receiving an ultrasound beam using the ultrasound probe (2), a sound acquisition unit that acquires a swallowing sound of the subject, and an evaluation unit (19) that evaluates swallowing of the subject using machine learning with a combination of the ultrasound image acquired by the image acquisition unit and the swallowing sound acquired by the sound acquisition unit.

A swallowing evaluation system (1) includes an ultrasound probe (2), an image acquisition unit that acquires an ultrasound image in a pharynx of a subject by transmitting and receiving an ultrasound beam using the ultrasound probe (2), a sound acquisition unit that acquires a swallowing sound of the subject, and an evaluation unit (19) that evaluates swallowing of the subject using machine learning with a combination of the ultrasound image acquired by the image acquisition unit and the swallowing sound acquired by the sound acquisition unit.

The invention relates generally to various systems, tools and methods for acquiring diagnostic information, including medical information, for a user, transmitting the information to a remote location, assessing the information, and transmitting resulting diagnosis and treatment information to the user and/or a third party for subsequent action. The present invention provides consumer and user-friendly telemedicine systems and procedures which enable health services and/or diagnosis to be provided at a distance remotely.

In at least one example, a medical device is provided. The medical device includes at least one therapy electrode, at least one electrocardiogram (ECG) electrode, at least one acoustic sensor, and at least one processor coupled with the at least one acoustic sensor, the at least one ECG electrode, and the at least one therapy electrode. The at least one processor can receive at least one acoustic signal from the at least one acoustic sensor, receive at least one electrode signal from the ECG electrode, detect at least one unverified cardiopulmonary anomaly using the at least one electrode signal, and verify the at least one unverified cardiopulmonary anomaly with reference to data descriptive of the at least one acoustic signal.

A method of identifying respiratory anomalies includes obtaining respiratory data over a first time period and a second time period that is different than the first time period, identifying at least one type of sound associated with respiration in the respiratory data over the first time period, identifying the at least one type of sound associated with respiration in the respiratory data over the second time period, and identifying abnormal respiration based on a comparison of the at least one type of sound associated with respiration in the respiratory data over the first time period to the at least one type of sound associated with respiration in the respiratory data over the second time period. The at least one type of sound associated with respiration in the respiratory data over the first time period is identified using a first set of features generated by a first processing method.

A method and device for detecting phrenic nerve stimulation (PNS) in, or using, a cardiac medical device. A test signal sensitive to contraction of a diaphragm of a patient may be sensed and signal artifacts of the test signal within each of a first window of the test signal prior to a predetermined cardiac signal and a second window of the test signal subsequent to the predetermined cardiac signal may be determined. The PNS beat criteria may be evaluated, for example, using the test signal, which may be a heart sounds signal.

Methods and apparatus provide monitoring of a sleep disordered breathing state of a person such as for screening. One or more sensors may be configured for non-contact active and/or passive sensing. The processor(s) (7304, 7006) may extract respiratory effort signal(s) from one or more motion signals generated by active non-contact sensing with the sensor(s). The processor(s) may extract one or more energy band signals from an acoustic audio signal generated by passive non-contact sensing with the sensor(s). The processor(s) may assess the energy band signal(s) and/or the respiratory efforts signal(s) to generate intensity signal(s) representing sleep disorder breathing modulation. The processor(s) may classify feature(s) derived from the one or more intensity signals to generate measure(s) of sleep disordered breathing. The processor may generate a sleep disordered breathing indicator based on the measure(s) of sleep disordered breathing. Some versions may evaluate sensing signal(s) to generate indication(s) of cough event(s) and/or cough type.

Examples of systems and methods described herein may classify agonal breathing in audio signals produced by a user using a trained neural network. Examples may include a smart device that may request medical assistance if an agonal breathing event is classified.

A ventilation monitoring system for assisting in proper placement of an endotracheal tube in a subject includes: a capnography sensor configured to be placed in fluid communication with the endotracheal tube and to provide information representative of the subject's breath; and a processor in communication with the capnography sensor. The processor is configured to provide an indication of proper endotracheal tube placement when (1) a first indication of the subject's breath and a positive result of a first auscultation are identified within a first predetermined time period, and (2) a second indication of the subject's breath and a positive result of a second auscultation are identified within a second predetermined time period. The first auscultation includes auscultation of a subject's left lung, right lung, left axillary region, right axillary region, or abdomen. The second auscultation includes auscultation of another region of the subject different from the first auscultation.