Various methods and systems are provided for an automated clinical exam workflow. In one example, method comprises performing a signal quality check of an electronic stethoscope at a first recording location on a subject, recording physiological data for an exam at the first recording location via the electronic stethoscope in response to the signal quality check satisfying a quality threshold, and outputting a signal quality alert in response to the signal quality check not satisfying the quality threshold. In this way, clinically relevant data may be obtained with reduced user effort and fewer manual inputs.

A method is provided that includes receiving an accelerometer signal from an accelerometer in a headphone configured to be mounted in a user's ear canal and filtering the accelerometer signal to extract a cardiac signal. The method further includes detecting a plurality of peaks in the cardiac signal and determining a cardiac rate of the user based on the detected plurality of peaks.

Described herein are a computer enhanced medical method and device for generating an asthmatic condition indication. The apparatus receives a lung signal from a stethoscope, the lung signal having been converted from an analog signal to a digital signal. Furthermore, circuitry included in the apparatus performs, inter alia, the following: displays a patient recording canvas corresponding to physical locations on a body of the patient, the canvas including an anterior patient orientation and a posterior patient orientation, generates a recording process, the recording process including recording, for a predetermined period of time, the detected lung signal, and associates the recording with a marked location. Furthermore, the circuitry merges the recorded lung signal from each marked location on the patent recording canvas as merged information, and applies processing to the merged information to generate the asthmatic condition indication.

A self-auscultation device and method of using the self-auscultation device to listen to a target anatomy is described. The self-auscultation device includes a chest piece to receive a listening device, such as an earphone. The listening device is mounted in the chest piece to detect a sound from the target anatomy, through the chest piece. The listening device can operate in a self-auscultation mode to adapt the listening device to generate audio data corresponding to the detected sound. An equalization filter can be applied to the audio data to compensate for a frequency response of the listening device. A data processing system can compare the audio data to predetermined auscultation data to determine a health condition of the target anatomy. Other embodiments are also described and claimed.

A lightweight inflatable vest is provided with embedded listening devices. Once inflated, the vest enables a physician to hear amplified lung sounds and heart beats and rhythms of a patient wearing the vest, via connection to a smart phone application, through a patient portal, or the like. By using the device on a patient, a physician is provided with an accurate way to perform a respiratory and heart health assessment of the patient during a telehealth visit.

A metallic diaphragm disk incorporating a piezoelectric material bonded thereto and operatively coupled to a base rim of a housing provides for closing an open-ended cavity at the first end of the housing. At least one inertial mass is either incorporated in or attached to the housing. A plastic film adhesively bonded to at least one of an outer rim of the housing or an outer-facing surface of the disk provides for receiving an adhesive acoustic interface material to provide for coupling the housing to the skin of a test subject.

A snoring sound detection apparatus includes one or plural microphones that receive sounds produced by a subject, and a controller including circuitry which converts the sounds produced by the subject to received signals, converts the received signals to sound intensity signals, measures the periodicity of sound intensity signal using one or plural sound intensity signals, evaluates the validity of the periodicity of sound intensity signal in terms of respiratory rate, and detects snoring sound using the sound intensity and the validity of the periodicity of sound intensity signal in terms of respiratory rate.

A method for medical diagnosis includes recording voice signals due to sounds spoken by a patient and recording acoustic signals output, simultaneously with the voice signals, by an acoustic transducer in contact with a thorax of the patient. A transfer function is computed between the recorded voice signals and the recorded acoustic signals or between the recorded acoustic signals and the recorded voice signals. The computed transfer function is evaluated in order to assess a medical condition of the patient.

An electronic device is provided. The electronic device includes a biometric sensor for detecting biometric data, a situation sensing module, memory, and a processor operatively coupled to the biometric sensor, the situation sensing module, and the memory. The processor can check whether a user is in an inactive state using the situation sensing module, check reference biometric data corresponding to the inactive state if the user is in the inactive state, extract biometric data of the user using the biometric sensor, and measure the blood pressure of the user on the basis of the extracted biometric data and the reference biometric data.

A method to detect and analyze cough parameters remotely and in the background through the user's device in everyday life. The method involves consecutive or selective execution of 4 stages, which solve a variety of the following tasks: Detection of coughing events in sound, in environmental noise. Separation of the sound containing the cough into the sound of the cough and the rest of the sounds, even when extraneous sounds occurred during the cough. Identify the user by the sound of the cough to prevent analyzing the sounds of the cough that do not belong to the user (for example when another person coughs nearby). Assessment of cough characteristics (wet/dry, severity, duration, number of spasms, etc.). The method can work on wearable devices, smart devices, personal computers, laptops in 24/7 mode or in a selected range of time, and has a high energy efficiency.