177 results about "Lung sound" patented technology

The present invention relates to device, system and method for detecting a cardiac and / or respiratory disease of a subject. The proposed device comprises a sound input (20) for obtaining a sound signal representing sounds generated by the subject's body; a motion input (21) for obtaining a motion signal representing motions generated by the subject's body; and a processor (22) for processing the obtained sound signal and motion signal. This processing includes identifying inhalation and / or exhalation periods of the subject based on the motion signal, detecting abnormal lung sounds during inhalation and / or exhalation periods based on the sound signal, determining abnormal lung sound characteristics of the detected abnormal lung sounds, determining breathing characteristics of the subject's breathing based on the sound signal, determining the phase of the abnormal lung sounds in the inhalation-exhalation cycle, and detecting a cardiac and / or respiratory disease of the subject based on the determined abnormal lung sound characteristics, the determined breathing characteristics and the determined phase of the abnormal lung sounds in the inhalation-exhalation cycle.

A lung sound diagnostic system for use in collecting, organizing and analyzing lung sounds associated with the inspiration(s) and expiration(s) of a patient. The system includes a plurality of transducers that may be placed at various sites around the patient's chest. The microphones are coupled to signal processing circuitry and A / D converters which digitize the data and preferably provides the digital data to a computer station. A data collection and organization program, executing on the computer station, organizes and formats the data into a combination display for display or printing. The combinational display includes at least two display elements. In a first display element, the data is shown for both inspiration and expiration combined in a first time scale. In a second display element, the data for inspiration and expiration are shown individually in a second time scale that is time-expanded relative to the first time scale. The system may also include application programs for detecting and classifying abnormal sounds. The resulting information may be displayed in a variety of formats to facilitate diagnosis. Additionally, the system may include an analysis program for comparing selected criteria corresponding to the detected abnormal sounds with predefined thresholds in order to provide a likely diagnosis.

Adventitious lung sounds indicative of lung congestion are detected using an implantable sensor. The sensor is adapted to be positioned adjacent to a pulmonary system and to output signals indicative of lung sounds in response to pulmonary system activity. A controller receives the signals and processes the signals to detect the presence of adventitious lung sounds. A respiratory cycle sensor operating in conjunction with the lung-sound sensor enables classification of an adventitious lung sound according to its time occurrence within the respiratory cycle. Posture sensing in conjunction with lung-sound sensing provides valuable additional information as to the severity of the lung congestion.

The invention relates to a heart-lung sound signal classification method, a detection method, a medium and a computer device. The heart-lung sound signal classification method includes the steps of acquiring a heart-lung sound signal to be classified, and converting the heart-lung sound signal by using a time-frequency analysis method to obtain a time-frequency signal; and performing dimensionality reduction on the time-frequency signal by using a matrix decomposition method to obtain an independent component signal; processing the independent component signal according to time-frequency masktechnology to obtain a heart sound spectrum signal and a lung sound spectrum signal; and performing inverse transform corresponding to the time-frequency analysis method on the heart sound spectrum signal and the lung sound spectrum signal to obtain a heart sound signal and a lung sound signal. In this way, the classification of the heart sound signal and the lung sound signal in the heart-lung sound signal can be realized by means of signal processing, the refined independent examination and analysis of the heart sound signal and the lung sound signal are facilitated, manual auscultation is unnecessary, examination items for heart and lung diseases can be simplified, and the efficiency of heart and lung disease examination can be therefore increased.

A system and method are provided for diagnosis of bovine respiratory diseases using auscultation techniques wherein the acoustic characteristics of a recorded spectrogram is compared with existing data enabling a caregiver to make a diagnosis for a diseased animal. Lung sounds are obtained by use of an electronic stethoscope, and the sounds are stored as digital data. Signal conditioning is used to place the data in a desired format and to remove undesirable noise associated with the recorded sounds. An algorithm is applied to data, and lung scores are calculated. The lung scores are then categorized into various levels of perceived pathology / disease within the animal based upon baseline data that categorizes the lung scores. From the lung scores, a caregiver may then associate a diagnosis, prognosis, and a recommended treatment. Analysis software in the present invention generates the lung scores from the recorded sounds, and may also provide the user a visual display of presumptive diagnoses as well as recommended treatments.

A device for sensing lung sounds, comprising: a piezoelectric sensor comprising an electrical conductive plate attached to a piezoelectric material, said sensor encased in a body structure; a first electric wire connected to the piezoelectric material on the opposite side of said plate; a second electric wire connected to said plate; a connector connected to the other ends of said first and second electric wires; and an adhesive layer connected to the surface of said plate on the side opposite to the piezoelectric material, said adhesive layer facing away from said plate; said device adapted to provide electrical signals representing vibrations present on the surface of a object when it is attached to said object surface with said adhesive layer; said electrical signals resulting from vibrations on the object surface, wherein stress applied on the piezoelectric material generates electrical voltage-difference on both sides of the piezoelectric material, creating voltage build-up on said first and second electric wires.

The present invention relates to a lung sound classification method, system and application based on a convolutional neural network. An image identification convolutional neural network is applied tolung sound classification, a general model is used to solve huge defects that a traditional algorithm has manual extraction of features and join experience limitation conditions and cannot be generally suitable for all the samples, and solve problems that a traditional algorithm cannot be enhanced with a data set and cannot be subjected to autonomic learning enhancement.

The invention discloses a soft close-fitting intelligent health monitoring vest, and belongs to the field of health monitoring equipment. The scheme includes that a flexible printed circuit board is arranged at a front chest of a vest body, a sensor module, a control core device and a key module are arranged on the flexible printed circuit board, the sensor module which is in contact with the skins of a wearer is provided with non-sticky conductive rubber jackets, and portions, except for the sensor module, of the flexible printed circuit board are in contact with the skins of the wearer via lint after being insulated and isolated; the sensor module is used for monitoring electrocardiogram signals, heart and lung sound signals and body temperature signals and transmitting the electrocardiogram signals, the heart and lung sound signals and the body temperature signals to the control core device; external instruments can be transmitted to the control core device by the key module; data can be exchanged between the control core device and a mobile phone in a wireless mode, can be uploaded to a cloud data management system by the mobile phone and can be called by doctors or users or family members. The soft close-fitting intelligent health monitoring vest has the advantages that the soft close-fitting intelligent health monitoring vest which is an intelligent health monitoring garment can be used by old people, old people can wear the intelligent health monitoring garment comfortably, influence on normal life can be prevented, and the intelligent health monitoring garment is free of maintenance or complicated operation; the vest is used for monitoring the health of old and weak people.

A network-type instrument for detecting blood pressure, cardiac rhythm, body temp and cardiopulmonary murmur is composed of power supply, CPU, information acquisition unit, information processing unit, operating unit, display unit, loudspeaker and communication unit. Said information can be displayed on display device or transmitted via network to remote monitor center.

The invention discloses an auscultation system for heart and lung sound separation based on deep learning; bone conduction is used for auscultation. The auscultation device includes an auscultation head, a signal acquisition module, a heart and lung sound signal separation module, a memory, a user interface, an output driving unit and a bone conduction unit. The signal acquisition module acquires heart and lung sound signals and digitizes the heart and lung sound signals, and the heart and lung sound signal separation module adopts a time-frequency masking deep circulatory neural network for heart and lung sound signal separation; the user interface can select heart-lung sound modes and store expert tags. The output driving unit receives heart or lung sound time-domain signals separated from previous stage for power amplification, and drives the bone conduction unit to generate vibration. The auscultator can automatically separate clean heart and lung sounds from the overlapped heart and lung sounds, facilitate data acquisition and post-analysis, and enhance the auscultation experience.