The present invention provides a carotid blood pressure detection device, comprising: a first sensing unit, a second sensing unit, and a controller connected or coupled to the first sensing unit and the second sensing unit. The first sensing unit is disposed on a subject's neck and adjacent to a first position of the subject's carotid arteries. The second sensing unit is disposed on the subject's neck and adjacent to a second position of the subject's carotid arteries. The controller derives a mean arterial pressure of a section of the subject's carotid arteries that lies between the first position and the second position of the subject's carotid arteries from pulse wave data measured and obtained by the first sensing unit and pulse wave data measured and obtained by the second sensing unit.

The invention is a device, system, and method for providing an initial assessment of potential heart valve disease and recommending and/or providing follow-up assessments for heart valve disease. The invention includes a simple ECHO device which uses ultrasonic signals to detect and determine maximum blood flow velocities, and compares the maximum blood flow velocities to set thresholds to determine if it is appropriate for the patient to be subjected to additional and more detailed assessments for heart valve disease.

A cardiovascular detection system and method, comprising an active compression cuff contracting at a frequency higher than the systolic frequency of the heart. Meanwhile, the detection device is used to capture the influence of the active compression cuff and cardiac systole on the blood of the part to be detected. In addition, it is supplemented by electrocardiography to monitor the reference value of cardiac systole to distinguish the difference between the pulse wave generated by the active compression cuff and the pulse wave generated by the heart. In this way, the state of the cardiovascular system can be quickly understood. Since the active compression cuff is contracted at a frequency higher than the systolic frequency of the heart, it can be more accurately determined whether the blood vessel is blocked or hardened.

A method of managing a medical suction device through a network may be embodied by the management server through the steps of: storing operation information of at least one medical suction device in a storage unit provided in the management server, generating an operation start determination reference value of the medical suction device based on the operation information, receiving information on conditions of a patient from a medical suction device installed at an outside, and determining whether to start an operation of the medical suction device that has transmitted the information on conditions of the patient based on the operation start determination reference value and the information on conditions of the patient.

A method of managing a medical suction device through a network may be embodied by the management server through the steps of: storing operation information of at least one medical suction device in a storage unit provided in the management server, generating an operation start determination reference value of the medical suction device based on the operation information, receiving information on conditions of a patient from a medical suction device installed at an outside, and determining whether to start an operation of the medical suction device that has transmitted the information on conditions of the patient based on the operation start determination reference value and the information on conditions of the patient.

Embodiments of the present disclosure relate to heart sound measurements using mobile devices. In an embodiment, a medical system for monitoring heart sounds of a subject comprises a medical device configured to obtain, during a first sampling interval, a first physiological signal. The medical system further comprises a mobile device comprising an accelerator, wherein the accelerator is configured to obtain, during a second sampling interval, a second physiological signal. And, the medical system comprises an analysis component configured to extract heart sounds data from the second physiological signal.

Embodiments of the present disclosure relate to heart sound measurements using mobile devices. In an embodiment, a medical system for monitoring heart sounds of a subject comprises a medical device configured to obtain, during a first sampling interval, a first physiological signal. The medical system further comprises a mobile device comprising an accelerator, wherein the accelerator is configured to obtain, during a second sampling interval, a second physiological signal. And, the medical system comprises an analysis component configured to extract heart sounds data from the second physiological signal.

A wearable stethoscope includes a sound sensing device for collecting heart sound signals of the body, an electrocardiogram sensing device for collecting electrocardiogram signals of the body, a processing unit, powered by a power source, coupled to the sound sensing device and the electrocardiogram sensing device to perform data preprocessing on the above-mentioned signals to remove background noise. An external electronic computing device is set up to analyze and process the fed pre-processed ECG signal and heart sound signal, perform feature extraction in combination with the user's physiological parameters and medical records to obtain related feature vectors, input the feature vectors into a screening model, obtain an evaluation value and give corresponding suggestions. After screening, users can upload the verification results to the cloud database to expand the existing training samples for further optimizing the parameters of the screening model.

A wearable stethoscope includes a sound sensing device for collecting heart sound signals of the body, an electrocardiogram sensing device for collecting electrocardiogram signals of the body, a processing unit, powered by a power source, coupled to the sound sensing device and the electrocardiogram sensing device to perform data preprocessing on the above-mentioned signals to remove background noise. An external electronic computing device is set up to analyze and process the fed pre-processed ECG signal and heart sound signal, perform feature extraction in combination with the user's physiological parameters and medical records to obtain related feature vectors, input the feature vectors into a screening model, obtain an evaluation value and give corresponding suggestions. After screening, users can upload the verification results to the cloud database to expand the existing training samples for further optimizing the parameters of the screening model.

Systems and methods for monitoring patients with a chronic disease are described. A patient management system may sense physiological signals from a patient using one or more implantable or other ambulatory sensors, and generate from the physiological signals a chronobiological rhythm indicator (CRI) such as indicating a circadian rhythm. A reference CRI associated with a prior hospital admission event of the patient may be provided to the patient management system, which compares the CRI to the reference CRI and generates a readmission risk score indicating the patient's risk of subsequent hospital readmission due to a worsened condition of the chronic disease. The readmission risk score may be provided to a user or a process, or used to initiate or adjust a therapy delivered to the patient.