A61B7/00

Method and apparatus for monitoring respiratory distress based on autonomic imbalance

An example of a system for monitoring and treating respiratory distress in a patient may include signal inputs, a signal processing circuit, and a respiratory distress analyzer. The signal inputs may be configured to receive patient condition signals indicative of autonomic balance of the patient. The signal processing circuit may be configured to process the patient condition signals and to generate patient condition parameters indicative of the autonomic balance using the processed patient condition signals. The respiratory distress analyzer may be configured to determine a state of the respiratory distress using the patient condition parameters, and may include a parameter analysis circuit configured to analyze the autonomic balance of the patient and to determine the state of the respiratory distress using an outcome of the analysis.

Method of managing medical suction device through network and management server used for the same
11541162 · 2023-01-03 · ·

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.

Systems and methods for heart failure management

Systems and methods for managing heart failure are described. The system receives physiological information including a first HS signal corresponding to paced ventricular contractions and a second HS signal corresponding to intrinsic ventricular contractions. The system detects worsening heart failure (WHF) using the received physiological information. A signal analyzer circuit can generate a paced HS metric from the first HS signal and a sensed HS metric from the second HS signal, and determine a concordance indicator between the paced and the sensed HS metrics. In response to the detected WHF, the system can use the concordance indicator to generate a therapy adjustment indicator for adjusting electrostimulation therapy, or a worsening cardiac contractility indicator indicating the detected WHF is attributed to degrading myocardial contractility.

PIEZOELECTRIC SENSOR WITH RESONATING MICROSTRUCTURES
20220409095 · 2022-12-29 ·

A sensor system may have a force sensor formed from a piezoelectric film. The piezoelectric film may comprise a number of tuned microstructures that are configured to resonate at a particular frequency. In accordance with the tuning of the microstructures, frequency signals corresponding to the microstructure resonance may be mechanically amplified before being processed by associated processing electronics. The processing electronics may be configured to identify a type of biological vibration detected by the force sensor.

Using an In-Ear Microphone Within an Earphone as a Fitness and Health Tracker
20220409134 · 2022-12-29 ·

Trained machine learning models can be used for analysis of signals obtained through an in-ear or on-body device. Signals can be analyzed to determine information related to activities such as eating, chewing, drinking, coughing, or sneezing. In addition, data from an in-ear thermometer or other data sensors can be analyzed in conjunction with the machine learning models to provide data or recommendations to a user on a user device or initiate an action.

Using an In-Ear Microphone Within an Earphone as a Fitness and Health Tracker
20220409134 · 2022-12-29 ·

Trained machine learning models can be used for analysis of signals obtained through an in-ear or on-body device. Signals can be analyzed to determine information related to activities such as eating, chewing, drinking, coughing, or sneezing. In addition, data from an in-ear thermometer or other data sensors can be analyzed in conjunction with the machine learning models to provide data or recommendations to a user on a user device or initiate an action.

Enabling Ride Sharing During Pandemics
20220410930 · 2022-12-29 ·

The disclosed technology provides solutions for protecting the health of ride-sharing passengers by detecting passenger illnesses, and taking precautions to safely address potentially exposed vehicles. A process of the disclosed technology can include steps for: collecting sensor-data corresponding with one or more AV passengers, determining a likelihood that at least one of the AV passengers is suffering from a physical illness, and transmitting a wellness notification to a fleet management system if the likelihood exceeds a predetermined threshold. Systems and machine-readable media are also provided.

Device, system and method for detecting a cardiac and/or respiratory disease of a subject

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.

Earphones for measuring and entraining respiration

An earphone includes a loudspeaker, a microphone, a housing supporting the loudspeaker and microphone, and ear tip surrounding the housing and configured to acoustically couple both the loudspeaker and the microphone to an ear canal of a user, and to acoustically close the entrance to the user's ear canal. A processor provides output audio signals to the loudspeaker, receives input audio signals from the microphone, extracts a rate of respiration from the input audio signals, adjusts the output audio signals based on the extracted rate of respiration, and provides the adjusted output audio signals to the loudspeaker.

Method for operating snoring-preventing smart mattress system

The present invention relates to a method of operating a smart mattress system for preventing snoring which can stop snoring of a user, wherein an air mattress and an air pillow interlock with a user terminal so that a user can easily control the air mattress and the air pillow.