A leadless implantable medical device (IMD) and method of using same are provided. The IMD comprises: a housing, a fixation element, electrodes configured to sense electrical cardiac activity (CA) signals over a period of time, an HS sensor configured to sense HS signals over the period of time, memory to store specific executable instructions, and one or more processors. The one or more processors and method: identify a characteristic of interest (COI) of a heartbeat from the CA signals, calculate a center of mass (COM) for at least one HS based on the HS signals to obtain a corresponding at least one HS COM, and calculate at least one of a therapy-related (TR) delay or a sensing-related (SR) blanking interval (BI) based on the at least one HS COM.

A leadless implantable medical device (IMD) and method of using same are provided. The IMD comprises: a housing, a fixation element, electrodes configured to sense electrical cardiac activity (CA) signals over a period of time, an HS sensor configured to sense HS signals over the period of time, memory to store specific executable instructions, and one or more processors. The one or more processors and method: identify a characteristic of interest (COI) of a heartbeat from the CA signals, calculate a center of mass (COM) for at least one HS based on the HS signals to obtain a corresponding at least one HS COM, and calculate at least one of a therapy-related (TR) delay or a sensing-related (SR) blanking interval (BI) based on the at least one HS COM.

A system and method for monitoring heart function based on heart sounds (HS) is provided. The system includes electrodes configured to sense electrical cardiac activity (CA) signals over a period of time. An HS sensor is configured to sense HS signals over the period of time. The system includes memory to store specific executable instructions and includes one or more processors that, when executing the specific executable instructions, is configured to: identify a characteristic of interest (COI) of a heartbeat from the CA signals. The processors overlay a HS search window onto an HS segment of the HS signals based on the COI from the CA signals and calculate a center of mass (COM) for at least one of S1 or S2 HS based on the HS segment of the HS signals within the search window to obtain a corresponding at least one of S1 COM or S2 COM. The processors calculate at least one of an electromechanical activation time (EMAT) or a systolic interval (SI) based on the at least one of S1 COM or S2 COM and record the at least one of the EMAT or SI.

A system and method for monitoring heart function based on heart sounds (HS) is provided. The system includes electrodes configured to sense electrical cardiac activity (CA) signals over a period of time. An HS sensor is configured to sense HS signals over the period of time. The system includes memory to store specific executable instructions and includes one or more processors that, when executing the specific executable instructions, is configured to: identify a characteristic of interest (COI) of a heartbeat from the CA signals. The processors overlay a HS search window onto an HS segment of the HS signals based on the COI from the CA signals and calculate a center of mass (COM) for at least one of S1 or S2 HS based on the HS segment of the HS signals within the search window to obtain a corresponding at least one of S1 COM or S2 COM. The processors calculate at least one of an electromechanical activation time (EMAT) or a systolic interval (SI) based on the at least one of S1 COM or S2 COM and record the at least one of the EMAT or SI.

A method and a system of alerting and/or monitoring patient with sleep disorder includes: a detector for detecting a change in a first parameter, a storage device, a control unit for deciding if the change meets a set criteria, and if the change meets the set criteria, saving the first parameter and/or time in the storage device, a feedback unit for adjusting the set criteria according to sleep behavior of the patient, and an alarm device for sending an alarm, wherein the first parameter includes sound, motion, heart rate, blood pressure, breathing frequency, magnitude and/or frequency of movement, muscle activity, brain activity, eye movements, heart rhythm, heart rate variability, blood oxygen levels, breathing pattern, and/or body position.

A device for determining the physiological condition of a person in a simple manner, which device measures the pulse rate and based on that additionally determines the heart rate variability. In addition, at least one parameter should be used for the history of one of the two above-mentioned values. The deviation of the pulse rate and the heart rate variability from a normal variable is preferably integrated and used as an additional indicator. The device preferably includes a wearable electrocardiography device.

The present invention relates to a smart mobile cart for nursing and caring that includes a pole assembly, a flexible gooseneck tube arm and a vital sign sensing device. The flexible gooseneck tube arm has two ends, one of which the two ends is connected with the pole assembly and another end is configured with a device connector. A mobile device is attached to the smart mobile cart through the device connector. The vital sign sensing device is placed on the smart mobile cart through a device convenient carrier. The pole assembly, the flexible gooseneck tube arm, and the device convenient connector are configured to have a ground height adjustable above from a ground level, so as to provide the mobile device and the vital sign sensing device at different ground clearances respectively for a user to operate.

A biological information measuring device comprises: a plurality of sensors that each acquire a base signal containing biological information and noise information; and a processing device that acquires biological information on the basis of a plurality of base signals. The processing device comprises: a component analysis part that performs a prescribed component analysis on the basis of the plurality of base signals and generates a plurality of component signals which constitute the plurality of base signals; and a biological information acquisition part that determines whether a component signal is biological information.

The present invention discloses a method for determining a degree of response to a physical activity. Acquire a physical activity signal measured by a sensing unit in the physical activity. Determine first data of a first physical activity feature set based on the physical activity signal. Determine a recognition of the degree of response to the physical activity based on the first data of the first physical activity feature set by a mathematical model describing a relationship between the first physical activity feature set and the degree of response to a physical activity. A portion of a first mechanism of the mathematical model adopts at least one portion of a second mechanism of a first neural network model associated with the second physical activity feature set.

A wireless, patient-worn, physiological sensor configured to, among other things, help manage a patient that is at risk of forming one or more pressure ulcers is disclosed. According to an embodiment, the sensor includes a base having a top surface and a bottom surface. The sensor also includes a substrate layer including conductive tracks and connection pads, a top side, and a bottom side, where the bottom side of the substrate layer is disposed above the top side of the base. Mounted on the substrate layer are a processor, a data storage device, a wireless transceiver, an accelerometer, and a battery. In use, the sensor senses a patient's motion and wirelessly transmits information indicative of the sensed motion to, for example, a patient monitor. The patient monitor receives, stores, and processes the transmitted information.