Abstract: Method for determining a blood pressure value including the steps of: providing a pulsatility signal, determining a time-related feature and a normalized amplitude-related feature on the basis of the pulsatility signal; and calculating a blood pressure value on the basis of a blood pressure function depending on the time-related feature, the normalized amplitude-related feature and function parameters.

Abstract: A method for determining a physiological parameter, including: providing a PPG sensor device configured to measure a PPG signal; measuring a PPG signal on the user, the PPG signal containing at least two cardiac cycles; identifying PPG pulses from the PPG signal, each corresponding to a cardiac cycle and having a non-modulated component and a time-modulated component; for each PPG pulse, determining at least one venous-related feature indicative of the contribution of venous pulsatility to the time-modulated component of the PPG pulse; assigning a weighting factor to each pulse including calculating the weighting factor by using a weighting function including a mathematical operator inputted with the set of at least one venous-related feature; computing a weighted-average PPG pulse by using the PPG pulses and their respective weighting factors; and determining the physiological parameter by using the weighted-average PPG pulse.

Abstract: A method based on pulse wave analysis for monitoring cardiovascular vital signs, including: measuring a photoplethysmography (PPG) signal during a measurement time period such as to obtain a time series of PPG pulses; and during the measurement time period, identifying individual PPG pulses in the PPG signal, each PPG pulse corresponding to a PPG pulse cycle. For each PPG pulse, the method uses a pulse-wave analysis technique to determine, within the pulse cycle, at least one of: a time-related feature comprising a time duration and a normalized amplitude-related pulse-related feature and a SNR-related pulse-related. For each PPG pulse, a machine learning model is used in combination with the determined time-related, normalized amplitude-related and SNR-related features, to classify each PPG pulse in the pre-processed PPG signal as “normal”, “pathological” or “non-physiological” such as to output a time series of pulse classes.

Abstract: A wearable measuring system configured for determining a blood pressure of a user, including: a first measuring unit including a PPG sensor, a first voltage measuring electrode and a first current injecting electrode; and a second measuring unit including a second voltage measuring electrode and a second current injecting electrode. The first measuring unit is removably attachable to a user's body first location such that a PPG signal can be measured by a PPG sensor at the first location, and the second measuring unit is removably attachable to a user's body second location, such that an ECG and an ICG signal can be measured between the first and second locations. The wearable measuring system further includes a signal processing module configured for processing the measured ECG, ICG and PPG signals to determine a blood pressure value.

Abstract: A method for estimating blood pressure (BP) values comprises: measuring at a first PTT value, a second PTT value, and further PTTref values using a method comprising measuring a first arterial pressure pulse arrival time (PAT) and measuring a second PAT value; calculating a PTT value from the difference between the first PAT value and the second PAT value; processing a sequence of electrical impedance tomography (EIT) images to identify at least one region of interest (ROI); and estimating at least one of the first and second PAT value from the variation of impedance value determined from the at least one ROI. The method allows for the non-invasive and continuous determination of the PB values by using a calibration factor.

Abstract: Devices and methods for detecting meal intake are disclosed herein. In some embodiments, one or more sensors can be used to detect or monitor physiological parameters of a user (e.g., heart rate, body movements, temperature, pH, impedance, gastric stretch, sound emissions, and the like). The outputs of the sensors can be received by a computer system configured to analyze the sensor data and make a determination as to whether meal intake has occurred or is presently occurring. The computer system's determination can be used to trigger, modulate, or otherwise control one or more therapeutic devices. Other types of devices can also be controlled using this determination, such as monitoring or logging devices.

Abstract: Devices and methods for detecting meal intake are disclosed herein. In some embodiments, one or more sensors can be used to detect or monitor physiological parameters of a user (e.g., heart rate, body movements, temperature, pH, impedance, gastric stretch, sound emissions, and the like). The outputs of the sensors can be received by a computer system configured to analyze the sensor data and make a determination as to whether meal intake has occurred or is presently occurring. The computer system's determination can be used to trigger, modulate, or otherwise control one or more therapeutic devices. Other types of devices can also be controlled using this determination, such as monitoring or logging devices.

Abstract: A method for estimating blood pressure (BP) values comprises: measuring at a first PTT value, a second PTT value, and further PPT values using a method comprising measuring a first arterial pressure pulse arrival time (PAT) and measuring a second PAT value; calculating a PTT value from the difference between the first PAT value and the second PAT value; processing a sequence of electrical impedance tomography (EIT) images to identify at least one region of interest (ROI); and estimating at least one of the first and second PAT value from the variation of impedance value determined from the at least one ROI. The method allows for the non-invasive and continuous determination of the PB values by using a calibration factor.

Abstract: Devices and methods for detecting meal intake are disclosed herein. In some embodiments, one or more sensors can be used to detect or monitor physiological parameters of a user (e.g., heart rate, body movements, temperature, pH, impedance, gastric stretch, sound emissions, and the like). The outputs of the sensors can be received by a computer system configured to analyze the sensor data and make a determination as to whether meal intake has occurred or is presently occurring. The computer system's determination can be used to trigger, modulate, or otherwise control one or more therapeutic devices. Other types of devices can also be controlled using this determination, such as monitoring or logging devices.

Abstract: Devices and methods for detecting meal intake are disclosed herein. In some embodiments, one or more sensors can be used to detect or monitor physiological parameters of a user (e.g., heart rate, body movements, temperature, pH, impedance, gastric stretch, sound emissions, and the like). The outputs of the sensors can be received by a computer system configured to analyze the sensor data and make a determination as to whether meal intake has occurred or is presently occurring. The computer system's determination can be used to trigger, modulate, or otherwise control one or more therapeutic devices. Other types of devices can also be controlled using this determination, such as monitoring or logging devices.

Abstract: Method for determining a blood pressure value including the steps of: providing a pulsatility signal, determining a time-related feature and a normalized amplitude-related feature on the basis of the pulsatility signal; and calculating a blood pressure value on the basis of a blood pressure function depending on the time-related feature, the normalized amplitude-related feature and function parameters.

Abstract: Devices and methods for detecting meal intake are disclosed herein. In some embodiments, one or more sensors can be used to detect or monitor physiological parameters of a user (e.g., heart rate, body movements, temperature, pH, impedance, gastric stretch, sound emissions, and the like). The outputs of the sensors can be received by a computer system configured to analyze the sensor data and make a determination as to whether meal intake has occurred or is presently occurring. The computer system's determination can be used to trigger, modulate, or otherwise control one or more therapeutic devices. Other types of devices can also be controlled using this determination, such as monitoring or logging devices.

Abstract: Devices and methods for detecting meal intake are disclosed herein. In some embodiments, one or more sensors can be used to detect or monitor physiological parameters of a user (e.g., heart rate, body movements, temperature, pH, impedance, gastric stretch, sound emissions, and the like). The outputs of the sensors can be received by a computer system configured to analyze the sensor data and make a determination as to whether meal intake has occurred or is presently occurring. The computer system's determination can be used to trigger, modulate, or otherwise control one or more therapeutic devices. Other types of devices can also be controlled using this determination, such as monitoring or logging devices.